With the proliferation of connected objects (computers, tablets, watches, etc.), huge masses of data are generated every second. This Big Data has led to the emergence of a data economy, where data is the main source of competitive advantage for companies. In this sense, data and its processing tools have become a strategic priority for companies, and the main gas pedal of their digital transformation.

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This MOOC addresses the role of data in the digital transformation of organizations through 10 course sequences spread over 5 weeks and a wide variety of content:

- Slideshows and video-scribes explaining the impact of data on businesses, the digital transformation needed to capitalize on data, and the tools, methods and technologies needed to implement these data-driven strategies.
- Videos featuring testimonials from professionals and academics, highlighting through concrete examples the importance of data as a catalyst for digital transformation and a source of competitive advantage.
- Compulsory reading to complement the topics covered in the slides and video, in particular the challenges and benefits of data management as part of digital transformation.
- MCQs covering the entire content of each chapter.

A certificate is awarded for any grade above 50%.

This MOOC has received financial support from the Patrick & Lina Drahi Foundation.

Data intelligence for businesses and managers


This course delves into the various risks and concerns associated with Generative AI, including business model risks, inaccuracies in AI-generated content, data security, and privacy concerns.

It emphasizes the importance of the CEO in understanding and addressing these risks. A significant part of this course is dedicated to exploring the ethical considerations for using GenAI. It highlights the importance of developing responsible AI principles and practices, guiding CEOs in creating ethical principles for Responsible AI tailored specifically to their own companies. The course also focuses on the critical issues of data security and privacy in the use of GenAI. It concludes by providing an overview of the legal and regulatory landscape for GenAI, offering guidance on how to navigate this landscape effectively and ensure legal and regulatory compliance in the use of GenAI.

Navigating Generative AI Risks for Leaders


In this 1-hour long project-based course, you will learn how to create interpretable machine learning applications on the example of two classification regression models, decision tree and random forestc classifiers. You will also learn how to explain such prediction models by extracting the most important features and their values, which mostly impact these prediction models. In this sense, the project will boost your career as Machine Learning (ML) developer and modeler in that you will be able to get a deeper insight into the behaviour of your ML model. The project will also benefit your career as a decision maker in an executive position, or consultant, interested in deploying trusted and accountable ML applications.

2-hour course, including time of video recordings, practicing and readings, taking the quiz.

Interpretable Machine Learning Applications: Part 1


As leaders in your chosen field, you need to not only know how to ask the right questions but also answer them using data-based methods. Through this class, you will be able to get to the bottom of what you really want to know, describe the associated data related to that question, and visualize the information from that data to understand and explain the results.

This course can be taken for academic credit as part of CU Boulder’s Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder.

Defining, Describing, and Visualizing Data


Data Modeling in Power BI

This course forms part of the Microsoft Power BI Analyst Professional Certificate. This Professional Certificate consists of a series of courses that offers a good starting point for a career in data analysis using Microsoft Power BI.

In this course, you'll learn how to use Power BI to create and maintain relationships in a data model and form a model using multiple Schemas. You'll explore the basics of DAX, Power BI's expression language, and add calculations to your model to create elements and analysis in Power BI. You'll discover how to configure the model to support Power BI features for insightful visualizations, analysis, and optimization.

After completing this course you'll be able to:

●	Create and maintain relationships in a data model.
●	Form a model using a Star Schema
●	Write calculations DAX to create elements and analysis in Power BI
●	Create calculated columns and measures in a model
●	Perform useful time intelligence calculations in DAX
●	Optimize performance in a Power BI model

This is also a great way to prepare for the Microsoft PL-300 exam. By passing the PL-300 exam, you’ll earn the Microsoft Power BI Data Analyst certification.


In today's data-driven world, generating reports efficiently is a valuable skill for professionals across various industries. This course introduces beginners to the world of automated report generation using AI-powered tools and techniques. You will learn how to leverage the capabilities of artificial intelligence to streamline the reporting process, save time, and improve data accuracy.

By the end of this course, you will not only grasp foundational concepts but also have the skills to streamline your personal and professional life; whether it's tracking and reporting on your personal finances, health and wellness, home energy efficiency, or implementing automated reporting solutions for your company's sales or marketing, saving valuable time and resources while improving data accuracy and decision-making. Moreover, you'll have the knowledge and confidence to explore automation opportunities within your workplace, making you an asset in the digital transformation era.

Upon completing this course, learners can utilize AI-driven tools to generate automated reports, thereby improving productivity and data accuracy in their respective fields.

Audience: Office Professionals, Consultants, Students, Small Business Owners, Reporting and Automation Enthusiasts

To fully benefit from the " Introduction to Automated Report Generation with AI " course, learners should have basic computer skills, familiarity with software, an interest in data, analytics, and reporting, and access to a computer or device for practice.

Automated Report Generation with Generative AI


By completing this course, learners will be able to analyze structured datasets, apply Pivot Tables for meaningful summaries, design effective charts, interpret data using advanced visualization techniques, and perform dynamic calculations using Excel equations and intelligent analysis tools.

This Advanced Excel course is designed to help learners move beyond basic spreadsheet usage and develop strong analytical and visualization skills required in today’s data-driven roles. Learners will gain hands-on experience in understanding dataset structure, building Pivot Tables, and transforming raw data into clear, insightful charts. The course also explores advanced chart formatting, dataset parameters, and Excel’s smart features such as Analyze Data and recommended charts to enhance accuracy and efficiency.

What makes this course unique is its structured, outcome-driven approach that connects data preparation, visualization, and analysis into a single learning journey. Each concept is reinforced through practical examples that mirror real-world business scenarios, enabling learners to make confident, data-backed decisions. Whether for reporting, analytics, or dashboard creation, this course equips learners with practical Advanced Excel skills that are immediately applicable in professional environments.

Analyze & Visualize Data Using Advanced Excel


Advertising in the Age of Generative AI

The Advertising in the Age of Generative AI course provides you with the knowledge, skills, and tools needed to build and maintain a clear and strong brand that is distinguishable from the competition and builds customer loyalty, familiarity, and comfortability. This course will allow for you to appropriately practice using Generative AI to generate compelling and effective logos as part of a brand strategy. This course is ideal for marketing professionals looking to create and establish a strong brand identity for their organization and want to gain valuable insights on how Generative AI is used in brand awareness and logo generation.

University of Virginia Darden School Foundation


Develop the ability to analyze global currencies, evaluate exchange rate dynamics, and apply currency conversion techniques in real-world financial scenarios. This course equips learners with practical skills to interpret currency movements, solve multi-step conversion problems, and assess global financial implications with confidence.

Learners will gain a strong foundation in foreign exchange concepts, including currency identification, economic determinants, and global currency systems. Through structured examples, real-life case studies, and problem-solving exercises, the course enables learners to move from basic understanding to advanced application.

What makes this course unique is its hands-on, scenario-driven approach—combining conceptual clarity with practical problem-solving. Learners will engage with travel-based examples, multi-currency calculations, and assessment-style challenges that mirror real financial decision-making.

By the end of the course, learners will be able to confidently handle currency conversions, evaluate financial outcomes across currencies, and apply treasury-related insights in global business environments, making it highly valuable for finance professionals, students, and aspiring analysts.

Analyze & Apply Currency Conversion in Treasury


Master the skills to analyze financial statements and make informed corporate decisions in today’s dynamic business environment. Learn how to evaluate profitability, interpret financial reports, and apply economic principles to real-world scenarios.

This course provides a practical, hands-on approach to financial analysis, accounting, and corporate finance, helping you build job-ready skills used by financial analysts. You’ll learn how to structure income statements, analyze balance sheets, assess working capital, and evaluate key metrics like revenue recognition, inventory valuation, and earnings per share (EPS).

Unlike traditional courses, this program integrates economics, accounting, and financial decision-making, enabling you to connect theory with real business applications. Through structured frameworks and real-world examples, you will develop the ability to assess company performance and make strategic financial decisions.

By the end of this course, you will confidently interpret financial reports, evaluate investments, and support business strategy with data-driven insights.

Financial Statement Analysis & Corporate Finance Decisions


Master Excel VBA for financial modeling and automate complex finance workflows with real-world projects and simulations.
Learn how to build dynamic financial models, automate repetitive Excel tasks, and develop advanced analytical tools using VBA.

This hands-on course teaches practical VBA programming for finance professionals, analysts, and Excel users. Learners will create automated financial models, retirement planning systems, Monte Carlo simulations, GARCH-based stock forecasting models, and Asian option pricing tools. The course also covers debugging, user forms, add-in creation, data cleaning automation, and advanced Excel workflows.

By the end of the course, learners will confidently apply VBA to streamline financial analysis, improve reporting efficiency, and build scalable Excel-based financial solutions used in real business environments.

Financial Modeling with Spreadsheet Automation


Learn how to analyze mutual funds, ETFs, portfolio strategies, and investment risks using practical financial market concepts and industry-focused learning. This course provides a comprehensive understanding of mutual fund investing, taxation, debt funds, ETFs, portfolio metrics, and investor strategies used in modern financial markets.

The course begins with the foundations of mutual funds and the Indian mutual fund industry structure, helping learners understand diversification, fund participants, AMCs, custodians, registrars, and regulatory frameworks. Learners will build a strong understanding of how mutual funds operate and how investors participate in financial markets.

As the course progresses, learners explore equity mutual funds, index investing, large-cap diversification strategies, and portfolio performance metrics such as NAV, AUM, expense ratio, tracking error, and portfolio turnover. The course explains how professional investors evaluate fund performance and investment quality.

Advanced modules cover ETFs, Gold ETFs, exchange-based investing, market making, liquidity management, debt funds, bond pricing, yield concepts, interest rate risk, credit risk, and fixed maturity strategies. Learners will also understand taxation concepts such as indexation, dividend options, growth strategies, and regulatory investor protection mechanisms.

The course also emphasizes practical investment techniques including SIP, STP, SWP, dividend reinvestment, portfolio diversification, long-term wealth planning, and NCFM preparation strategies.

What makes this course unique is its comprehensive blend of mutual fund investing, ETF analysis, taxation, portfolio management, and practical market preparation. By the end of the course, learners will be able to confidently analyze mutual fund schemes, evaluate portfolio performance, apply investment strategies, and make informed financial decisions in real-world market environments.

Mutual Fund Investing and Market Preparation


Learn how to analyze budgeting processes, apply variance analysis techniques, and create MIS-based financial reports using practical business and Excel-driven approaches. This course provides hands-on skills in budgeting, cost control, financial performance evaluation, and management reporting for real-world decision-making.

The course begins with strong budgeting foundations, helping learners understand the role of budgeting in financial planning and organizational control. Learners will explore the differences between forecasting and budgeting, understand the characteristics of effective budgeting systems, and develop structured sales budgets used in business planning.

As the course progresses, learners build expertise in variance analysis by understanding how financial deviations are identified, interpreted, and used to evaluate performance. The course covers standard variance formulas and provides practical insights into material and labor cost variances for effective financial analysis and cost control.

Advanced modules focus on overhead variances and MIS reporting applications. Learners will analyze fixed and variable overhead variances and create variance analysis reports using Excel-based MIS techniques to support operational and strategic decision-making.

What makes this course unique is its integrated approach that combines budgeting, variance analysis, and MIS reporting into a single practical workflow. By the end of the course, learners will be able to confidently prepare budgets, interpret financial variances, create professional MIS reports, and apply financial analysis techniques in real business environments.

Budgeting and Variance Analysis Techniques


Prospecting and Selling Insurance

Prospecting and Selling Insurance focuses on effective strategies to sell insurance, from identifying potential customers to building long-lasting client relationships.

Throughout this course, you'll master various methods to find and generate leads, including prospecting and lead generation techniques. You'll explore how successful salespeople identify and connect with potential clients, and learn practical skills through hands-on lessons and activities.

The course will also delve into the sales process, where you'll gain expertise in consultation strategies, assessing customer needs,  presenting tailored insurance solutions, overcoming objections, and closing sales. By mastering these techniques, you’ll confidently guide customers towards the best insurance options available.

Finally, you'll focus on client retention and growth strategies. You'll discover how to keep clients satisfied, identify opportunities for upselling, and generate referrals. Through interactive lessons and real-world examples, you'll learn to apply these techniques to retain clients and expand your business.


Develop practical quantitative finance skills by learning how to analyze, apply, and evaluate financial data using SAS. This course introduces the essential statistical techniques and SAS procedures used to interpret financial datasets, assess market behavior, and support data-driven financial decision-making.

You will begin by exploring the SAS environment and applying descriptive statistics to financial data. As you progress, you will analyze datasets using T-Tests and correlation methods, then apply regression modeling and variance analysis to interpret statistical relationships and evaluate financial market behavior. Building on these foundations, you will use advanced SAS procedures to analyze economic datasets, forecast financial trends, and interpret real-world financial market data, including the BSE Sensex and foreign exchange markets.

This course is designed for learners who want to strengthen their quantitative finance and financial data analysis skills using SAS. Its practical approach emphasizes applying statistical methods to real financial and economic scenarios rather than focusing on theory alone. By the end of the course, you will be able to analyze financial datasets, apply SAS procedures, interpret statistical outputs, forecast financial trends, and evaluate financial risks with greater confidence.

Quantitative Finance with SAS: Apply, Analyze & Evaluate


Introduction to Personal Finance

This course is a general overview of a variety of personal finance topics - including budgeting, the importance of your credit score, cash flow, setting financial goals, and taxes.  Taught by two CERTIFIED FINANCIAL PLANNER™ Professionals, the concepts are broken down through videos, readings, and activities so you can apply what you are learning in real time. The course provides the foundation to build on for the rest of The Fundamentals of Personal Finance Specialization or as a standalone survey course to improve your understanding of basic personal finance terminology, as well as how they apply to your own financial situation.

Whether you are just starting college, nearing retirement, or somewhere in between, this course will provide you with the knowledge to understand your money and actionable steps to manage your finances in the future. This course is geared towards learners in the United States of America.


This course features Coursera Coach!

A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.

Master the core foundations of QuickBooks Online and gain the confidence to manage your business finances with clarity and control. In this course, you’ll learn how to navigate the interface, record daily transactions, manage customers and vendors, track inventory, and generate powerful financial reports. By understanding both the “how” and the “why” behind bookkeeping processes, you’ll develop practical accounting skills that directly support smarter business decisions.

You’ll begin with a beginner-friendly introduction to QuickBooks Online, exploring its interface and innovative features. Then, through a comprehensive bootcamp experience, you’ll move step-by-step from setup and customization to managing products, services, and chart of accounts. Along the way, you’ll optimize workflows using shortcuts, automation tools, and best practices to avoid common user errors.

As the course progresses, you’ll handle real-world scenarios including invoicing, receiving payments, managing expenses, working with bank feeds, reconciling accounts, and generating Profit & Loss and Balance Sheet reports. You’ll also explore advanced features like recurring transactions, job costing, journal entries, and AI-powered bank rules to improve efficiency and accuracy.

This course is ideal for small business owners, freelancers, aspiring bookkeepers, and administrative professionals who want hands-on control of their financial systems. No prior accounting experience is required, though basic computer literacy is recommended. The course is designed at a beginner level and progresses in a structured, practical manner.

By the end of the course, you will be able to confidently set up, manage, automate, and reconcile business transactions in QuickBooks Online while generating accurate financial reports for informed decision-making.

Introduction to QuickBooks Online & Setting Up Your Business


By the end of this course, learners will be able to identify the functions of financial markets, differentiate between equity, debt, and derivative instruments, evaluate the pros and cons of investment tools, and analyze the role of intermediaries, stock exchanges, and regulators in capital markets.

This comprehensive program is designed to give learners a practical and structured understanding of capital markets and financial instruments. Starting from foundational concepts, it explores equity, preference shares, debentures, derivatives, and mutual funds, while also covering the infrastructure, intermediaries, and processes that ensure smooth market operations.

Learners will benefit from step-by-step lessons, structured modules, practice quizzes, and graded assessments that reinforce knowledge and build confidence. The course uniquely combines conceptual clarity with applied insights, making complex topics like derivatives, corporate actions, and trade life cycles easy to understand and apply in real-world scenarios.

Whether you are an aspiring investor, finance student, or professional looking to strengthen your market knowledge, this course equips you with the ability to analyze, evaluate, and make informed investment decisions with confidence.

Capital Markets: Analyze, Evaluate & Invest


PHI-Ellipses and Fibonacci Trading

Master advanced technical analysis using PHI-Ellipses and Fibonacci trading strategies.
Learn how to identify high-probability trades with precision and confidence.

This course is designed to help traders move beyond basic indicators and develop a structured, reliable trading approach. You will learn how PHI-Ellipses dynamically adapt to price movements and how to combine them with Fibonacci tools, candlestick patterns, and chart structures.

Through practical examples, you will understand how to filter market noise, identify trend reversals, and improve entry and exit timing. The course focuses on combining multiple confirmations to increase trading accuracy while maintaining disciplined risk management.

By the end of this course, learners will be able to analyze market trends, apply advanced tools effectively, and build a robust trading strategy suitable for both short-term and long-term trading environments.


Financial Accounting Fundamentals

This course, developed at the Darden School of Business at the University of Virginia and taught by top-ranked faculty, will teach you the tools you'll need to understand the fundamentals of financial accounting. Concise videos, the financial records of a small business, and "your turn" activities guide you through the three most commonly used financial statements: the Balance Sheet, the Income Statement, and the Statement of Cash Flows. Beyond recording transactions, you'll learn how to prepare these financial statements, and read and analyze them to draw basic conclusions about a company's financial health.

By the end of this course, you will be able to:
- Use journal entries to record transactions
- Prepare and use t-accounts to summarize transactions recorded during an accounting period
- Describe the three most commonly used financial statements and how they fit together
- Prepare these financial statements based on transactions recorded during an accounting period
- Draw basic conclusions about a company's financial health


Payment Controls and Approvals

Did you know that organizations lose an average of 5% of their revenue annually due to fraud, with payment fraud being one of the most common schemes? This Short Course was created to help accounting professionals accomplish systematic verification of financial controls and authorization processes.

By completing this course, you'll be able to confidently explain the business rationale behind dual authorization systems, systematically verify transaction approvals using standardized checklists, and create clear documentation that supports internal control compliance. These skills will transform your ability to safeguard organizational assets and ensure regulatory adherence in your daily accounting operations.

By the end of this course, you will be able to:
Understand the rationale for dual authorization controls on high-value transactions
Apply a checklist to confirm proper approval on financial documents

This course is unique because it combines foundational control theory with hands-on verification practice, using real-world scenarios that mirror actual accounting department workflows and compliance requirements.

To be successful in this project, you should have a background in basic accounting principles and familiarity with financial document processing.


Learn how to analyze mutual fund structures, evaluate portfolio performance, and apply investment strategies to optimize risk and returns in modern financial markets. This course provides practical knowledge of mutual fund investing, asset allocation, performance analysis, risk evaluation, and portfolio management techniques.

The course begins with the foundations of mutual funds, helping learners understand mutual fund structures, benefits, key characteristics, and the roles of different participants involved in fund management and investment operations. Learners will build a strong conceptual understanding of how mutual funds support diversified investing and wealth creation.

As the course progresses, learners focus on portfolio construction and fund management techniques, including asset allocation strategies, fund categories, accounting principles, and performance evaluation methods. The course explains how equity, debt, and hybrid mutual funds are managed and assessed using real-world financial metrics.

Advanced modules cover portfolio performance measurement, risk analysis, and practical numerical applications. Learners will calculate returns, interpret expense ratios, compare benchmark performance, and evaluate mutual funds using structured analytical techniques and investment frameworks.

What makes this course unique is its comprehensive, application-driven approach that combines mutual fund fundamentals, portfolio analysis, risk evaluation, and practical calculations into one cohesive learning experience. By the end of the course, learners will be able to confidently evaluate mutual funds, analyze portfolio performance, assess risks, and make informed investment decisions aligned with financial goals.

Mutual Fund Performance and Risk Analysis


Digital Tools & Data Management

Every tax workpaper, every ONESOURCE entry, and every research note a CB1 tax analyst produces starts with the same foundation: knowing how to get data, structure it, use AI responsibly, and find the authoritative guidance that backs up your work. This course builds that foundation from the ground up.

Digital Tools & Data Management is the first long course in the Tax Analyst with AI Skills Professional Certificate. Across five short courses, you will build the everyday toolkit that carries forward into every later course in the program: constructing Excel tax support schedules that reconcile cleanly and withstand reviewer scrutiny, using AI tools including ChatGPT to draft summaries and checklists within approved data-handling limits, writing structured prompts using the OJSFC framework to produce reliable AI outputs for routine tax tasks, conducting defensible tax research using the hierarchy of tax authorities with AI as a framing tool rather than a citable source, and extracting trial balance and account activity data from ERP systems using crosswalk templates to map accounts to tax return lines.

No prior tax, AI, or ERP experience is required. You need only basic spreadsheet familiarity — entering formulas and navigating multiple tabs — to get started.

By the end of this course, you will be equipped to handle the foundational data and tool workflows that support every compliance task in a CB1 tax analyst role.


In this project, we will use Python to perform stocks analysis such as calculating stock beta and expected returns using the Capital Asset Pricing Model (CAPM). CAPM is one of the most important models in Finance and it describes the relationship between the expected return and risk of securities. We will analyze the performance of several companies such as Facebook, Netflix, Twitter and AT&T over the past 7 years. This project is crucial for investors who want to properly manage their portfolios, calculate expected returns, risks, visualize datasets, find useful patterns, and gain valuable insights. This project could be practically used for analyzing company stocks, indices or  currencies and performance of portfolio.

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Python for Finance: Beta and Capital Asset Pricing Model


Banking, Credit, and Consumer Debt

Money moves through your life every single day — through your bank account, your debit card, your credit score, and your monthly bills. Yet many people never stop to examine the systems behind those transactions or how understanding them could put more control back in their hands. In this course you'll take a clear-eyed look at the financial tools you use every day and learn how to use them more strategically, from managing a checking account to understanding what your credit score is really saying about you.

Your credit score can be the difference between getting approved or rejected, between a low interest rate and an expensive one. Your banking choices affect how quickly money moves, how much you pay in fees, and how protected you are when something goes wrong. And the true cost of borrowing is almost always higher than the rate you're quoted. This course gives you the knowledge to navigate all of it — not just to avoid costly mistakes, but to make the financial system work in your favor.


Accounting Data Entry Speedily

Did you know that efficient accountants can save up to 25% of their time each week by mastering data entry shortcuts and streamlined software workflows? Speed and accuracy together are what make financial record-keeping truly effective.

This Short Course was created to help accounting professionals accelerate data entry processes, improve accuracy, and enhance efficiency in financial record-keeping tasks.

By completing this course, you will be able to enter financial data quickly and correctly using keyboard shortcuts and accounting software tools, helping you complete expense entries and reporting tasks with greater confidence and precision.

By the end of this course, you will be able to:

- Recognize keyboard shortcuts for numeric data entry in spreadsheets.
- Apply accounting software to accurately enter expense data.

This course is unique because it focuses on practical speed and accuracy techniques, empowering you to boost productivity through smarter data entry methods that reduce errors and save valuable time in your accounting workflow.

To be successful in this project, you should have:
- Basic spreadsheet skills.
- Knowledge of QuickBooks or similar tools.
- Understanding of financial data formats.


Master brokerage operations and the complete trade lifecycle in financial markets. Learn how trades move from execution to settlement in real-world capital markets.

This course provides a comprehensive understanding of brokerage operations, covering trade processing, clearing, settlement, and reconciliation. You will explore key financial instruments such as equities, bonds, options, and derivatives while gaining practical insights into systems like CNS and DTC.

Designed for aspiring finance professionals, this course bridges the gap between theory and real-world operations. You will learn how brokerage firms function, how trades are executed and settled, and how risks are managed through margin and compliance processes.

By the end of this course, learners will be able to analyze trade workflows, apply operational concepts, and understand the infrastructure that powers global financial markets—making it ideal for careers in investment banking operations, middle office, and capital markets roles.Master brokerage operations and the complete trade lifecycle in financial markets. Learn how trades move from execution to settlement in real-world capital markets.

This course provides a comprehensive understanding of brokerage operations, covering trade processing, clearing, settlement, and reconciliation. You will explore key financial instruments such as equities, bonds, options, and derivatives while gaining practical insights into systems like CNS and DTC.

Designed for aspiring finance professionals, this course bridges the gap between theory and real-world operations. You will learn how brokerage firms function, how trades are executed and settled, and how risks are managed through margin and compliance processes.

By the end of this course, learners will be able to analyze trade workflows, apply operational concepts, and understand the infrastructure that powers global financial markets—making it ideal for careers in investment banking operations, middle office, and capital markets roles.

Financial Markets Operations and Settlement


Enforce Ethical Tax Practices

This course teaches tax professionals how to apply ethical safeguards when using AI in tax workflows. Learners will examine what information must never be entered into public AI tools, how to classify tax data by sensitivity, how to apply approved AI use controls in systems such as ONESOURCE and Excel-based workfiles, and how to respond to ethical concerns and potential breaches. The course is designed for early-career tax staff and other professionals who need practical, workflow-based guidance for protecting client confidentiality and maintaining professional integrity.

Course Learning Objectives
Explain why confidentiality and ethical controls are essential in modern tax practice
Distinguish between public AI tools and approved enterprise or internal AI environments
Classify tax-related information using a four-tier data classification model
Apply core AI use controls such as anonymization, draft labeling, source verification, human review, and documentation
Evaluate common ethical scenarios in tax work and identify appropriate responses
Follow reporting and escalation pathways for breaches, misstatements, policy violations, and workplace concerns


Basics of Accounting for Assets

This course provides a comprehensive understanding of key accounting principles related to assets. It covers topics such as revenue recognition, bad debt expense, and various inventory methods including FIFO, LIFO, and average cost. The course is designed to help learners comprehend how these concepts impact financial statements and the importance of matching costs with sales.

This short course is part of the previous Master Track Certificate in Business Essentials. You may also be interested in a related short course from this program, "The Basics of Accounting for Assets: Long-Term Assets."


Nossas boas-vindas ao Curso Riscos Financeiros (Crédito, Mercado e Liquidez).

Neste curso, você aprenderá sobre conceitos associados à seleção da carteira de investimento, à análise de retorno e riscos que são utilizados na gestão de carteiras e a conceitos sobre modelos utilizados na precificação e alocação dos ativos.

Ao final deste curso, você será capaz de:
- Reconhecer o risco e retorno de um ativo;
- Entender a teoria de carteira;
- Realizar o Apreçamento de ativo de capital;
- Mensurar a gestão e performance de risco.

Este curso é composto por quatro módulos, disponibilizados em semanas de aprendizagem. Cada módulo é composto por vídeos, leituras e testes de verificação de aprendizagem. Ao final de cada módulo, temos uma avaliação de verificação dos conhecimentos.

Estamos muito felizes com sua presença neste curso e esperamos que você tire o máximo de proveito dos conceitos aqui apresentados.

Bons estudos!


Master the fundamental building blocks of accurate financial record-keeping that every accounting professional needs. This course empowers you with essential double-entry bookkeeping knowledge to recognize normal account balances and execute precise month-end adjusting procedures using QuickBooks.

This Short Course was created to help accounting professionals accomplish reliable ledger maintenance and month-end closing procedures.

By completing this course, you'll be able to confidently identify whether major account categories carry debit or credit balances, calculate and record adjusting entries for accruals and prepaids, and ensure your general ledger remains balanced after posting transactions.

By the end of this course, you will be able to:
Recognize the normal debit or credit balance for major general ledger account categories.
Apply standard procedures to post month-end adjusting entries and balance the ledger.

This course is unique because it combines foundational accounting theory with hands-on QuickBooks practice, ensuring you develop both conceptual understanding and practical skills that translate directly to workplace success.

To be successful in this project, you should have a background in basic accounting concepts and access to QuickBooks.

Accounting: Balance Ledgers & Adjust Entries


AI Fundamentals in Financial Services

Artificial Intelligence (AI) is rapidly reshaping the financial services landscape. From fraud detection and algorithmic trading to customer service chatbots and credit scoring, AI is at the heart of a new era in finance. This course is designed to give you a clear, practical understanding of how AI works, what it enables, and how it’s transforming the way financial institutions operate.

Through real-world examples, case studies, and engaging learning activities, you’ll gain insights into the key technologies that make AI possible, including machine learning, deep learning, and natural language processing, and see how they are applied across core functions in banking, fintech, and asset management. You’ll also explore how data drives these systems, the different learning methods AI uses, and the implications for strategy, governance, and ethics.

Whether you’re a financial professional, policymaker, or simply curious about the future of finance, this course will equip you with the knowledge and confidence to engage in AI-related conversations and decision-making. No programming background is required, just an interest in how technology is shaping the future of financial services.

By the end of the course, you will be able to:

• Understand the foundational technologies that underpin Artificial Intelligence (AI), including Machine Learning, Natural Language Processing, and Deep Learning.
• Explore the central role of data in powering AI systems, and the key learning methods used to train them.
• Identify how AI is applied in financial services, including use cases such as fraud detection, credit scoring, customer service, and algorithmic trading.
• Critically evaluate the risks, limitations, and ethical challenges associated with deploying AI in financial services.

This course is the first in the AI in Financial Services: Foundations through Future Trends specialization. It provides the essential groundwork for understanding how AI works and why it matters in finance. After completing this course, we recommend continuing with 'Designing the Future of Finance' and 'Open Data and Intelligent Finance' courses to explore how AI intersects with Open Finance, embedded systems, and intelligent, ethical financial innovation.

Saïd Business School, University of Oxford


Plant Design & Economics

This course covers essential aspects of plant design and process optimization, focusing on their impact on cost and efficiency. Learners will explore strategies to improve process efficiency, understand methods for budgeting and financial planning, and learn how process simulation can enhance plant models. The course also addresses project management principles crucial for successful plant projects and essential safety considerations to ensure the well-being of personnel and compliance with regulations. Designed for engineers, plant managers, and industry professionals, this course equips participants with the knowledge to apply theoretical concepts practically, modernizing operations and improving economic performance.

This course is designed for engineers, plant managers, and industry professionals who are eager to deepen their understanding of plant design and process optimization. It is ideal for individuals looking to improve their plant's economic performance and stay ahead of industry trends. Whether you're a newcomer to these concepts or an experienced professional seeking to refine your skills, this course provides practical knowledge and strategies that are relevant to modernizing and optimizing plant operations.

No prior knowledge or experience is required to participate in this course. It is suitable for beginners who are interested in learning about plant design and process optimization, as well as for professionals seeking to enhance their expertise. The course is structured to accommodate a range of experience levels, ensuring that all participants can effectively engage with and benefit from the material presented.

By the end of this course, you will be equipped to describe core plant design and optimization concepts, understanding the fundamental principles that drive plant efficiency and operational performance. You will be adept at assessing how these principles can be applied to enhance economic outcomes and improve real-world scenarios. Additionally, you will develop and implement strategies for optimizing plant operations, ensuring alignment with industry trends and economic goals. Finally, you will gain the ability to recognize and address common challenges in plant design and process optimization, effectively resolving issues to achieve superior plant performance.


This course focuses on advanced DAX (Data Analysis Expressions) concepts and performance optimization techniques essential for Power BI developers. Participants will learn to write complex DAX formulas, create calculated columns and measures, and implement sophisticated business logic. The course emphasizes performance optimization methodologies and troubleshooting techniques to ensure reports are efficient and responsive. By leveraging tools like Performance Analyzer and DAX Studio, learners will diagnose and resolve common performance issues.

Advanced DAX and Performance Optimization


Updated in May 2025.

This course now features Coursera Coach!

A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.

Unlock the advanced capabilities of Oracle RMAN in this comprehensive course tailored for database administrators and IT professionals. This program equips you with the skills to efficiently manage Oracle databases through RMAN’s specialized features, covering database duplication, performance optimization, and integration with multitenant and RAC environments. Practical exercises and demonstrations ensure a hands-on learning experience to reinforce theoretical concepts.

The journey begins with exploring database duplication techniques using RMAN, covering various methods like active duplication and backup-based duplication, both with and without recovery catalog connections. As you advance, you'll delve into troubleshooting RMAN processes, interpreting diagnostics, and fine-tuning performance using techniques like asynchronous I/O and multiplexing.

The course then transitions to RMAN operations in Oracle multitenant and RAC environments. Learn to back up and recover Container Databases (CDBs) and Pluggable Databases (PDBs), manage complex recovery scenarios, and optimize RMAN usage in RAC setups. Conclude with a dive into Oracle Database Backup Cloud Service, from configuration to secure backup storage in the cloud.

This course is ideal for Oracle database administrators and IT professionals looking to elevate their expertise in RMAN. A basic understanding of Oracle databases and RMAN is recommended, with the content suited for intermediate-level learners seeking advanced techniques.

Specialized RMAN Features and Advanced Use Cases


Essential Concepts of Vector Databases

Updated in May 2025.

This course now features Coursera Coach!

A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.

In this comprehensive course, you will gain a deep understanding of vector databases, their structure, and how they differ from traditional databases. By exploring fundamental concepts, including their benefits and real-world applications, you will be equipped with the knowledge needed to leverage these cutting-edge technologies in data management and AI.

The course begins with an introduction to vector databases, explaining why they have become essential in modern data management. You will discover their key advantages and how they address limitations found in traditional databases. Moving forward, the course dives into embeddings and vectors, key components in understanding the data flow within vector databases, and the importance of similarity searches.

Next, the course covers a hands-on section where you will work with the Chroma vector database. Through practical exercises, you will learn how to set up your development environment, create databases, query data, and manage embeddings with OpenAI APIs. Additionally, the course explores advanced topics like vector similarity measures, including cosine similarity, Euclidean distance, and dot product, as well as the integration of vector databases with large language models (LLM).

This course is ideal for developers, data scientists, and anyone keen on understanding the cutting-edge field of vector databases. A solid grasp of databases and basic programming knowledge will be beneficial for mastering the material.


Containerization is more than a deployment tool—it’s the backbone of reliable, scalable machine learning systems. In this intermediate-level course, you’ll learn how to package, deploy, and manage ML models using Docker and Kubernetes. You’ll start by exploring why containerization matters—how it ensures reproducibility and stability across environments. Then, you’ll move into orchestration, learning how Kubernetes automates deployment, scaling, and monitoring for real-world applications.

Through concise videos, guided readings, and a hands-on project, you’ll write a Dockerfile, publish your image to an internal registry, and deploy it to a cluster using a Kubernetes configuration file. You’ll also practice testing and reflecting on your deployment process to strengthen your operational mindset. By the end, you’ll be able to build, deploy, and manage containerized ML applications confidently—skills essential for engineers, data scientists, and anyone bringing AI models into production.

Deploy, Manage, and Orchestrate Your Models


This course features Coursera Coach!
A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.

This comprehensive course on Lodash Essentials 2026—Practical Utility Library Guide will provide you with the tools to simplify JavaScript development using Lodash. By the end, you'll master key Lodash methods and advanced functions that optimize code efficiency and performance. You will work with arrays, objects, strings, and even custom methods, making your code cleaner and easier to maintain.

The course is divided into practical modules, each focusing on a specific Lodash functionality. You'll start with basic installation and basic methods before advancing to complex transformations like filtering, sorting, and grouping data. You will also be challenged with hands-on DIY projects that mimic real-world scenarios, solidifying your understanding of Lodash in practice.

This course is ideal for developers who want to optimize their JavaScript code using Lodash, from beginners to advanced learners.

By the end of the course, you'll be capable of implementing Lodash utilities in real-world projects.

Lodash Essentials 2026 - Practical Utility Library Guide


Welcome to this project-based course on Analyzing Box Office Data with Seaborn and Python. In this course, you will be working with the The Movie Database (TMDB) Box Office Prediction data set. The motion picture industry is raking in more revenue than ever with its expansive growth the world over. Can we build models to accurately predict movie revenue? Could the results from these models be used to further increase revenue? We try to answer these questions by way of exploratory data analysis (EDA) in this project and the next. The statistical data visualization libraries Seaborn and Plotly will be our workhorses to generate interactive, publication-quality graphs. By the end of this course, you will be able to produce data visualizations in Python with Seaborn, and apply graphical techniques used in exploratory data analysis (EDA).

This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed.

Notes:
-  You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.
- This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Analyze Box Office Data with Seaborn and Python


Extract, Transform, and Load Data

This course is designed for business and data professional seeking to learn the first technical phase of the data science process known as Extract, Transform and Load or ETL.

Learners will be taught how to collect data from multiple sources so it is available to be transformed and cleaned and then will dive into collected data sets to prepare and clean data so that it can later be loaded into its ultimate destination. In the conclusion of the course learners will load data into its ultimate destination so that it can be analyzed and modeled.

The typical student in this course will have experience working with data and aptitude with computer programming.


In this course, we’ll learn about more advanced machine learning methods that are used to tackle problems in the supply chain. We’ll start with an overview of the different ML paradigms (regression/classification) and where the latest models fit into these breakdowns. Then, we’ll dive deeper into some of the specific techniques and use cases such as using neural networks to predict product demand and random forests to classify products. An important part to using these models is understanding their assumptions and required preprocessing steps. We’ll end with a project incorporating advanced techniques with an image classification problem to find faulty products coming out of a machine.

Advanced AI Techniques for the Supply Chain


Build a strong foundation in machine learning, deep learning, and TensorFlow through a structured, hands-on learning experience that takes you from core concepts to practical model development. In this course, you will learn how machine learning works, explore real-world applications across industries, and set up a professional Python development environment using Jupyter Notebook, Anaconda, and essential data science libraries.

As you progress, you will develop practical skills in data wrangling with Pandas, numerical computing with NumPy, and data visualization using Matplotlib and Seaborn. You will also learn how to preprocess datasets, engineer features, and build classical machine learning models with Scikit-learn before advancing to deep learning with TensorFlow. Through hands-on exercises and real-world datasets, you will train, optimize, and evaluate regression models and neural networks, including image classification with the MNIST dataset.

Designed for beginners entering machine learning as well as professionals looking to strengthen their TensorFlow knowledge, this course combines clear explanations with coding practice, case studies, and assessments that reinforce every stage of the machine learning workflow. By the end of the course, you will be able to confidently preprocess data, build and evaluate machine learning and deep learning models, visualize insights, and apply industry-standard tools to solve real-world problems.

Master Machine Learning with TensorFlow: Basics to Advanced


Welcome to this course on applied natural language processing in engineering. This course is designed to provide you with an in-depth understanding of NLP, a pivotal area of artificial intelligence that empowers computers to comprehend, interpret, and generate human language. Throughout this course, you will explore a wide range of topics, from fundamental NLP tasks like text classification and Named Entity Recognition (NER) to advanced techniques in neural machine translation and optimization methods critical for machine learning. We will delve into the complexities of teaching language to machines, addressing challenges like ambiguity, grammar, and cultural nuances. By the end of this part 1 course, you will have a foundational understanding of how modern NLP systems work - particularly those involving machine learning and deep learning. These topics will equip you to build, analyze and improve NLP systems across many applications.

Applied Natural Language Processing in Engineering Part 1


Did you know you can automate R scripts to facilitate model deployment and enhance workflow efficiency in healthcare analytics?

This Guided Project is designed for data scientists, healthcare analysts, and professionals in healthcare technology who want to harness the power of automation in R.  In this 2-hour project-based course, you will learn how to deploy a machine learning model using R programming language and GitHub Actions, enabling seamless integration and automation of predictive tasks. To support the model deployment, you will also automate access to data in Google Sheets and send automated emails through a Google Service Account.

To achieve this, you will use a readmission model, write an R script for prediction, configure Google Sheets, Gmail, and GitHub Actions for automation, and deliver actionable insights for healthcare providers. This project is unique because it combines technical skills with real-world applications, preparing you to tackle complex challenges in data analytics.

Prior knowledge in R programming, including data manipulation (using the dplyr and tidyr packages), programming concepts (functions and control structures), GitHub repositories for code management, and basic command line use is recommended to maximize your learning experience.

Automate R scripts with GitHub Actions: Deploy a model


This course teaches you the essential skills required to process and prepare data, model, and evaluate machine learning models. Data processing is a fundamental step in extracting valuable insights from raw data and is crucial in professional data science and machine learning careers.

By mastering these techniques, you will enhance your ability to prepare and clean data, build effective machine learning models, and evaluate their performance. These skills are vital for ensuring that your models are accurate, reliable, and ready for deployment in real-world scenarios.

The course bridges theory with real-world applications by combining hands-on data processing exercises with machine learning techniques. This approach ensures learners not only understand theoretical concepts but also apply them effectively in practical situations.

This course is ideal for aspiring data scientists, machine learning engineers, and professionals looking to strengthen their modeling and evaluation skills. A basic understanding of data science concepts will help, though no advanced experience is required.

This course is part two of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. While it delivers standalone value and practical skills, learners seeking a more integrated and in-depth progression may benefit from completing the full Specialization.

From CompTIA DataX Study Guide Copyright © 2024 by John Wiley & Sons, Inc. All rights, including for text and data mining, AI training, and similar technologies, are reserved. Used by arrangement with John Wiley & Sons, Inc.

Data Processing, Machine Learning, and Model Evaluation


This course dives into how AI-powered decision systems are designed, modeled, and governed. Built for professionals who turn analytics into real business impact, it guides you through engineering intelligent decision workflows from end to end.

You’ll kick off by transforming business challenges into structured decision models designing fast, intuitive data flows and building ethical, human-aware processes that make every choice sharper, clearer, and more confident.

Next, you’ll turn raw data into intelligence using forecasting, optimization, and scenario simulations that reveal hidden patterns, anticipate outcomes, and fuel high-impact decisions that propel the business forward.

Finally, you’ll elevate trust across your pipelines with explainable AI, dynamic dashboards, and responsible governance, ensuring every decision is transparent, fair, and reliable enough to inspire confidence at every level.

By the end of this course, you will be able to:

- Analyze business challenges and define structured, data-driven decision problems.
- Design scalable, real-time data pipelines that power decision intelligence.
- Build predictive and prescriptive models for forecasting and optimization.
- Evaluate decision system performance through interactive dashboards.
- Apply responsible AI principles to ensure fairness, transparency, and accountability.

This course is ideal for data professionals, business analysts, AI engineers, and decision scientists seeking to turn analytics into high-value decisions. Prior experience in data analytics or machine learning will help deepen your learning.

Join this course to master intelligent, transparent, and responsible decision system design and learn how to unlock stronger business performance through data-driven intelligence.

Building and Optimizing Decision Systems


"Docker and Model Serving: Deploy ML APIs with FastAPI and ONNX is designed for ML engineers, MLOps practitioners, and backend developers who want to take models from notebooks to production. You'll learn to build Docker containers for ML workloads, design scalable REST APIs with FastAPI, serialize models with ONNX and SavedModel, and deploy with zero-downtime strategies like blue-green and canary releases.

The first module covers Docker fundamentals, image optimization, multi-stage builds, secrets management, and Docker Compose for multi-container ML apps.

The second module focuses on REST API design with FastAPI, model versioning, input validation with Pydantic, structured logging, and production-grade error handling.

The third module teaches scaling strategies — horizontal scaling, async queues, load balancing, batch vs. real-time inference, and latency optimization for high-throughput serving.

The final module covers model serialization formats (ONNX, pickle, SavedModel), blue-green and canary deployments, automated rollback, and disaster recovery.

By the end of this course, you will:

- Build and optimize Docker images for ML models using multi-stage builds and Compose
- Design scalable FastAPI endpoints with versioning, validation, and observability
- Scale ML inference with async queues, load balancing, and latency optimization
- Deploy models with ONNX serialization and zero-downtime blue-green rollbacks"

Model Serving Systems: Containers, APIs & Scalability


Unlock the power of K-Means clustering and discover how to analyze unlabeled data using R programming. In this hands-on course, you will build a strong foundation in unsupervised machine learning by learning how to prepare data, apply clustering techniques, and interpret meaningful segmentation results.

Designed for learners with a basic understanding of R and statistics, this course guides you through the complete clustering workflow using a real-world customer segmentation project. You will explore core clustering concepts, understand the goals of unsupervised learning, implement the K-Means algorithm in R, and examine how feature scaling influences cluster quality and performance.

By the end of the course, you will be able to construct clustering workflows, evaluate clustering effectiveness, analyze segmentation outcomes, and recommend data-driven grouping strategies for real-world datasets. The project-based approach combines conceptual understanding with practical implementation, helping you develop confidence in applying K-Means clustering to customer segmentation and other unlabeled data problems.

Whether you want to strengthen your data analysis skills or gain practical experience with clustering in R, this course provides a focused introduction to one of the most widely used unsupervised machine learning techniques.

R: Apply & Analyze K-Means Clustering for Unsupervised ML


By the end of this course, learners will be able to build, evaluate, and optimize machine learning models using Python. They will develop the ability to preprocess data with NumPy and Pandas, visualize insights using Matplotlib, and implement workflows with scikit-learn pipelines. Learners will apply regression, classification, clustering, and dimensionality reduction techniques to real-world datasets, while mastering hyperparameter tuning for improved model performance.

This course is designed to bridge theory with practice, offering hands-on experience in every stage of the machine learning lifecycle—from data collection and preparation to model deployment. Unlike traditional courses, it emphasizes practical coding exercises and end-to-end project workflows, ensuring that learners gain both conceptual clarity and applied skills.

Upon completion, learners will be equipped with the essential tools and confidence to tackle data-driven problems, analyze large datasets, and create scalable machine learning solutions. Whether pursuing a career in data science or enhancing analytical skills, this course provides a comprehensive pathway into applied machine learning with Python.

Machine Learning with Python: Build & Optimize


Integrate Embeddings and Chroma

Vector Databases for Machine Learning: A Comprehensive Guide - Integrate Embeddings and Chroma is an intermediate-level course designed for machine learning engineers and AI practitioners aiming to build robust, automated data ingestion pipelines. In modern AI applications, the success of vector search hinges on the seamless integration of embedding models with a vector database. This course provides the critical, hands-on skills to master that integration using ChromaDB.

You will move beyond theory to implement and troubleshoot a full vectorization pipeline. Through expert-led screencasts and hands-on labs, you will learn to connect both API-based (like OpenAI) and open-source (like HuggingFace) embedding models to ChromaDB, enabling automatic vectorization on data upload. The curriculum is built around real-world failure scenarios, teaching you to systematically diagnose and resolve common but critical errors, such as vector dimension mismatches and data encoding issues. By the end of this course, you won't just build a pipeline; you'll be able to ensure its reliability, a crucial skill for deploying production-grade machine learning systems.


This course provides a deep dive into reinforcement learning (RL) with a focus on practical applications using PyTorch. You'll explore core concepts like the OpenAI Gym API, deep Q-networks, and advanced RL libraries. As RL becomes increasingly important in fields like AI, robotics, and gaming, mastering this skill will help you stay ahead in the rapidly evolving tech industry.

Through hands-on projects and real-world scenarios, you'll enhance your problem-solving abilities and gain practical expertise in building RL models. The course covers a wide range of topics, from tabular learning and the Bellman equation to complex deep Q-networks, ensuring that you develop both foundational and advanced RL skills.

What sets this course apart is its blend of theoretical knowledge with practical coding exercises. You'll learn how to implement RL algorithms using PyTorch while understanding the underlying math and principles, providing a well-rounded approach to mastering reinforcement learning.

This course is perfect for professionals and students with a background in machine learning or Python programming. Prior knowledge of deep learning or neural networks will be helpful but not required to start.

This course is part one of a three-course Specialization designed to provide a comprehensive learning pathway in Reinforcement Learning. While it delivers standalone value, learners seeking an in-depth progression may benefit from completing the full Specialization.

Foundations of Deep Reinforcement Learning with PyTorch


Deep Learning with PyTorch : GradCAM

Gradient-weighted Class Activation Mapping (Grad-CAM), uses the class-specific gradient information flowing into the final convolutional layer of a CNN to produce a coarse localization map of the important regions in the image. In this 2-hour long project-based course, you will implement GradCAM on simple classification dataset. You will write a custom dataset class for Image-Classification dataset. Thereafter, you will create custom CNN architecture. Moreover, you are going to create train function and evaluator function which will be helpful to write the training loop. After, saving the best model, you will write GradCAM function which return the heatmap of localization map of a given class. Lastly, you plot the heatmap which the given input image.


Enhance Marketing with AI: Tools for Optimal Campaigns is an intermediate-level course designed for marketing professionals ready to harness artificial intelligence for transformative campaign results. In today's data-driven marketing landscape, AI tools are no longer optional—they're essential for competitive advantage. This course equips you with practical skills to implement AI agents for automation, master prompt engineering for brand-aligned content creation, and integrate analytics tools for comprehensive performance tracking. Through real-world case studies from Nike, Coca-Cola, and IBM Watson, you'll learn to transform manual marketing processes into intelligent, data-driven workflows. The course combines strategic frameworks with hands-on applications, enabling you to immediately apply AI tools to your marketing challenges. By completion, you'll have the knowledge to design AI-powered campaigns that save time, improve targeting, and deliver measurable business results. Whether you're optimizing social media strategies, creating compelling content, or analyzing customer journeys, this course provides the AI marketing foundation you need to lead in the digital age.

Agentic AI Content for Practitioners: Marketing


From Climate Science to Action

Each part of the world faces specific vulnerabilities to climate change and has different opportunities to mitigate the effects and build resilience in the 21st century. With the ratification of the Paris Agreement, many countries have acceded to act in combatting climate change. Indeed, without climate action, decades of sustainable development is at risk, thus making this a ‘make or break’ point in time. Showcasing the most recent scientific evidence, explaining the different regional impacts and divulging climate action strategies, along with interactive tools such as a Carbon Footprint Tracker and (I) NDC Platform, this MOOC provides some opportunities, where you can take action on climate change.

About the Course

This action-oriented MOOC gives you the opportunity to learn about regional climate change impacts and sector-specific strategies to increase resilience and move towards a low-carbon future. You will have the opportunity to explore these issues in depth and tailor your learning experience for one or more of the following regions:

•  Latin America and Caribbean
•  Sub-Saharan Africa
•  Middle East and North Africa
•  Eastern Europe and Central Asia
•  East Asia and Pacific
•  South Asia

 In this endeavor, the MOOC brings together renowned scientists and policymakers to provide a synthesis of the most recent scientific evidence on climate change, regional low emissions and climate resilient development strategies across sectors. A team of expert Instructors will lead discussions around the Paris Agreement, reflections from COP22 and the progress on Nationally Determined Contributions (NDCs).

Course Syllabus

Overview

‘From Climate Science to Action’ is divided into four weeks. The first two weeks will provide a comprehensive overview of the scientific evidence for climate change, followed by region-specific insights on the impacts of a warmer world in the 21st century. The last two weeks will focus on action strategies that are being undertaken in different regions and countries to meet the climate challenge, and how you as an individual can take action to avoid a warmer world!

Week 1:  Climate Change in the 21st Century

•  Historical and projected observed changes in the climate system, leading up to the end of the 21st century
•  The potential of Intended Nationally Determined Contributions (INDCs) submitted at COP 21 from 187 countries to induce climate action
•  Trends in climate change impacts, including loss of Arctic sea ice, melting glaciers, increased heat waves and extreme temperatures, and drought and aridity
•  Possible responses from natural systems, explaining how warming could result in sea-level rise, heat waves and extreme temperatures, and ocean acidification

Week 2: Sectoral and Regional Impacts

•  Impacts on key development sectors—from warming above pre-industrial temperatures and projected climate trends—across each of the world’s regions
•  Sectoral impacts focusing on agricultural production, water resources, ecosystem services, and coastal vulnerability for affected populations
•  Importance of risks with the potential to reverse hard-won development gains and potentially trap millions in poverty, illustrating the need for urgent action now

Week 3: From Science to Action on Climate Change

•  Region-specific discussions on mitigation actions needed to reduce emissions while decreasing vulnerability to climate change impacts through adaptation and by building climate resilience
•  Perspectives from regional experts on their experiences in strategies and actions proposed in each region to help transition towards a low-emissions, climate-resilient development path
•  Discussions on the progress of the Nationally Determined Contributions (NDCs), outcomes of the Paris Agreement and reflections from the Conference of Parties (COP)22

Week 4: What You Can Do

•  Transformative impact of day-to-day changes when brought to a global scale
•  The rationale for acting now, acting together and acting differently
•  Examples and expected benefits of mitigation and adaptation policies, considering both contributions to global emission reductions and local development opportunities

In addition to the core resources and assignments, you may choose to go further, engaging in fun optional exercises, networking, discussion, and diving deeper into our rich selection of supplemental resources. You will have the opportunity to explore these issues in depth and tailor your learning experience for one or more of the following regions:

•  Latin America and Caribbean
•  Sub-Saharan Africa
•  Middle East and North Africa
•  Eastern Europe and Central Asia
•  East Asia and Pacific
•  South Asia

Course Format

This MOOC has a week-by-week structure, with resources, activities and exercises for you to engage in during each of the four weeks of the course. Each week, you will find a variety of course material, including:

•  Interactive video talks by renowned climate scientists and practitioners
•  Interactive tools: the Carbon Footprint Tracker, (I) NDC platform
•  Resources: Core, optional (deep dive) and fun interactives on the week’s theme
•  Quizzes that check your knowledge, reinforce the lesson’s material and provide immediate feedback
•  Assignments that will sharpen your skills of analysis, reflection and communication
•  Discussion forums and social media that enable collaboration with others from around the world, enriching interaction among participants
•  As a final project, you will create a digital artifact

You can also go much further than this, engaging in optional exercises, networking, or discussion forums and dive deeper into our rich selection of additional resources. We also will use e-discussions, and other tools to facilitate dialogue between the learners and experts.

Recommended Background: No background knowledge is necessary. The content of this course is designed to be accessible to students from any discipline.

Connect: Communicate and share resources via Twitter using hashtag #learnclimate. Sign up for a free account at http://twitter.com


Have you come across large piles of garbage in neighbourhoods and streets and smelly waste disposal sites polluting the environment of low- and middle-income countries? Do you want to know what kind of sustainable solutions are appropriate to better manage waste and enhance recycling and recovery? If yes, this course is for you!

This course provides you with an overview of the municipal solid waste management situation in low- and middle-income countries. It covers key elements of the waste management system, such as its technical, environmental, social, financial and institutional aspects. Besides understanding the challenges, you will be introduced to appropriate and already applied solutions through selected case studies.

Municipal Solid Waste Management in Developing Countries

École Polytechnique Fédérale de Lausanne


How can we shape our urban development towards sustainable and prosperous futures?

This course explores sustainable cities as engines for greening the economy in Europe and around the world. We place cities in the context of sustainable urban transformation and climate change. We connect the key trends of urbanization, decarbonisation and sustainability. We examine how visions, experiments and innovations can transform urban areas. And we look at practices (what is happening in cities at present) and opportunities (what are the possibilities for cities going forwards into the future).

This course was launched in January 2016, and it was updated in September 2021 with new podcasts, films and publications. The course is produced by Lund University in cooperation with WWF and ICLEI – Local Governments for Sustainability who work with creating sustainable cities. The course features researchers, practitioners and entrepreneurs from a range organisations.

Greening the Economy: Sustainable Cities

Kes McCormick
Prof.  Lena Neij
Prof. James Evans
Prof. Harriet Bulkeley


User experience is a highly in-demand field which requires a holistic understanding of the design process. This course is a "sample" of the UX Design MasterTrack certificate program. You will have the opportunities to explore core topics in UX including Ethics and Research, User Research, User Testing, and Visual Literacy as four modules.

You can take the opportunity to gain some basic understanding of UX research, and take this course as a pathway to the  UX Design MasterTrack certificate program. The assignments you have accomplished in this open course can be carried over to the UX Mastertrack certificate program.

If you would like to continue learning after this open course, please visit our UX Design MasterTrack certificate program website: https://www.coursera.org/mastertrack/ux-design-minnesota

Introduction to UX Design MasterTrack Certificate Program


This course is designed to help you take the next step in your academic journey by mastering two critical skills: professional communication and strategic planning for research involvement. You’ll begin by learning how to write clear, respectful, and persuasive emails that encourage timely responses—an essential skill for connecting with professors and securing opportunities. Next, you’ll explore strategies for resilience and problem-solving when facing challenges such as unanswered messages or rejection. Finally, you’ll move from preparation to action by creating a personalized research plan, identifying your resources, and setting a realistic timeline to stay motivated. By the end of this course, you’ll have the confidence and tools to communicate effectively and turn your research goals into reality.

How to Write Emails and Engage Professors


Professionalism in an era of change

In this course we aim to provide you with an insight into how recent societal and technological developments have changed the work of professionals in a variety of professional domains and how this in turn affects professionalism. The course highlights core themes, discusses main insights and theories, raises questions and presents cases, and links insights to practical challenges in various professional domains. It provides a state of the art assessment of professionalism in transition, by looking back and looking forward. It supports target audiences in dealing with professional services and professionals.

The programme has an interdisciplinary approach and will focus on different levels:
At macro level the course presents a historical and sociological view on past and future changes in professions, focused on:
•	how do professional fields develop?
•	how is professionalism promoted and encouraged among professionals?
•	how do professional fields control and empower their members?

At meso level the course presents an organisational view on changes within professional partnerships and institutions, focused on the following questions:
•	how do norms and routines affect professionals and professional work?
•	how do professionals organise and lead professional work?

At micro level a psychological perspective on changing work and a changing work environment of professionals is presented. This part focuses on the following questions:
•	how do professionals deal with work pressure and remain motivated?
•	which competencies do professionals require to be able and capable to deliver?

We invite you to join us and increase your understanding of the topics addressed in this course through lectures, interviews, animations, readings and peer interaction.


This course is the third course in a series on the discipline of Archaeology. It is intended for learners at all stages, including advanced high school, college students, or life-long learners. Basic information about Archaeology and its history are presented in the first introductory course. The second course teaches common scientific methods used in archaeological research. This course focuses on forms of interpretation to reconstruct various aspects of the past through archaeological approaches. The final course covers contemporary social issues that archaeologists engage with.

Introduction to Archaeology: Reconstruction of The Past


This course will highlight the construction and interpretation of the U.S. Constitution through the centuries. You'll learn the history behind the Constitution, cases that formed important precedent, and how changes in interpretation have been dependent on shifts in cultural and political climate as well as the composition of the Supreme Court.

We'll start with an overview of the Constitution where we'll consider questions such as "Why the Constitution?" and "What function does the Constitution serve?" Next we'll examine how the Constitution and its subsequent interpretation established the powers of the federal, legislative, and judicial branches of government and allocated powers to the states.

Join me as we look at the questions both raised and answered by the Constitution and those that interpret it!

By the end of this course, you should be able to:

- Describe how the structure of the United States government has been shaped by both the text of the Constitution and by subsequent interpretation and practice of political actors in all branches of government

- Illustrate compromises found in the Constitution by citing examples and historic background

- Articulate the importance of key cases such as Marbury v. Madison, McCullough v. Maryland, and Lochner v. New York

- Explain how the outcome of cases is often dependent upon the current cultural and political climate as well as the composition of the court by citing particular cases and important shifts in the court's jurisprudence

- Assess the relative suitability of various approaches to constitutional interpretation and analysis

Chemerinsky on Constitutional Law - The Structure of Government


Vozes da Mudança Social

Em tempos de instabilidade política, desequilíbrio ambiental e desigualdade social, jovens agentes de mudanças sociais estão liderando o caminho para solucionar os desafios da atualidade. O que você está fazendo para gerar mudanças positivas e sustentáveis?

O programa Vozes da Mudança Social é um curso on-line, gratuito e de curta duração, elaborado e ministrado por oito jovens empreendedores. Siga os passos desses agentes de mudanças sociais que combinaram uma ideia ao desejo de ajudar outras pessoas a gerar impactos positivos na sociedade. Hoje, eles fazem a diferença na vida de muitos ao redor do mundo.

Desenvolvido pela rede Laureate International Universities em parceria com a International Youth Foundation (IYF) e o B Lab, o programa Vozes da Mudança Social fornecerá a estrutura e uma rede de suporte para você dá o próximo passo. Seja apoiar sua comunidade local, iniciar um empreendimento social ou promover uma iniciativa já existente.

Aprenda com aqueles que tiveram vitórias e derrotas no empreendedorismo social, conecte-se com outros agentes de mudanças sociais que estão fazendo as mesmas perguntas que você e elabore o seu próprio plano de ação.

O curso é composto por cinco (5) módulos, que podem ser realizados ao longo de cinco (5) semanas. Cada módulo possui lições que contêm vídeos, leituras e atividades para o seu aprendizado.

Inscreva-se no programa Vozes da Mudança Social, desenvolva suas habilidades e prepare-se para criar mudanças sociais sistêmicas e duradouras. Sua jornada começa agora!

5 semanas de estudo, 1-2 horas por semana.

Universidad Peruana de Ciencias Aplicadas

Nick Martin
Geórgia Nunes
DR Selene Martinez-Pacheco
Joel Adriance
Melanie Tran
Rafael Henrique
Daniela Andrea Retamales Gomez
Carolina Zuheill Rosales
Dina Buchbinder Auron
Dr William Schulz


By the end of this project, you will be ready to use Edpuzzle to make video learning content more interactive to improve student learning. Technology plays an ever-increasing role in education, both in the classroom and when moving to online learning. With Edpuzzle, you will begin with videos they have created or found on YouTube, Khan Academy, and other websites. You can then adjust the length, add your own narration, and add comprehension checks to ensure that your videos are not just being watched - they are effective instructional tools. If you are looking for ways to improve your flipped classroom, hybrid learning, or online learning environment, Edpuzzle is an essential tool to add to your Teacher’s Toolkit.

*You will need a free Edpuzzle account for this project.

Creating Interactive Learning Videos with Edpuzzle


*Broadening leadership competences to navigate economic, social and ecological challenges in wind energy transitions*

This course is designed to help you develop your leadership competencies through experiential learning, reflection, and applying new approaches based on what you learn. It consists of 6 modules which present different themes in the renewable energy transition, particularly: justice in the energy transition (Module 2), participatory practices with local community members (Module 3), perspectives of other-than-humans (Module 4), alternative ownership and governance models (Module 5), and the management of wicked problems in transitions (Module 6). Additionally, each module provides exercises to help you apply the gained insights in your daily work as a leader in the wind energy sector.

Steering towards a just and effective wind energy system demands strong leadership. While the idea of a strong leader is often associated with someone dominant, assertive, and focused on clear, immediate outcomes, the complexity and uncertainty involved in the wind energy transition require a different approach. As the EU works toward reaching its goal of 45 % renewable energy by 2030, accelerating wind energy presents a range of challenges. It is not just about what is technically and financially possible. Local authorities and developers involved in wind energy focus on economic, social, and environmental issues to transform the wind energy system towards greater justice and effectiveness.

Therefore, these 6 modules place a strong emphasis on developing transition leadership competencies such as deep listening, reflecting on your assumptions, considering the perspectives of others, facilitating collective learning, and collaborating with different actors. Completing this course, you have broadened your leadership competencies to navigate the complex and uncertain realities of the renewable energy transition.

Leadership in Transitions: Competences in Just Transitions


Population and Urbanization

Analyze the powerful population trends that shape modern society by focusing on urbanization - the historical development of cities and its profound impact on our contemporary social lives. By the end of this course, you will be able to explain how these demographic patterns directly influence the structure and experience of social life in cities today.


This course helps higher education faculty, instructors, and academic leaders make sense of the forces reshaping colleges and universities, and what they mean for everyday teaching practice. You will examine key shifts such as technological acceleration, especially advances in artificial intelligence, changing student expectations, and evolving labor market demands that are influencing perceptions of degree value and student outcomes. Throughout, you will distinguish between temporary environmental changes and the enduring mission and purposes of higher education.

Building on this foundation, you will explore how knowledge, skills, and judgment interact in a world where AI is increasingly capable of performing routine cognitive tasks. The course examines the continued role of faculty expertise in guiding learning, maintaining academic rigor, and supporting meaning-making—not just skill acquisition. You will analyze the gaps between academic learning and workforce expectations, and learn how skills can serve as connectors between disciplines and career pathways. Finally, you will identify concrete opportunities in your own courses to make learning more visible and transferable, incorporate more active and applied learning, and experiment with AI-supported tools that extend instructional presence while preserving faculty autonomy. You will leave with a practical, low-risk action plan for integrating new approaches into your teaching context and contributing thoughtfully to institutional responses to change.

Faculty, Skills, and the Future of Higher Education


Are you ready for the new, COVID-forced, online learning paradigm? This competency-based, skill-building course will help non-U.S. students, first-generation immigrants, and foreign-born professionals better understand and master American online learning, as well as other U.S. virtual environments, for college and career success. In the post-COVID era, the course can also be very instrumental in assisting U.S.-based institutions in organizing remote learning activities for their current or prospective international students.

The current pandemic has disrupted the world of higher education and work as we know it. Many thousands of international students and professionals can no longer travel internationally at will and must now learn how to effectively study and work remotely. To excel in American online learning and work environments, international students and foreign-born professionals need to know how American universities and companies use the Internet to organize study and work, develop and execute projects, communicate ideas, collaborate, and solve organizational and technical problems. By taking this course, you will learn how to enhance your cultural knowledge and assess potential skill gaps that may hinder your online experience or negatively impact your performance in U.S. virtual learning and work environments. Throughout the course you will systematically review competencies required for online work, come to better understand common barriers for non-native students and professionals, learn how to detect and overcome competency gaps, and develop plans for self-improvement and success. We believe that you will find the course useful and gain new knowledge and skills to become more successful in your remote study/work in the U.S.

The course was previously offered as iMOOC101 and iMOOC102 "Mastering American e-Learning". We have updated it to reflect the new realities of the Post (well, not yet!)-COVID era. We will be glad if you could share your own experiences in navigating the new world of remote teaching, learning, and work.

Mastering Remote Work and Online Study in U.S. in the post-COVID Era

Dr. Valeri Chukhlomin
Amy Giaculli
Dr.  Bidhan Chandra
Dr. Dana Gliserman-Kopans
Dr.  Anant Deshpande


Digital-driven changes are both generic and specific. Most transformations apply to all industries, equally and without exception. But in some industries or places, digital transformations are singular and atypical. To be a player in the digital world, you will need to master both the transformations common to all industries and the transformations at work on certain verticals. Retail and the sharing economy are emblematic of markets where specific transformations are unfolding. This module will tell you how.

Week 1 : New business models, new perimeters
Week 2 : Regulating the digital innovation
Week 3 : The value of digital innovation

Digital business - Grow on digital world

École Polytechnique
Institut Mines-Télécom


Digital Case Method

The course is suited for teaching and learning professionals, media professors, university leaders, and educators interested in learning, creating, and using Digital Case Studies.

This course will allow learners to tap into the power of visual storytelling through the powerful format of the digital case study, which can and should be created by students themselves. This class uses video tutorials and practical guides  to teach learners case creation using inexpensive tools such as a smartphone, stabilizer, and Adobe Premiere Software. It also dives into how to design, fund, and manage education programs built on digital case studies.

To be successful in this course no pre-requisite filmmaking knowledge is required. An interest in documentary-style filmmaking and video editing is all you need.


This course aims to provide an in-depth reflection on social work in different contexts, hereby focusing on their needs, the way the contexts have been influenced, and different challenges that have occurred during the last two years.
It aims to set up conversations with multiple professionals where they give information about the hurdles on their path, the lessons learned from these turbulent times, and to give an overview of important ideas and practices that could help reshape the future of social work.
In the end, the goal is to provide specific, hands-on, best practices collected from literature and professionals in Belgium and Europe that help organise social work, both during and after a pandemic.

This course was developed as part of the research project 'Pan-European Response to the Impacts of the COVID-19 and future Pandemics and Epidemics' (PERISCOPE, https://www.periscopeproject.eu/). Funded by the European Commission Research Funding programme Horizon 2020 under the Grant Agreement number 101016233, PERISCOPE investigates the broad socio-economic and behavioural impacts of the COVID-19 pandemic, to make Europe more resilient and prepared for future large-scale risks.

Reaching Vulnerable Groups through Pandemic Policy


Performance Studies: An Introduction explores the wide world of performance--from theatre, dance, and music to ritual, play, political campaigns, social media, and the performances of everyday life. Performance studies also ranges across cultures--Asia, Africa, the Caribbean, Europe, the Americas. And it spans historical periods from the art of the paleolithic caves to YouTube and the avantgarde. This course is devised by Richard Schechner, one of the pioneers of performance studies, in dialogue with more than a dozen expert scholars and artists. Performance Studies: An Introduction puts students in dialogue with the most important ideas, approaches, theories, and questions of this dynamic, new academic field.

Learning Objectives

By the end of this course, you should be able to:

Articulate and analyze the major concepts of performance studies
Identify and analyze performances within the “broad spectrum of performance”--from everyday life and social media to performance art and global spectacles such as the Olympics
Comprehend key terms of performance studies, including is/as performance, restored behavior, ritual, play, make-belief/make-believe, performance in everyday life, the performative, and intercultural performance
Produce collaborative work that demonstrates teamwork in applying ideas learned in the course
Compare, analyze, and interpret performances of their own and other cultures
Articulate how the major concepts of the course relate to their own experiences and worldviews
Analyze and criticize in a constructive way the work of classmates

The lessons present Schechner’s concept of performance studies along with online assignments. In the assignments, students apply what they are learning by composing short responses to materials, writing in their NYU Classes Forums, and by reviewing other students’ forum posts each week.

Students choose either to work in groups of 3 to 5 on a term-long project maintaining a project portfolio in NYU Classes or to write a research paper. During the term, each group will lead an in-class 25-minute discussion of their project-in-progress. During the last face-to-face class, each group will present their project.

The weekly content is:

What is Performance?
What is Performance Studies?
Performance Processes
From Not Performing to Performing
Ritual
Play
Performing in the Paleolithic
Ramlila of Ramnagar
The Performing Brain
Performativity
Constructing Social Roles
Social Media
Intercultural, Transcultural, Global
Group Projects & Wrap Up
Course Requirements

Each student is required to complete the week’s online lesson prior to the class session, attend and participate in the class sessions, complete the weekly assignments, participate and present the group project or submit a final paper.

Required Readings

See weekly online lessons.

Required Viewings (Videos)

See weekly online lessons.

Written work

Each student will either participate in a group project or write a research paper due at the end of the term, submitted electronically. Your professor will confer online and/or face-to-face during office hours to help students develop their writing and their projects. If you do a group project your professor may ask you to do some writing in relationship to your project.

Academic Integrity

The policy on plagiarism and academic honesty is posted on Classes. Read this document carefully, and be guided by it.

Copyright

Keep in mind the material you find in the online lessons is subject to copyright. You may not reproduce, reuse, or distribute it without permission outside of your work in this course. For more information on copyright and how it applies to course materials, see the Copyright Basics research guide.

Richard Schechner's Introduction to Performance Studies