Encryption and Cryptography Essentials

Over 10,600 confirmed breaches were reported globally in 2024, exposing millions of records, including sensitive healthcare and financial data. Organizations need cybersecurity professionals who can protect them against this costly risk. This Encryption and Cryptography Essentials course gives aspiring cybersecurity professionals job-ready skills in encryption, hashing, and digital signatures—key competencies employers are looking for.

You’ll master symmetric (AES) and asymmetric (RSA) encryption techniques and apply hashing methods like MD5 and SHA to ensure data integrity. You’ll learn how to manage and verify certificates using the Online Certificate Status Protocol (OCSP). Plus, you’ll explore blockchain technology and its applications.

This course is a comprehensive guide to mastering encryption and cryptography in cybersecurity. Through hands-on labs, interactive quizzes, and projects, you’ll learn how to secure digital information, tackle cybersecurity challenges, and implement encryption and cryptographic solutions.

If you’re looking to add job-ready encryption and cryptography skills employers need to your resume, enroll today!


Over 80% of enterprises now rely on cloud-native technologies to drive innovation and scale efficiently (CNCF). Professionals with cloud-native, microservices, and DevOps skills are highly sought after! This course equips both aspiring and experienced professionals with the practical, job-ready expertise employers are looking for.

During the course, you’ll explore cloud-native fundamentals, including hybrid cloud infrastructures and modernization strategies. Plus, you'll gain hands-on experience mastering RESTful APIs, CI/CD pipelines, and Agile and Scrum practices that enhance collaboration and delivery.

The course also covers essential containerization concepts for using Docker and Kubernetes, ensuring you can build scalable and resilient applications. Plus, through interactive labs and real-world projects, you'll develop the technical skills and confidence to apply these practices effectively in professional environments.

By the end, you'll have the expertise to build scalable cloud-native applications, automate development workflows, and align technical solutions with business objectives. If you’re keen to open up exciting career opportunities in cloud, enroll today!

Cloud Native, Microservices, Containers, DevOps and Agile


Supervised Machine Learning: Regression

This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error metrics to compare across different models. This course also walks you through best practices, including train and test splits, and regularization techniques.

By the end of this course you should be able to:
Differentiate uses and applications of classification and regression in the context of supervised machine learning
Describe and use linear regression models
Use a variety of error metrics to compare and select a linear regression model that best suits your data
Articulate why regularization may help prevent overfitting
Use regularization regressions: Ridge, LASSO, and Elastic net

Who should take this course?
This course targets aspiring data scientists interested in acquiring hands-on experience  with Supervised Machine Learning Regression techniques in a business setting.

What skills should you have?
To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics.

Mark J Grover
Miguel Maldonado
Svitlana (Lana) Kramar


Introduction to Data Engineering

Start your journey in one of the fastest growing professions today with this beginner-friendly Data Engineering course! You will be introduced to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in the ecosystem.

You will begin this course by understanding what is data engineering as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in this exciting field. Next you will learn about the data engineering ecosystem, the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks.

You will become familiar with the components of a data platform and gain an understanding of several different types of data repositories such as Relational (RDBMS) and NoSQL databases, Data Warehouses, Data Marts, Data Lakes and Data Lakehouses. You’ll then learn about Big Data processing tools like Apache Hadoop and Spark. You will also become familiar with ETL, ELT, Data Pipelines and Data Integration.

This course provides you with an understanding of a typical Data Engineering lifecycle which includes architecting data platforms, designing data stores, and gathering, importing, wrangling, querying, and analyzing data. You will also learn about security, governance, and compliance.

You will learn about career opportunities in the field of Data Engineering and the different paths that you can take for getting skilled as a Data Engineer. You will hear from several experienced Data Engineers, sharing their insights and advice.

By the end of this course, you will also have completed several hands-on labs and worked with a relational database, loaded data into the database, and performed some basic querying operations.


What is Data Science?

Do you want to know why data science has been labeled the sexiest profession of the 21st century? After taking this course, you will be able to answer this question, understand what data science is and what data scientists do, and learn about career paths in the field.

The art of uncovering insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and accurately predicted the Nile River's flooding every year. Since then, people have continued to use data to derive insights and predict outcomes. Recently, they have carved out a unique and distinct field for the work they do. This field is data science.

In today's world, we use Data Science to find patterns in data and make meaningful, data-driven conclusions and predictions.
This course is for everyone and teaches concepts like how data scientists use machine learning and deep learning and how companies apply data science in business.

You will meet several data scientists, who will share their insights and experiences in data science. By taking this introductory course, you will begin your journey into this thriving field.

3 weeks of study, 2-3 hours/week, 1 optional week


This is the final course in the IBM Backend Development Professional Certificate. This capstone project course will give you the chance to practice the work that back-end developers do in real life when working with applications.

In this course, you will assume the role of a real-life developer working to develop and deploy back-end microservices and applications.

You will be tasked to develop, deploy, and integrate an application composed of several microservices, and integrating them seamlessly. You will use various back-end tools and technologies, including Flask, Django, NoSQL, and Mongo DB, to accomplish this project while applying coding best practices. You will also deploy and scale and update each of the application’s microservices independently using Cloud Native technologies: Kubernetes, OpenShift and serverless (Code Engine).

In this course, you’ll mostly focus on hands-on work to demonstrate and apply what you have learnt in previous courses. By successfully completing this Capstone you will have added a project to your programming portfolio to showcase to employers.

Back-end Application Development Capstone Project


This is the fifth course in the IBM AI Enterprise Workflow Certification specialization.   You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones.

This course introduces you to an area that few data scientists are able to experience: Deploying models for use in large enterprises.  Apache Spark is a very commonly used framework for running machine learning models.  Best practices for using Spark will be covered in this course.  Best practices for data manipulation, model training, and model tuning will also be covered.  The use case will call for the creation and deployment of a recommender system. The course wraps up with an introduction to model deployment technologies.

By the end of this course you will be able to:
1.  Use Apache Spark's RDDs, dataframes, and a pipeline
2.  Employ spark-submit scripts to interface with Spark environments
3.  Explain how collaborative filtering and content-based filtering work
4.  Build a data ingestion pipeline using Apache Spark and Apache Spark streaming
5.  Analyze hyperparameters in machine learning models on Apache Spark
6.  Deploy machine learning algorithms using the Apache Spark machine learning interface
7.  Deploy a machine learning model from Watson Studio to Watson Machine Learning

Who should take this course?
This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises. If you are an aspiring Data Scientist, this course is NOT for you as you need real world expertise to benefit from the content of these courses.

What skills should you have?
It is assumed that you have completed Courses 1 through 4 of the IBM AI Enterprise Workflow specialization and you have a solid understanding of the following topics prior to starting this course: Fundamental understanding of Linear Algebra; Understand sampling, probability theory, and probability distributions; Knowledge of descriptive and inferential statistical concepts; General understanding of machine learning techniques and best practices; Practiced understanding of Python and the packages commonly used in data science: NumPy, Pandas, matplotlib, scikit-learn; Familiarity with IBM Watson Studio; Familiarity with the design thinking process.

This course requires 7.5 to 9 hours of study.

AI Workflow: Enterprise Model Deployment


JavaScript Full Stack Capstone Project

Show your mastery of JavaScript full-stack application development by completing this capstone project! In this course, you will apply your knowledge and skills to a real-life inspired challenge and use your expertise to develop a successful solution.

The project provides you with an opportunity to solidify your JavaScript full-stack proficiency. As you design a dynamic user experience using React, you will develop frontend pages, build services for communication with a NoSQL Mongo database, and configure CI/CD pipelines, all while applying Agile practices.

In this capstone, you apply knowledge of in-demand skills such as:

- Architecting an application

- Creating a dynamic frontend using HTML, CSS, and the React JavaScript library

- Communicating with backend services such as databases

- Use DevOps practices such as CI/CD pipelines

- Deploying a serverless application

- Creating and invoking RESTful microservices

- Deploying the entire solution on the cloud using Kubernetes

When you complete this project, you will have a working full-stack application that will impress potential employers.

Before starting this course, we highly recommend you complete all the courses offered in the IBM JavaScript Full Stack Software Developer Professional Certificate.


This IBM course will equip you with the skills to implement, train, and evaluate generative AI models for natural language processing (NLP) using PyTorch. You will explore core NLP tasks, such as document classification, language modeling, and language translation, and gain a foundation in building small and large language models.

You will learn how to convert words into features using one-hot encoding, bag-of-words, embeddings, and embedding bags, as well as how Word2Vec models represent semantic relationships in text.

The course covers training and optimizing neural networks for document categorization, developing statistical and neural N-Gram models, and building sequence-to-sequence models using encoder–decoder architectures. You will also learn to evaluate generated text using metrics such as BLEU.

The hands-on labs provide practical experience with tasks such as classifying documents using PyTorch, generating text with language models, and integrating pretrained embeddings like Word2Vec. You will also implement sequence-to-sequence models to perform tasks such as language translation.

Enroll today to build in-demand NLP skills and start creating intelligent language applications with PyTorch.

Gen AI Foundational Models for NLP & Language Understanding


Introduction to Networking and Storage

Keen to kickstart your IT career with networking and storage skills employers need? This beginner course introduces essential IT concepts to help you diagnose and support modern systems.

 During this course, you’ll explore networking fundamentals such as cables, topologies, network types, and communication models and learn how data travels across wired and wireless connections using protocols and standards. You’ll dive into Wi-Fi, exploring SSID configuration, access point setup, security evolution from WEP to WPA3, and Wi-Fi 6 (802.11ax) features such as frequency bands and channel planning. Plus, you’ll look at NFC (near-field communication) concepts and practical applications.

 Next, you’ll get hands-on with device configuration and the command-line tools used to troubleshoot connectivity issues in Windows environments. You’ll look at storage essentials, exploring memory , local versus cloud options, and file, block, and object storage. Plus, you’ll learn how to select storage solutions for different networking scenarios while examining NVMe performance factors, including PCIe generations and thermal management.

Enroll now to build IT skills in networking and storage employers need!

IBM Skills Network Team
Ramanujam Srinivasan


Build RAG Applications: Get Started

Data Scientists, AI Researchers, Robotics Engineers, and others who can use Retrieval-Augmented Generation (RAG) can expect to earn entry-level salaries ranging from USD 93,386 to USD 110,720 annually, with highly experienced AI engineers earning as much as USD 172,468 annually (Source: ZipRecruiter).

In this beginner-friendly short course, you’ll begin by exploring RAG fundamentals—learning how RAG enhances information retrieval and user interactions—before building your first RAG pipeline.

Next, you’ll discover how to create user-friendly Generative AI applications using Python and Gradio, gaining experience with moving from project planning to constructing a QA bot that can answer questions using information contained in source documents.

Finally, you’ll learn about LlamaIndex, a popular framework for building RAG applications. Moreover, you’ll compare LlamaIndex with LangChain and develop a RAG application using LlamaIndex.

Throughout this course, you’ll engage in interactive hands-on labs and leverage multiple LLMs, gaining the skills needed to design, implement, and deploy AI-driven solutions that deliver meaningful, context-aware user experiences.

Enroll now to gain valuable RAG skills!

Wojciech 'Victor' Fulmyk
IBM Skills Network Team


Skill up for the CompTIA Core 2 Certification exam! This course gives aspiring IT support professionals, helpdesk professionals, and system administrators essential skills for this career-launching certification and a job in IT support, networking, and system management.

During this course, you’ll explore key operating systems (OS), including Microsoft Windows, Apple macOS, Linux, and cloud-based platforms. You’ll learn how to install, update, and manage IT systems while mastering their unique features and functionalities. Plus, you’ll look at IT support best practices, and how to diagnose and troubleshoot common PC and mobile issues, address malware threats, and configure system security.

You’ll also explore full-disk encryption methods, vulnerabilities, firewall settings, data backup and recovery, remote access management, and privacy policy essentials. You’ll gain insights into AI for public and private usage in OS. Plus, you’ll get hands-on experience using real-world tools, from command-line utilities to firewall settings and SOHO router security.

Enroll today to strengthen your resume and take the next step toward the CompTIA Core 2 certification exam!

Core 2: OS, Software, Security and Operational Procedures


Business Intelligence (BI) Essentials

This course provides a comprehensive introduction to business intelligence (BI), its key concepts, components, and the benefits and challenges of implementing BI solutions. It also discusses career opportunities and roles available in the BI arena and the skills and qualifications required.

You will also gain insight into the data ecosystem, BI analytics landscape, data repositories, and the extract, transform, and load (ETL) process. Additionally, you will be introduced to the role of statistical analysis in mining and visualizing data to identify patterns and trends and how to weave a compelling story with data.

The course offers practical exposure with hands-on activities and a final project that enables you to apply your knowledge in real-world scenarios. This specialized program is tailored for individuals interested in pursuing a career as a BI analyst, and no prior data analytics experience or degree is required to take this course.


Python Project for Data Engineering

Showcase your Python skills in this Data Engineering Project! This short course is designed to apply your basic Python skills through the implementation of various techniques for gathering and manipulating data.

You will take on the role of a Data Engineer by extracting data from multiple sources, and converting the data into specific formats and making it ready for loading into a database for analysis. You will also demonstrate your knowledge of web scraping and utilizing APIs to extract data.

By the end of this hands-on project, you will have shown your proficiency with important skills to Extract Transform and Load (ETL) data using an IDE, and of course, Python Programming.

Upon completion of this course, you will also have a great new addition to your portfolio!

PRE-REQUISITE:

**Python for Data Science, AI and Development** course from IBM is a pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python for Data Science, AI and Development course from IBM or have equivalent proficiency in working with Python and data. NOTE: This course is not intended to teach you Python and does not have too much new instructional content. It is intended for you to mostly apply prior Python knowledge.


Build AI Agents using MCP

Get hands-on designing secure, intelligent AI agent workflows using the Model Context Protocol (MCP) in this labs-driven course. You’ll see how AI systems connect to external tools, services, and data sources. You’ll learn how those connections can be designed to stay safe and predictable using structured permissions, user prompts, and validation workflows. And in hands-on labs, you’ll build agents that reason, retrieve information, and carry out tasks while maintaining security and control.

You’ll also work with permission enforcement models, JSON-schema-based elicitation, auditing concepts, and real-world security scenarios. You’ll explore how MCP works and why secure design decisions matter in practice. Plus, you’ll break down user requests, shape safe execution flows, and reduce the risk of unintended actions.

Finally, you’ll plan and test a complete MCP-driven agent workflow, showing how usability, capability, and security come together in a real implementation.

This course is designed for professionals in development, architecture, automation, or AI-powered applications who want hands-on, practical experience building responsible AI workflows.

Abdul Fatir
Zikai Dou
Joseph Santarcangelo
Wojciech 'Victor' Fulmyk
Joshua Zhou
Jianping Ye


Introduction to UX/UI Design

With user experience now a top priority, the UX/UI design market is growing fast (Global Growth Insights). Talented UI/UX designers are in high demand! This course gives you the essential skills to confidently take your next step in learning UX/UIdesign.

During the course, you’ll learn the basics of user experience (UX) and user interface (UI) design and discover how they work together to create effective, user-friendly products. From websites and mobile apps to emerging technologies like AR/VR, you’ll see how UX/UI shapes the way we interact with digital experiences.

You'll also explore how UX/UI fits into the product development process and learn about core technical skills, including wireframing, prototyping, user research, and interaction design.

You’ll  learn about tools used by UX/UI designers such as Figma, and learn how to select the right tools for different design tasks. You’ll also gain hands-on experience developing a prototype using Figma.
By the end, you’ll have a clear understanding of potential career paths and the skills needed to take your next step in UX/UI design.

Whether you're exploring design for the first time or looking to build your UX/UI skillset, enroll today and start your UX/UI journey.


IBM Storage Scale Remote Data Access

This course is intended for IT professionals tasked with administering a Storage Scale storage cluster consisting of Linux nodes. The course includes information on various Storage Scale features that enable remote access to data that is stored in a cluster file system. This includes: multi-cluster support, clustered NFS, cluster export services (CES) and protocol support (NFS, SMB, and Object), Active File Management (AFM), and AFM-based Asynchronous Disaster Recovery (AFM DR). The features are described in lecture materials and implemented in lab exercises.


Data Science Methodology

If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. In this course, you will learn and then apply this methodology that you can use to tackle any Data Science scenario. You’ll explore two notable data science methodologies, Foundational Data Science Methodology, and the six-stage CRISP-DM data science methodology, and learn how to apply these data science methodologies. Most established data scientists follow these or similar methodologies for solving data science problems.

Begin by learning about forming the business/research problem Learn how data scientists obtain, prepare, and analyze data. Discover how applying data science methodology practices helps ensure that the data used for problem-solving is relevant and properly manipulated to address the question. Next, learn about building the data model, deploying that model, data storytelling, and obtaining feedback You’ll think like a data scientist and develop your data science methodology skills using a real-world inspired scenario through progressive labs hosted within Jupyter Notebooks and using Python.


Vector databases provide the solid foundation required by large language models to deliver AI-powered similarity searches and recommendation systems for e-commerce recommendations, cybersecurity fraud detection,  medical diagnostics, bioinformatics research, and other complex analysis tasks. Begin learning how to take advantage of the efficiencies vector databases offer in this introductory course by IBM.

In this introductory microcourse, you'll build your knowledge of vector database fundamentals and explore the importance of vector databases in today’s data management landscape. Then, dive into how vector databases differ from traditional databases and learn about vector database types and their uses.

You’ll also gain hands-on experience setting up environments for vector database operations and performing day-to-day database tasks using Chroma DB. You will learn how to:

•	Set up environments for vector database operations.
•	Perform update, delete, and collection-related tasks.
•	Demonstrate vector database skills and implement similarity searches using real-world data sets.

This microcourse is built to provide you with broad, foundational vector database knowledge. This course is for engineers, data scientists, machine learning engineers, DevOps engineers, AI Engineers, and others who work with or intend to build large language models (LLMS), generative AI applications, and related transformative technologies.

Enroll today and learn how to take advantage of the efficiencies that vector databases offer!

Vector Databases: An Introduction with Chroma DB


Get ready to put your Generative AI, Natural Language Processing (NLP), and PyTorch skills into action in this hands-on capstone project from IBM.

During this course, you’ll solve a real-world text classification challenge by building an end-to-end NLP workflow, from raw text processing to model evaluation.

You’ll design and implement complete pipelines, including text preprocessing, tokenization, vocabulary creation, and dataset preparation using PyTorch Dataset and DataLoader. You’ll train and compare RNN, LSTM, and Transformer models, and explore how each architecture processes language differently. Plus, you’ll fine-tune pretrained models using Hugging Face Transformers, applying techniques used in production-grade AI systems.

By the end of the course, you’ll have a portfolio-worthy capstone project that showcases your ability to build, optimize, and evaluate NLP models using metrics such as accuracy and F1-score. Great for talking about in interviews.

Enroll today to strengthen your Generative AI and NLP skills and showcase your expertise with this powerful, job-oriented capstone project.

Generative AI for NLP with PyTorch Capstone Project


Demonstrate your job-ready skills to employers in this portfolio-worthy capstone project! During this course, you’ll apply your systems and solutions architecture, stakeholder management, and cloud-native deployment skills to create a real-world enterprise architecture.

As you work through the modules, you’ll apply systems and solutions architect strategies, including stakeholder engagement, requirements gathering, system design, security architecture, cloud deployment, and compliance alignment.

Through hands-on labs, you’ll create project charters, UML, and ERD diagrams. You’ll design scalable cloud-native architectures with Docker and IBM Cloud/AWS, and combine enterprise data pipelines, and incorporate secure frameworks. Plus, you’ll build end-to-end process flow, CI/CD pipelines, and a phase implementation roadmap.

By the end, you’ll have a comprehensive capstone project that demonstrates your expertise in systems and solutions architecture, highlighting your ability to address real organizational challenges and improve enterprise infrastructure.

Enroll today to gain demonstrable experience completing a capstone project that provides valuable practical experience you can discuss in interviews!

18 hours (7 weeks of study, 2-3 hours/week)

Systems and Solutions Architect Capstone Project


Data engineering processes have undergone an amazing transformation since the advent of Generative AI. In this course, you will explore the impact of generative AI on data engineering. You as a data engineer can use Generative AI to enhance productivity by introducing innovative ways to deliver projects.

Data engineering is responsible for building strong data pipelines, managing data infrastructure, and ensuring high-quality data evaluation.

This course is suitable for existing and aspiring data engineers, data warehousing specialists, and other data professionals such as data analysts, data scientists and BI analysts.

You will learn how to use and apply generative models for tasks such as architecture design, database querying, data warehouse schema design, data augmentation, data pipelines, ETL workflows, data analysis and mining, data lakehouse, and data repositories. You will also explore challenges and ethical considerations associated with using Generative AI.

Demonstrate your new generative AI skills in a hands-on data engineering project that you can apply in your real-life profession.

Then, complete your final quiz to earn your certificate. You can share both your project and certificate with your current or prospective employers.

Generative AI: Elevate your Data Engineering Career


AIX Operating System Fundamentals

This beginner-friendly course introduces AIX from the ground up, requiring no prior UNIX knowledge. You'll explore AIX's core components, navigate its file system, and perform basic operations. Learn to work with the vi editor, manage processes, and customize your environment. By the end, you'll gain practical skills to use AIX confidently, including writing simple shell scripts.


This course introduces administrative tasks that a system administrator can perform with Linux hosted on IBM Power servers. This includes virtualization concepts such as logical partitioning, installation of Linux, command-line operations, and more interesting administration and device management tasks.

This course includes hands-on exercises with systems from an IBM data center.

Linux System Administration with IBM Power Systems


Introduction to Technical Support

Technical Support professionals are in great demand! This is the first course in the IBM IT Support Professional Certificate program, designed to prepare you for a rewarding career in technical support.

You will begin this self-paced course by learning what Informational Technology (IT) support is all about. You'll find out the roles and responsibilities of Technical Support professionals and become familiar with all the different career paths you can take in Technical Support. You will also hear from experts in the IT industry about getting started in the field and how you can pursue this career without prior experience or degrees. You'll also learn some basics about the technology that technical support professionals use.

You will hear from industry insiders about how you can develop a customer support mindset and how to talk with customers and solve their problems. You will gain insights into performance evaluation, career paths, and the industry-recognized certifications that can propel your technical support career forward.

You'll then gain a comprehensive understanding of support tools and support channels and how they streamline issue resolution. You will also learn about the importance of Service-Level Agreements (SLAs) and how they contribute to delivering exceptional support experiences.

Next you will explore ticketing systems, a fundamental component of modern technical support. You'll learn about their features, benefits, and the lifecycle of a ticket or a support issue. Moreover, you'll immerse yourself in tech support methodologies, frameworks, and the art of effective documentation.

The course wraps up with a project that provides you with the opportunity to use a ticketing system hands-on and simulate the work that IT Support Specialists and Helpdesk Technician’s perform.


Ready to get hands-on exploring software, programming, and databases in this comprehensive introduction to the digital technologies transforming today’s workplaces?

During this course, you’ll build a strong foundation in computing platforms, software lifecycles, application compatibility, and cloud-based deployment. You’ll learn to install, manage, and secure modern web browsers using extensions and plug-ins. You’ll explore programming with coding logic and get hands-on using languages like Python. Plus, you’ll discover data and database fundamentals, including interfaces, backups, and real-world applications.

 You’ll also dive into cutting-edge concepts such as artificial intelligence (AI), generative AI, chatbots, and modern analytics applications. Additionally, you’ll explore data monetization strategies and gain insight into how organizations are leveraging data as an asset for growth and innovation.

Throughout, you’ll get hands-on experience in labs. Then, in a final project, you’ll apply your new skills in software, programming, databases, and emerging technologies.

Enroll today to build core skills you need to kickstart your career in IT!

Introduction to Software, Programming, and Databases


This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing.

By the end of this course you should be able to:
Retrieve data from multiple data sources: SQL, NoSQL databases, APIs, Cloud
Describe and use common feature selection and feature engineering techniques
Handle categorical and ordinal features, as well as missing values
Use a variety of techniques for detecting and dealing with outliers
Articulate why feature scaling is important and use a variety of scaling techniques

Who should take this course?
This course targets aspiring data scientists interested in acquiring hands-on experience  with Machine Learning and Artificial Intelligence in a business setting.

What skills should you have?
To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Calculus, Linear Algebra, Probability, and Statistics.

Exploratory Data Analysis for Machine Learning

Joseph Santarcangelo
Svitlana (Lana) Kramar


Linux on LinuxONE

This course is for Linux Systems Administrators, Architects and Developers who are already familiar with Linux components and everyday tasks, but need a primer on how to best take advantage of the LinuxONE platform. This includes working with the hardware, software, facilities, and processes unique to LinuxONE.  It is comprised of videos, links to online resources, and a final test for a badge.


This course is designed to prepare you to enter the job market as a data engineer. It provides guidance about the regular functions and tasks of data engineers and their place in the data ecosystem, as well as the opportunities of the profession and some options for career development. It explains practical techniques for creating essential job-seeking materials such as a resume and a portfolio, as well as auxiliary tools like a cover letter and an elevator pitch. You will learn how to find and assess prospective job positions, apply to them, and lay the groundwork for interviewing. You will also get inside tips and steps you can use to perform professionally and effectively at interviews. Let seasoned professionals share their experience to help you get ahead of the competition.

Data Engineering Career Guide and Interview Preparation


Introduction to Management Consulting

Many aspiring consultants struggle to break into the field, unsure of what management consulting really involves or how to develop the structured thinking that top firms demand.

This comprehensive introduction demystifies management consulting, taking you inside the profession to understand how consultants create value for organizations. From the top three or MBB firms to specialized boutiques, you'll explore the consulting landscape and identify your best-fit career path. Master foundational frameworks like MECE and hypothesis-driven thinking through hands-on exercises with real business cases. Learn to distinguish symptoms from root causes, structure ambiguous problems, and communicate solutions with impact.

Basic computer literacy. No prior consulting experience required.

This course is designed for aspiring management analysts, recent graduates considering consulting careers, professionals transitioning into consulting, and anyone seeking to understand the fundamentals of management consulting and structured problem-solving.

By course completion, you'll possess the analytical toolkit and professional insights needed to launch your consulting journey. Whether targeting traditional firms or internal consulting roles, you'll understand what excellence looks like and how to position yourself for success in this dynamic, rewarding field.


Working knowledge of SQL (or Structured Query Language) is a must for data professionals like Data Scientists, Data Analysts and Data Engineers. Much of the world's data resides in databases. SQL is a powerful language used for communicating with and extracting data from databases.

In this course you will learn SQL inside out- from the very basics of Select statements to
advanced concepts like JOINs.
You will:
-write foundational SQL statements like: SELECT, INSERT, UPDATE, and DELETE
-filter result sets, use WHERE, COUNT, DISTINCT, and LIMIT clauses
-differentiate between DML & DDL
-CREATE, ALTER, DROP and load tables
-use string patterns and ranges; ORDER and GROUP result sets, and built-in database functions
-build sub-queries and query data from multiple tables
-access databases as a data scientist using Jupyter notebooks with SQL and Python
-work with advanced concepts like Stored Procedures, Views, ACID Transactions, Inner & Outer JOINs through hands-on labs and projects

You will  practice building SQL queries, work with real databases on the Cloud, and use real data science tools.

In the final project you’ll analyze multiple real-world datasets to demonstrate your skills.

Databases and SQL for Data Science with Python


Data analytics professionals are in high demand around the world, and the trend shows no sign of slowing. There are lots of great jobs available, but lots of great candidates too. How can you get the edge in such a competitive field?

This course will prepare you to enter the job market as a great candidate for a data analyst position. It provides practical techniques for creating essential job-seeking materials such as a resume and a portfolio, as well as auxiliary tools like a cover letter and an elevator pitch. You will learn how to find and assess prospective job positions, apply to them, and lay the groundwork for interviewing.

The course doesn’t stop there, however. You will also get inside tips and steps you can use to perform professionally and effectively at interviews. You will learn how to approach a take-home challenges and get to practice completing them. Additionally, it provides information about the regular functions and tasks of data analysts, as well as the opportunities of the profession and some options for career development.

You will get guidance from a number of experts in the data industry through the course. They will discuss their own career paths and talk about what they have learned about networking, interviewing, solving coding problems, and fielding other questions you may encounter as a candidate. Let seasoned data analysis professionals share their experience to help you get ahead and land the job you want.

Data Analyst Career Guide and Interview Preparation


Application developers and DevOps professionals must ensure their app works at its best. However, these app may need help with bugs, slow speed, or subpar performance. Professionals need to monitor and observe its performance continually.

Application monitoring involves identifying, measuring, and evaluating the effectiveness of an application. On the other hand, Observability refers to how well an app can be monitored by the data obtained from monitoring. Both monitoring and observability are necessary to gain insights into the system and ensure its proper functioning.

This course thoroughly introduces monitoring and observability, covering fundamental concepts and popular tools like Prometheus, Grafana, Mezmo (LogDNA), and Instana. You will also learn about the three pillars of observability and tracing for container applications and gain hands-on experience with the OpenTelemetry framework.

Throughout the course, you will complete interactive hands-on labs to apply your knowledge, and gain experience with the tools and techniques used by software and DevOps professionals.

By the end of this course, you will be able to demonstrate your knowledge of monitoring and observability, and you will gain the confidence to perform these tasks in a practical setting.

Monitoring and Observability for Development and DevOps


Data Analysis with Python

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts!

This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy.

Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions.

By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement.

This course requires approximately two hours a week for six weeks.


Comprehensively prepare for the CompTIA A+ certification exam with expert-designed cheat sheets and 2 simulated mock exams.

During the course, you'll explore the A+ exam domains, testing strategies, eligibility requirements, and sign-up procedures. Plus, you’ll access 60+ pages of exam-focused cheat sheet content to support your certification preparation strategies.

To boost your preparation, you’ll then assess your Core 1 and Core 2 skills with ungraded practice exams. Plus, you’ll complete two graded, simulated mock exams that test your IT knowledge relative to the CompTIA A+ domains. These tests contain the same number and types of questions and exam timing as the official CompTIA A+ Core 1 and Core 2 Certification exams.

This course assumes basic familiarity with IT fundamentals (ITF+), Core 1, and Core 2 content. If you're new to these skills, consider completing the IBM IT Support Professional Certificate or IBM Information Technology (IT) and Cloud Fundamentals Specialization before enrolling in this course.

Limited time offer:  Pass your mock exams and receive a 30% discount voucher for the A+ Certification exams. Enroll today!

Practice Exams for CompTIA A+ Certification: Core 1 & Core 2


McKinsey estimates that generative AI (GenAI) can boost marketing productivity by up to 15%. Marketing professionals who can leverage GenAI to enhance efficiency, personalization, and content creation are in high demand. This course gives you the sought-after GenAI skills businesses need.

During the course, you’ll explore using GenAI to automate content creation, enhance ad copy, and personalize email campaigns and social media posts. You’ll learn to optimize digital advertising using AI for audience segmentation, creative refinement, and personalized campaigns. You’ll discover how AI can enhance SEO through keyword research, content optimization, and competitor analysis. You’ll explore AI-driven approaches for enhancing e-commerce experiences.

You’ll get hands-on practice generating engaging content, personalizing campaigns, and optimizing strategies for better results.

Additionally, you’ll examine ethical considerations, challenges, and best practices for AI integration in digital marketing.

If you’re looking to boost your career with in-demand GenAI skills businesses are looking for, enroll today and power up your resume in just a few weeks!

Generative AI: Accelerate your Digital Marketing Career


Deep Learning with PyTorch

Get hands-on experience in building and deploying intelligent systems using PyTorch by using one of the most widely used deep learning frameworks in AI development.

In this practical course, you’ll gain job-ready skills in deep learning, machine learning, and neural networks, boosting your resume for roles like AI Engineer, Machine Learning Engineer, and Data Scientist.

During the course, you’ll implement logistic regression and softmax regression, train deep neural networks, and build convolutional neural networks (CNNs) for real-world image classification tasks. You’ll master core techniques such as gradient descent, backpropagation, and cross entropy loss, while improving performance with weight initialization, dropout regularization, and batch normalization. Additionally, you’ll leverage GPU acceleration, perform hyperparameter tuning, and apply transfer learning using pretrained models such as ResNet18.

Finally, you’ll complete a project, where you’ll design, train, and evaluate models using modern model optimization and data preprocessing workflows. Great to talk about in interviews!

Enroll today to accelerate your career in deep learning, AI, and machine learning.


Get ready to power up your resume with the GenAI development skills employers need. During this course you’ll explore core prompt engineering strategies—like in-context learning and chain-of-thought—and create and manage robust prompt templates. Plus, you’ll follow best practices to handle common errors and experiment with different LLMs and configurations to strengthen your outputs.

You’ll then dive deeper into LangChain, mastering chains, tools, and agents to create smarter, more responsive applications. Through interactive labs, you’ll build a complete generative AI app using Python that accepts user input and processes it through your backend prompt logic. Plus, you’ll explore web-based interfaces using tools like Flask and Gradio, developing real-time user experiences powered by LLMs.

By the end, you’ll have the job-ready skills and demonstrable practical experience employers look for to design and implement full-stack GenAI apps that solve real-world problems. Sound good? Enroll today!

Develop Generative AI Applications: Get Started


Great consultants distinguish themselves not through individual skills but through their ability to synthesize diverse capabilities into coherent solutions.

This capstone course challenges you to integrate everything you've learned into a comprehensive consulting project. You'll tackle GlobalRetail Inc.'s transformation challenge, a multi-faceted problem requiring strategic repositioning, operational improvement, financial restructuring, and organizational change. Through progressively complex modules, you'll experience the full consulting lifecycle: scoping the engagement, conducting analyses, developing recommendations, creating deliverables, and presenting to executives. Unlike previous courses focusing on individual skills, this capstone emphasizes integration and synthesis.

By completion, you'll have created a complete consulting portfolio demonstrating your readiness to add value from day one in professional consulting roles.

Capstone: Integrated Management Consulting Project


SMP/E for z/OS Workshop

This course is designed to provide the SMP/E skills needed in the installation and maintenance of optional features and maintenance in the z/OS operating environment. Students are taught to define the SMP/E database and invoke SMP/E to add, modify, or replace system elements. The course includes extensive hands-on labs using a current level of SMP/E. Students will get practical experience in the SMP/E tasks involved in installing a z/OS product. Emphasis is on interpreting results of SMP/E processing. SMP/E concepts examined in this course include modification control statements, the consolidated software inventory, zone structure, and error analysis. SMP/E commands such as RECEIVE, APPLY, ACCEPT, RESTORE, REPORT, and LIST are discussed. Students will also learn how to perform automated SMP/E delivery of z/OS and product maintenance over the Internet with an automated SMP/E process that downloads and installs IBM preventive and corrective service over the Internet.
After completing this course, you should be able to:
•Describe how SMP/E is used as a tool for system maintenance
•Interpret modification control statements in a sample SYSMOD
•Create a consolidated software inventory database to support installation and maintenance requirements
•Use the SMP/E dialogs to install a product and its related service
•Manage exception SYSMOD data
•Describe the use of the primary and secondary data sets required by SMP/E
•Analyze output from SMP/E processing and resolve commonly encountered problems
•Describe the use of the REPORT command to determine software dependencies between zones
•Use the BUILDMCS process to create a function SYSMOD from an installed product and its service
•Use the new SMP/E functions to install software service automatically over the Internet
▪Implement support for communication server FTP client
▪Use the new RECEIVE ORDER command to order and install z/OS maintenance automatically over the Internet
•Use z/OSMF to install software and perform service update


Ready for an interactive learning experience to build real-world generative AI applications and chatbots?

In this hands-on course, you’ll develop a series of guided projects using Python, Flask, Gradio, and LangChain to create AI-powered applications for practical scenarios, including a voice assistant, a meeting summarizer, a language translator, and a personalized career coach. You’ll work with popular large language models (LLMs) such as GPT-3, Llama 2, and Flan-UL2, hosted on platforms like IBM watsonx and Hugging Face.

You’ll also explore advanced concepts, such as retrieval-augmented generation (RAG), to enhance LLM responses with external knowledge, and integrate speech-to-text (STT) and text-to-speech (TTS) using IBM Watson® Speech Libraries and OpenAI Whisper to enable voice interactions.

While a basic understanding of Python is essential, knowledge of HTML, CSS, or JavaScript is helpful but not required. The course includes supporting readings and videos to build foundational knowledge of the models and frameworks used. In addition, a comprehensive course glossary will help reinforce your learning.

Building Generative AI-Powered Applications with Python


This course introduces the foundational shift from traditional data engineering to AI-native data engineering.
Learners reframe data platforms and pipelines as intelligent, production-grade assets that power analytics, machine learning, generative AI systems, semantic search, RAG workflows, and AI-powered assistants.
This course explains how AI workloads consume data differently, introduces embeddings and vector retrieval as core primitives, demystifies LLMs as technical systems, and helps learners connect familiar data engineering skills to modern AI data lifecycles and AI-native architectures.
The updated Course 1 design also emphasizes that production AI-native systems require ownership boundaries and collaboration across data engineering, ML/AI engineering, application engineering, platform engineering, security/governance, and product teams.
By the end of the course, learners understand how modern AI systems are built end to end, how data engineering enables them, and how to redesign legacy pipelines to support semantic search, RAG, and AI-powered workflows.

Foundations of AI Native Data Engineering


Introduction to Software Engineering

Are you curious about the lucrative field that is software engineering and how you might be a part of it? This is the course for you! By taking this course, you will gain foundational knowledge of software development, programming, and the many exciting job roles and career paths that the IT industry offers.

Learn about the power of the Software Development Lifecycle (SDLC), and modern software development frameworks methodologies like Agile and Scrum. Explore fundamental programming principles and foundations of design, architecture, and deployment. The course offers a number of labs that will help you get important hands-on experience. These include getting started with an IDE, the basics of programming in Python, and Hello World in 10 languages.

The field of software engineering is growing at an estimated rate of 22% according to the US Bureau of Labor and Statistics. In addition to aspiring software engineers, front-end, back-end, full-stack developers, and DevOps professionals, this course is also suitable for those in related careers such as Product and Project Managers, IT Managers, Information Developers, UI/UX designers, and others who communicate and interact with software engineers.

You will learn about the different job opportunities and possible career paths in software engineering and hear from industry professionals about their daily work.
Software engineering professionals are in great demand, and now is the right time to learn more about this exciting domain. Start by enrolling now!


O curso Gestão para a Aprendizagem: Módulo Gestão Estratégica aborda uma nova concepção de gestão escolar focada na aprendizagem dos alunos e nas dimensões de trabalho do gestor visando o sucesso escolar, com foco na rede pública. O cerne do curso é o planejamento estratégico e os instrumentos práticos, tais como a caracterização da comunidade escolar, a avaliação de eficácia, a análise SWOT e o plano de ação.

Silvana Tamassia
Claudia Zuppini Dalcorso
Ednéia Regina Burger


Introdução ao Marketing Analítico

Público-Alvo
Profissionais, estudantes e interessados da área de Marketing que desejam conhecer os fundamentos básicos de Marketing Analítico e sua aplicação prática.

Objetivo do Curso
O curso tem como objetivo central introduzir o conceito de Marketing Analítico e apresentar de forma simplificada e prática algumas técnicas, de modo que o participante possa avaliar e recomendar decisões e ações em Marketing baseadas em análise de dados.

Objetivos de Aprendizagem
Ao final do curso o aluno será capaz de:
•	Explicar a importância de definir e utilizar métricas em Marketing.
•	Desenvolver métodos de levantamento de dados primários e secundários.
•	Desenvolver hipóteses testáveis inferindo causalidades.
•	Segmentar o mercado com base no comportamento do consumidor.
•	Gerar insights para o posicionamento de marca.
•	Suportar a tomada de decisões em Marketing com base em fatos e dados.

Dedicação e Carga-Horária
Cinco módulos temáticos de aproximadamente 3h cada, totalizando 15h. Cada módulo tem duração estimada de uma semana.

Assista ao vídeo de divulgação do curso: https://youtu.be/FvtgLAW_s8Y

5 módulos de 3h de atividades, totalizando 15h.

Carlos R. F. Bara
Danny Claro
Silvio Laban


Nesse curso, você irá entender um ingrediente fundamental da revolução digital: a amostragem, que permite que sinais como músicas e imagens sejam armazenados e processados em dispositivos digitais.

Processamento Digital de Sinais - Amostragem


剪辑：像编剧一样剪辑

剪辑台前，剪辑师就像厨师对待食材一样，摆弄着拍摄现场记录下来的影像片段，用影像和声音去捕捉线索和瞬间，讲述一个故事，同时赋予故事以力量、以情感。怎样平衡剪辑給画面带来的跳跃？当有几条情节线索相互穿插时，又应使用哪些剪辑手法？剪辑过程和编剧的过程一样，以叙事和抒情为最高准则，同时不断突破陈规，创造专属于自己的独特风格。本课程将带领学习者从剪辑开始，认识镜头，认识剪辑的语法，揭开微电影创作的神秘面纱。

5 周课程, 2-4 小时/周


Chinese Characters for beginner 汉字

Welcome to "Chinese Characters for beginner"!
This is an elementary course on learning Chinese characters. Together, we will start from the basic element of Chinese characters-- Strokes. Then we will learn 1,200 basic Chinese words composed of 240 commonly used Chinese characters, which begin with  “一”(one), including pronunciation, shape and meaning, so that to improve the learning effect.

①  Each Chinese character is with pinyin;

②  Each Chinese character is shown in the form of animation in the process of writing, namely strokes;

③  English translation is used on the Chinese character can be a word itself. Other Chinese characters can not be independent of words are the characters of. The English translation of this kind of characters is marked in parentheses;

④  Each Chinese word is accompanied by Pinyin, English translation and picture, which is easy to understand;

⑤  There are proper exercises at the end of each lesson.

Good luck !


透过摄影看世界

对于我们中的许多人来说，虽然拍照、分享和浏览照片已经成了日常生活中的习惯，但我们与图像的频繁接触并未培养我们在视觉表达上的素养。

这个课程的目的在于通过介绍影响摄影作品的创意、手段与技术，讨论观看照片与真正理解照片之间距离的问题。

在这个课程里，你将近距离观看纽约现代艺术博物馆收藏的照片，聆听从不同角度对照片的解读，以及摄影在将近180年历史中被使用的方式：作为艺术表现的途径、作为科学和探索的工具、作为纪实文献的媒介、作为讲述故事和记录历史的手段，以及作为日益视觉化的文化中一种交流和批评的模式。

学习目标

训练技巧，以便更好地检视和理解照片与摄影图像之间的不同。

发现语境如何影响摄影图像的制作、传播和接收。

学习摄影中各种不同模式的艺术和技术试验和创新。

探讨摄影在日益视觉化的文化中所发挥的作用

预估课时和工时： 学习为期六个星期，每星期需约1-2小时的时间。


创新思维

通过本门课程的学习，你的创新能力将会获得大幅提升。课程首先致力于观念的转变，其次我会讲到很多具体的创新思维和创新方法。创新并不仅仅是那些黑科技。解决生活或工作中碰到的每一个问题，都需要创新。每一个人的发展都会受到资源的制约，我希望这门课程里，你能找出制约自己发展的那些内部和外部条件，并创造性地解决，突破自己成长的天花板。

4 周课程, 1-3 小时/周

University of Science and Technology of China


社会调查与研究方法，
首先，是一套观察社会现象、测量社会现象的工具；
其次，是一套分析和运用社会现象数据的科学方法；
最高境界，则是一套针对社会、经济、教育、政治、法律、管理、公共卫生、新闻报道等人类的生产与生活现象，进行科学沟通的思维逻辑与表达方式。

社会调查与研究方法 （上）Methodologies in Social Research (Part I)


Data Structures and Algorithms (II)

By learning this course, you will get a comprehensive  grasp of stack, queue, binary tree, graph and BST structures and algorithms, as well as their applications. By the end of this course, you will be able to understand and implement stack, queue and binary tree, use binary trees to solve problems such Huffman encoding, understand and implement the graph structure as well as related algorithms such BFS, DFS and PFS, understand and implement  AVL tree.

通过学习本课程，你将全面了解栈、队列、二叉树、图和二叉搜索树结构、算法及其应用。 在本课程结束时，你将能够理解和实现栈、队列和二叉树，使用二叉树解决霍夫曼编码等问题，理解并实现图结构以及相关算法（例如BFS，DFS和PFS），理解并实现AVL树。


游戏产业概论

本课程为“初级课程”，为了适应初学者需求，章节安排分为三个板块。1-5章为初学者进行了知识普及和铺垫，6-7章为学员了解行业做进一步介绍，8-9章带领学员深入中国游戏行业了解产业发展和产品运营，层层进阶、循序渐进。而课程二《游戏策划与设计》整体知识难度将有升级，重视实操，请学员做好准备。
从游戏诞生之初至今已走过半个多世纪。但许多人任认为游戏产业并未成熟，然而其高速发展的势头引人注目。蕴含市场潜力的游戏产品推陈出新，品类丰富多样，终端靓丽时尚，游戏玩家人数激增，游戏产业逐渐成为欧、美、日、韩等国创意经济新的增长点。本课程包括游戏起源、游戏发展史、游戏分类、游戏的研发制作流程、世界游戏产业纵览和知识产权保护等章节，为培养成熟的游戏产业市场经理人打下良好基础。

9 周课程, 3-5 小时/周


生命安全与救援Life Safety and Rescue

人最宝贵的是生命，而在生命历程中充满着安全威胁与挑战。本课程以“珍爱生命、关注安全”为主线，期望通过该课程教学，努力增强学生在体育运动及野外活动中的安全防范意识，提高自我保护能力，掌握生存、自救和互救的基本技能，学会常见运动创伤的处置方法以及危险环境中的避险、自救和互助技能，具备应对突发事件的基本能力。


心理学与生活

心理学很神秘？你会发现，只要有人的地方，就有心理学！
心理学很深奥？你会发现，似乎每个人都是大众心理学家，谁都可以说点“心理学”。
的确，我们生活中处处都是心理学！但这门课程却要告诉你，我们常常挂在嘴边的“心理学”绝大部分是错的，剩下的一小部分也是不全面的。
在本课程中，我们会一起把看似复杂的心理学理论运用到简单的生活现象中，在理解和掌握心理规律和原理后，用独具的慧眼看到一个与原先完全不同的生活世界。


利用 Gemini CLI 加快应用开发速度

本课程的适用对象是想要借助于 Gemini CLI（一款专为终端打造并由 Gemini 提供支持的生成式 AI 智能体）来更智能地工作的应用开发者和 DevOps 工程师。

本课程探讨了 Gemini CLI 的安装和配置，并介绍了其应用场景和安全最佳实践。课程中还详细讲解了命令、工具、MCP 服务器和扩展程序。通过实践练习，您将安装和配置 Gemini CLI，并使用它来分析代码以及构建和修改应用。


在 Google Cloud 上将应用与 Gemini 集成

"这一简短的课程将介绍如何在 Google Cloud 上将应用与 Gemini 集成，可帮助您探索 Gemini API 及其生成式 AI 模型。此课程会教您如何通过代码访问 Gemini 模型。课程会安排您在应用中使用文本、图片和视频提示来测试这些模型的功能。


使用 Vertex AI 和 Flutter 构建生成式 AI 智能体

在本课程中，您将学习如何使用 Google 的可移植 UI 工具包 Flutter 来开发应用，并将开发的应用与 Google 的生成式 AI 模型家族 Gemini 相集成。您还将练习使用 Vertex AI Agent Builder，这是 Google 为构建和管理 AI 智能体及应用而提供的平台。


大学化学

本课程是北京大学开设的一门在线大学化学基础课，主要面向具有大学水平的化学初学者。课程内容基本涵盖全部基础化学概念。


真格—北大在线创业课堂

《真格北大创业课》是真格基金与北京大学国家发展研究院首次联合开发的中文“慕课”（MOOC, Massive Open Online Course，大型公开在线课程)。课程以创业为主题，共分为三个部分：创业前的准备工作，创业中的要点，以及融资、众筹的技巧等。此课程的目的是让所有有创业意愿的或者刚刚起步的创业者更好地了解现在中国创业行业的氛围，以及创业初期不得不知的干货。每节课都凝结了真格基金业内专家和北京大学资深教授的丰富知识，也包括多位成功创业者的实践经验。完成本课程之时，你将能够为自己绝妙的创意找到切实可行的商业模式，组建能力出色行动高效的团队，撰写专业具体可执行的策划书。在课程的最后，我们希望所有的学员可以完成一份完整的商业计划书，把自己的创业想法有效地表达出来。成功完成慕课的学生会得到由Coursera提供的真格基金与北京大学联合认证的付费认证书，并且其商业计划书会得到真格基金的认真考虑。

课程特点：
•	真格基金与北京大学国家发展研究院联合开发的首部中文“慕课”
•	徐小平、王强领衔，多位来自国内知名机构的专家和成功创业公司的创始人亲授
•	北京大学国家发展研究院BiMBA商学院张黎院长、杨壮院长对创业者倾力指导

•	专注于创业的在线课程
•	注重实践，最鲜活的案例教学
•	充分利用碎片化时间学习，每节课15分钟以内，每周仅需1-2个小时学习时间
•	无需相关教育或工作背景，对所有人开放

参与本课程，您将收获：
•	12位知名公益专家亲自设计的教学内容、资料
•	加入讨论区，与业内专家、资深教授和同行互动的机会
•	对中国创业大环境的进一步了解
•	为自己绝妙的创意找到切实可行的商业模式

•	组建能力出色行动高效的团队
•	撰写专业具体可执行的策划书
•	您在课程结束时提交的商业计划书将得到真格基金的认真考虑

除此之外，完成课程的同学可以获得由课程平台提供方Coursera颁发的付费认证证书（电子版）。获得认证证书要求同学们总体得分超过80%，并需向Coursera支付$29美金的费用。您可以先免费注册课程，开始学习课程后再选择支付证书费用。

3 周课程, 1-3 小时/周

徐小平 杨壮 王强 张黎


现代语言服务行业要求从业人员必须具有利用计算机及网络来使用各类技术辅助工具帮助其工作的能力，而不是仅仅学会几款狭义的计算机辅助翻译软件。

本课程主要讲授计算机辅助翻译技术的基础概念，学习多种计算机辅助翻译工具的使用方法，锻炼学生在技术环境下从事翻译工作等各类语言服务工作的能力，帮助学生理解信息化时代的语言服务工作。

课程完整涵盖现代语言服务的基本情况介绍、翻译技术基本概念、语言服务项目执行过程的信息环境与信息技术、如何利用电子辞典、网络资源及语料库工具辅助翻译工作、狭义和广义的计算机辅助翻译工具原理及实战演练、翻译内容质量评定、多人协同翻译项目、翻译管理等多方面的内容。作为翻译类专业学生的必修课程，本课程适合语言类专业学生学习。通过课程的学习，有助于学习者了解现代语言服务行业，增强各类计算机辅助翻译工具的使用技能，提高包括翻译工作在内的各类语言服务工作的效率。

该课程是“北大-德稻网络公开课程”中的一门，由北京大学与德稻教育联合提供。

本课程同时受到“语言能力协同创新计划”资助和支持。

Those who work in modern language service industry are required to be capable of using computers and Internet to aid their translation job by adapting a variety of efficient tools, rather than just using word processor tools and several basic computer-aided translation software.

This course teaches the basic concepts of computer-aided translation technology, helps students learn to use a variety of computer-aided translation tools, enhances their ability to engage in various kinds of language service in such a technical environment, and helps them understand what the modern language service industry looks like.

This course covers introduction to modern language services industry, basic principles and concepts of translation technology, information technology used in the process of language translation, how to use electronic dictionaries, Internet resources and corpus tools, practice of different computer-aided translation tools, translation quality assessment, basic concepts of machine translation, globalization, localization and so on. As a compulsory course for students majoring in Translation and Interpreting, this course is also suitable for students with or without language major background. By learning this course, students can better understand modern language service industry and their work efficiency will be improved for them to better deliver translation service.

The course is one of the PKU-DeTao MOOCs, which is a joint effort by Peking University and DeTao Masters Academy.

计算机辅助翻译原理与实践 Principles and Practice of Computer-Aided Translation


中日文化交流史

追溯日本文明发展的历史，阐明日本人独特的思考模式，解析日本独特的审美意识。本课程讲授公元前3世纪至清末的中日文化交流的历史。以文化艺术的交流为主线，以实地考察为背景展示了中日两国丰富灿烂的交流史实。通过中日双方在吸收对方文化过程中所表现出来的不同的受容方式剖析了中日文化之不同特性，可以帮助受课者准确地把握日本文化的内质，并启发其对自我民族历史文化之思考。生动的图片，倾心的讲授，可以让学习者在轻松愉快的氛围中完成六章的学习和有趣的试题，以期丰富学习者的人文积淀。


人群与网络

本课程是北京大学开设的一门在线跨学科选修课程，主要面向信息技术、社会学和经济学等专业的本科生。课程内容涉及用计算思维的方法讨论社会学和经济学的一些经典问题。学习运用计算思维分析社会学、经济学问题的方法，加深对某些生活现象的理解，体会计算与社会科学的互动。
Learn to analyze and reason about problems in social sciences with computational thinking, appreciate interactions between computing and social sciences, as well as gain deeper understanding of some common phenomena in life and society


刑法学总论 Criminal Law

刑法是规定犯罪与刑罚的法律。刑法学是研究刑法的科学，主要研究犯罪的成立条件以及刑罚的种类与适用刑法的制度等问题。本课程的主要目的是简明完整地说明现代刑法学总论的基本概念、基本理论与基本方法，包括的主要内容有刑法与刑法学的基本概念，刑罚的正当性，罪刑法定原则，刑法解释，刑法的适用范围，犯罪与犯罪构成的概念，犯罪构成的主要内容，排除犯罪的根据，犯罪的未完成状态，共同犯罪，刑罚的概念与体系，量刑制度，数罪并罚，缓刑、减刑与假释。本课程通过理论说明与案例分析对有关问题进行讲解，鼓励同学们通过刑法发展来认识刑法的生命，通过刑法比较来认识刑法的国际标准，通过确立刑法理想来追求社会的公平正义。

本课程将系统完整地说明、分析现代刑法学总论中的基本概念、基本理论。同学们通过本课程的讲述、案例的讨论、理论的分析，可以对现代刑法学知识的基本使用方法有一个完整的理解，从而有助于理解与分析现代社会面临的刑法问题。


计算机系统基础（一） ：程序的表示、转换与链接

本课程主要介绍高级语言程序中的数据类型及其运算、语句和过程调用等是如何在计算机系统中实现的。主要包含三个主题：（1）表示。不同数据类型（如带符号整数、无符号整数、浮点数、数组、结构等）数据在寄存器或存储器中的表示和存储；指令的格式、编码及其在存储器中的存储；存储地址（指针）的表示。（2）转换。高级语言程序中的过程（函数调用）、循环、选择等语句与机器级代码之间的对应关系。（3）链接。多个可重定位目标文件如何链接生成可执行目标文件并加载到系统中。
通过本课程的学习，使学习者能从程序员角度认识计算机系统，能够建立高级语言程序、ISA、OS、编译器、链接器等之间的相互关联，对指令在硬件上的执行过程和指令的底层硬件执行机制有一定的认识和理解，从而增强在程序调试、性能提升、程序移植和健壮性等方面的能力，并为后续的“计算机组成与设计”、“操作系统”、“编译原理”、“计算机体系结构”等课程打下坚实基础。
学完本课程后，学习者将对以下问题有比较深刻的认识，并能解决相关实际问题。
----程序中处理的数据在机器中如何表示和运算？
----程序中各类控制语句对应的机器级代码结构是怎样的？
----多个程序模块是如何链接起来形成可执行目标文件的？
----机器级代码及构成机器级代码的指令是如何在机器上执行的？


.Net平台下的软件开发技术毕业项目

毕业设计项目将综合5门课程所学知识，设计完成一个基于.Net平台的小型软件项目，以验证你是否具备了.Net应用程序开发的基本能力。

项目具体要求如下：
1. 该系统应该包括客户端和管理端；
2. 客户端包括以下功能：
①用户登录；
②用户注册；
③菜品订购；
④购物车功能；
⑤订单增、删、改、查功能；
3. 管理端包括以下功能：
①用户管理；
②订单管理（增、删、改、查）；
③菜品管理（增、删、改、查）；
④统计管理（日销量、月销量、用户订餐细节）。

如果你能够在.Net环境下利用C#语言独立完成毕设项目，说明你已经达到面向.Net框架的初级程序员水平。

8周学习时间，每周1-3小时


系统平台与计算环境

* "系统平台与计算环境"仅是"大学计算机"系列课程的第一部分，我们将在不久的未来推出“算法与C语言编程基础”，"大学计算机"系列课程的第二部分，敬请关注！*

计算机科学是研究抽象和自动计算的学科，涉及的理论知识众多。作为计算机科学的入门，“大学计算机”系列课程将从基础知识入手，循序渐进，帮助你在了解计算机系统整体结构和基本原理的基础上，具备“选择和利用各种已有工具软件解决问题的能力”和“编写程序解决一般专业问题的能力”。

本系列课程由“系统平台与计算环境（第一部分）”和“算法与C语言编程基础（第二部分）”两门课程构成。每门课程独立开设，既自成一体，又相互衔接，构成体系。本课程，即第一部分的内容，将涉及计算模型与信息表示、软硬件系统组成及工作原理、网络技术及应用、OFFICE基本操作等多个知识模块。本课程的学习目标是了解计算机软硬件系统组成、信息表示方法、网络技术等计算机学科的基础知识和基本操作技能；在未来我们将提供系列课程第二部分的学习目标，即学会编写简单的C语言控制台程序以及排序、查找等基本算法。

本课程是学习计算机的入门课程，无需信息技术方面的基础，但需要你会一些计算机的基本操作，比如：文字录入、通过网络获取信息（网络信息检索）等。

吴 宁
陈 文革
杨 忠孝


使用 BigQuery 机器学习推理功能

了解 BigQuery 机器学习推理功能，以及数据分析师为何应使用该功能，它有哪些应用场景，有哪些受支持的机器学习模型。您还将了解如何在 BigQuery 中创建和管理这些机器学习模型。


Chinese for HSK 4

大家好！Hi, everyone, welcome to join our Chinese for HSK Level 4 course. This is CHEN Li and LU Yun, and we are very happy to meet you here!
Chinese for HSK 4 is a 10-week course. It consists of two parts: Part I, which is a 6-week program, covers vocabulary and grammar delivered mainly through dialogues and passages; Part II takes 4 weeks to complete and the foci are exercises and testing strategies.
Chinese for HSK 4 aims at the fourth level of HSK. It is the counterpart of Level 4 of the Chinese Language Proficiency Scales for Speakers of Other Languages and the B2 Level of the Common European Framework of Reference for Languages.
Chinese for HSK 4 includes:

	424 new HSK 4 vocabularies;
	Detailed explanation  about 96 key words and grammar points;
     Analyze reading and listening materials from Official Examination Paper of HSK Level 4
     Review the words you have learnt in HSK 1 、HSK 2、HSK 3 courses.
	New words and texts via audio;
	Quizzes  for each lesson and HSK test papers;

At the end of the course, you will be able to converse in Chinese on a wide range of topics and are able to communicate fluently with native Chinese speakers.
Specifically, you will master certain grammar knowledge containing fundamental sentence structure and usage like sentences with “不仅A而且/还B”(not merely A, but also B);“无论(A还是B)，都.....”(whether A or B);“既然…..就…..” (since); “在…….下" (on the condition of );“即使……也”(even though/if );“甚至" (even to the extent that) ;“千万要/不要/别”(make sure to ) and so on.
It does not matter if you complete HSK Level 3 or not, as long as you have obtained elementary Chinese language competency. Hope you enjoy our HSK courses.
CHEN Li, LU Yun and Chinese for HSK Level 4 team.


Gemini in Gmail - 简体中文

Google Workspace 专用 Gemini 是一个插件，可在 Google Workspace 中为客户提供生成式 AI 功能。在本迷你课程中，您将了解 Gemini 的主要功能，以及如何在 Gmail 中使用这些功能来提高工作效率。


全球卫生导论

全球卫生导论回顾了全球范围内公共卫生发展的各个历史时期令人关注及其影响重大的事件，介绍公共卫生、国际卫生和全球卫生等相关概念和背景，阐述全球疾病负担、健康决定因素、主要健康问题及其应对策略，剖析目前全球关注的影响健康的主要卫生问题，从群体的层面的因素分析到个体层面的行为指导，分析社会发展、卫生系统、公共政策和全球合作对人群健康状况的决定作用。
全球卫生以提高全球范围内的健康水平、实现全球健康公平为宗旨，重点关注超越国界的健康问题、健康决定因素和解决方案，涉及医学领域内外的多学科，提倡不同学科间的通力合作和人群预防与临床治疗的综合，同等对待不同地域、不同经济水平、不同的种族的所有人群。作为一门普适型的全球卫生导论课，旨在使不同学科和专业领域的学习者能了解全球卫生的历史和相关概念，熟悉全球疾病负担、健康决定因素、主要健康问题和全球应对策略。
课程内容包括全球卫生概述、卫生系统与筹资、全球疾病负担、环境与健康、营养/生活方式与健康、妇幼保健与生殖健康、耐药结核病流行与控制、艾滋病的流行与控制、老龄化与慢性病防治、突发公共卫生事件应对等。
授课团队由复旦大学公共卫生学院各二级学科的带头人和资深教授组成。本课程期望能引起不同学科的学生对全球健康问题的关注，激发其致力于探究健康相关问题的兴趣，引导其分析健康问题的社会决定因素，赋予其用合力解决全球健康问题的理念。

陈文 姜庆五 陈英耀 何更生 钱序 阚海东 徐飚 何纳 傅华 赵根明 丁永明


AI 基础设施：部署类型

本课程全面指导如何在 Google Cloud 上部署、管理和优化 AI 和高性能计算 (HPC) 工作负载。通过一系列课程和实际演示，您将探索从基于 Google Compute Engine (GCE) 的高度可定制环境，到 Google Kubernetes Engine (GKE) 等托管式解决方案的各种部署策略。具体来说，您将学习如何创建集群并部署 GKE 进行推理。


本课程介绍了 AI 可解释性和透明度的相关概念，探讨了 AI 透明度对于开发者和工程师的重要性。同时探索了有助于在数据和 AI 模型中实现可解释性和透明度的实用方法及工具。

Responsible AI for Developers: Interpretability & Transparency - 简体中文


抗菌药与超级细菌 －－天使与魔鬼的博弈

超级细菌肆虐、感染无药可医，人类正面临前所未有的困境。
面对这危及每个人的严酷现实，是坐以待毙还是奋力反击？相信你心中已有答案。
本课程将以独特、新颖的视角，为你展现抗菌药和超级细菌间博弈的历程；以深入浅出、生动形象的课件，教你抗菌药与超级细菌的知识；以浅显易懂、亦庄亦谐的教学情景剧，让你辩证地看待菌药的关系。
战争已经打响，智慧勇敢的你，快来加入我们的行列，从自身做起阻止超级细菌的产生与蔓延。


高阶竞争策略（中文版）

与之前的“竞争策略”(https://www.coursera.org/learn/competitivestrategyzh)相比，“高阶竞争策略”课程将在讲解新课题和新模块的同时，结合更多实际案例并提供更多与学生互动交流的机会。

在“高阶竞争策略”课程中，我们将研究企业如何通过增加转换成本和推进战略客户锁定来建立和维护客户群。探索企业如何通过寻求适当的价格歧视和产品差异化策略来提高收益。

我们将举例介绍在欧盟竞争政策和美国反垄断政策前提下可接受的行为，并且找到企业通过战略性利用网络效应和规模经济来增加回报的方法。我们会进一步强化新学的有关网络效应的知识，并讨论专门为网络市场定制的策略。

我们还会分析兼并和收购的运作方式，此外，帮助您思考有助于公司有机增长的其他策略。

This is a Chinese version of Advanced Competitive Strategy. You can find the original course in English from our course catalog.
【 此版本是Coursera首次尝试推出的中文翻译版。课程视频为英文原版附中文字幕，课程页面和测验已译成中文，帮助中心提供中文支持。此版本仍在测试中，欢迎批评指正。】


AI 时代安全性简介

人工智能 (AI) 具备巨大的变革潜力，但也带来了新的安全挑战。本课程专为负责安全性和数据保护的领导者而设计，助其运用相关策略在组织内安全管理 AI。学习一个有助于实现以下目标的框架：主动识别并减轻 AI 特有的风险，保护敏感数据，确保遵从法规，构建弹性 AI 基础设施。通过四个不同行业的精选用例，探索这些策略如何应用于现实场景。


使用 Google Cloud Operations 进行扩缩

各种规模的组织都在利用云的强大功能和灵活性来改变运营方式。然而，有效管理和扩缩云资源可能是一项复杂的任务。本课程探讨了云中现代运营、可靠性和弹性方面的基本概念，以及 Google Cloud 如何帮助支持这些工作。

作为 Cloud Digital Leader 学习路线的一部分，本课程旨在帮助个人在自己的岗位上成长，并为企业谋求未来发展。


操作系统原理（Operating Systems）

《操作系统原理》是针对计算机科学技术专业三年级本科生开设的一门专业基础课程。本课程着重学生系统观的培养，通过重点讲述操作系统的内部结构、工作原理及典型技术的实现，使学生建立起对操作系统的整体及各个功能模块的认识，从而系统掌握计算机的专业知识，进一步提升学生的软件开发能力乃至系统软件开发能力。

任何计算机都必须在加载相应的操作系统之后，才能构成一个可以运转的、完整的计算机系统。操作系统的功能是否强大，决定了计算机系统的综合能力；操作系统的性能高低，决定了整个计算机系统的性能；操作系统本身的安全可靠程度，决定了整个计算机系统的安全性和可靠性。操作系统是软件技术的核心和基础运行平台。因此，计算机科学技术专业的学生需要学习和掌握操作系统的基本原理和专业知识。

本课程的教学目标是：

1．掌握操作系统的基本概念、功能组成、系统结构及运行环境；

2．熟悉并运用操作系统工作原理、设计方法和实现技术，理解有代表性、典型的操作系统实例（如UNIX、Linux和Windows）；

3．了解操作系统的演化过程、发展研究动向、新技术以及新思想，为后续相关课程的学习打下良好基础，为后续职业发展奠定基石。


手把手教你心理咨询：谈话的艺术

心理咨询似乎很神秘，我们常常想靠近它，但又害怕靠近它！
所以，才有了“手把手教你心理咨询”这门系列课程。我并不是要教你成为一名心理咨询师，而是要帮助你了解心理咨询、懂得心理咨询。并且手把手地教会你，将心理咨询的理念和技巧，合理、恰当地运用到你的实际生活中去，让你的生活变得更加和谐、更加精彩！
“谈话的艺术”是“手把手教你心理咨询”系列课程中的第一门课，在这门课当中的所有情景展示，都是基于我们日常生活中的谈话，而并非是真正的心理咨询。因为我想告诉你，心理咨询并不是什么神秘、高深的技术。只要愿意学习，你也可以掌握其中的基本方法；只要运用得当，你会让你自己和你身边的人从中受益！

5周学习，2-3小时/周


Data Structures and Algorithms (IV)

By learning this course, you will get a comprehensive grasp of Priority Queues and string match techniques, as well as their applications. By the end of this course, you will be able to understand/implement Bucketsort, Counting-sort, and Radixsort, understand the principle/implementation/application of different Priority Queues such as complete binary heap and leftist heap, understand and implement Heapsort, understand and implement typical string matching algorithms such as KMP, BM, and Karp-Rabin, implement and analyze advanced selection/sorting algorithms such as Quicksort, QuickSelect, LinearSelect, and Shellsort.

通过学习本课程，你将全面了解优先级队列和字符串匹配技术及其应用。 在本课程结束时，你将能够了解/实现桶排序，计数排序和基数排序，了解不同优先级队列的原理/实现/应用，例如完全二叉堆和左倾堆，了解并实现堆排序，了解并实现典型的字符串匹配算法（例如KMP，BM和Karp-Rabin），实现并分析高级选择/排序算法，例如快速排序、快速选择、线性选择和希尔排序。


在本课程中，您将了解 Google Cloud 中依托生成式 AI 技术的协作工具 Gemini 如何帮助开发者构建应用。您将学习如何向 Gemini 输入提示，让其为您解释代码、推荐 Google Cloud 服务并为您的应用生成代码。您将通过实操实验体验 Gemini 对应用开发工作流的改进作用。

Duet AI 已更名为 Gemini，这是我们的新一代模型。

Gemini for Application Developers - 简体中文


编剧：像导演一样编剧

电影编剧不同于文学创作，它意味着要以影像化、动作化的方式赋予故事生命，在这个意义上，编剧不仅是导演，而且还是那个灵动的新世界的创造者。这个世界中的每一个人物命运，每一个起承转合，都表达着创作者对于人性的判断和立场。本课程将通过丰富的案例和针对性的练习，阐述电影编剧的基本步骤、基础知识和内在规律。

4 周课程, 2-4 小时/周

许 肖潇
梁永安
龚金平


生物学概念与途径

《生物学概念与途径》课程由饶毅2008年在北京大学设立和主持，面向所有大学生和研究生，目的是让年轻的学生了解生物学历史上，一些重要的概念是如何提出的，一些重要的途径和方法是如何用来解决重要且有深刻意义的生物学问题的。
        大部分内容由饶毅讲授，带着大家一起解读1866年孟德尔的遗传学论文，解读1910年摩尔根的果蝇论文，解读1944年Avery、McLeod、McCarty如何提出DNA是遗传物质的论文。这些经典性的工作，让我们从思想上理解科学研究是怎么做的。
        北京大学物理系的汤超教授、哈佛大学的谢晓亮教授、北京生命科学研究所的王晓东教授、北京大学化学院何川教授、清华大学的施一公教授、北京大学的植物生物学的邓兴旺教授和顾红雅教授，分别从物理的定量、化学与生物的交叉、生物化学的经典实验、化学角度的生物大分子、结构生物学、现代农业生物技术与种业发展、驱动演化的“力”等多学科，多角度讲授重要的概念和途径。
        本课程重思想，重交叉，重培养学生的科学能力；培养科学研究的价值观（比如判断什么是好的科学），力求为未来科学探索树立参照系；老师提供一个起点，能看的多深，发展多远，取决于同学们的天赋和努力。
        希望大家通过我们的慕课有所收获。


"本课程能让机器学习从业者掌握评估生成式和预测式 AI 模型的基本工具、方法和最佳实践。要确保机器学习系统在实际运用中提供可靠、准确、高效的结果，做好模型评估至关重要。
学员将深入了解各项评估指标、方法及如何在不同模型类型和任务中适当应用这些指标和方法。课程将着重介绍生成式 AI 模型带来的独特挑战，并提供有效解决这些挑战的策略。通过利用 Google Cloud 的 Vertex AI Platform，学员可学习如何在模型选择、优化和持续监控工作中实施卓有成效的评估流程。"

Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - 简体中文


MOOC and Blended Learning

The development of online education has brought opportunities and challenges for traditional teaching and learning. Nowadays it’s very important to learn about online education, which can help us study better and more easily.
This course focuses on 5 themes:
1.interpreting online education
2.discussing why online education is needed
3.explaining the current status of online education in colleges and universities
4.predicting the future of online education,
5.sharing online education practices and experiences from a large number of excellent teachers
Follow us on Facebook Page and Twitter (@TsinghuaX).


Google Workspace 数据治理

本课程旨在帮助学员掌握在 Google Workspace 环境中管理数据的技能。学员将探索如何在 Gmail 和云端硬盘中利用数据泄露防护规则来防止数据泄露。然后学习如何使用 Google 保险柜来保留、保存和检索数据。接着，学员将学习如何配置数据区域和导出设置，以遵循监管法规。最后，学员将了解如何使用标签对数据进行分类，以强化组织管理并提升安全性。


借助 Gemini Enterprise 加速知识交流

Agentspace 结合了 Google 在搜索和 AI 领域的专长。它是一款企业工具，让员工只需通过一个搜索栏，就能从文档库、电子邮件、聊天消息、工单系统及其他数据源中查找具体信息。Agentspace 助理还能帮助进行头脑风暴、开展研究、生成文档大纲并执行其他操作，比如邀请同事参加某日历活动。因此它能加快知识型工作的进度并提升协作效率。


了解 Google Cloud 智能体

本课程全面概述了 Google Cloud 的智能体平台，包括 Vertex AI Agent Builder、Gemini Enterprise、Conversational Agents 和智能体开发套件。学员将了解每项产品的独特功能，区分具体应用场景的最佳解决方案，并获得有关创建搜索和聊天应用的基础知识。


这是一节入门级微学习课程，探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能，还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。

Introduction to Large Language Models - 简体中文


软件测试 (Software Testing)

从认识和理解软件Bug开始，介绍软件测试的基本理论，阐述软件测试设计的多样性原理。基于多样性原理，介绍白盒测试方法和黑盒测试，具体包括随机测试、等价类测试、控制流测试、数据流测试等；邀请业界专家讲解功能测试、性能测试、移动应用测试技术。


Business Chinese 1 中级汉语 （上）

《中级汉语(商务篇)》慕课是为汉语水平达到HSK三级的外国留学生制作的汉语学习慕课。它以汉语语言知识和交际技能为主要教学内容，培养留学生在一般工作情景和真实商务情境中运用汉语进行交际的能力，将生活汉语与商务汉语有机融合，情境设计贴近飞速发展的科技和商务生活，能同时满足留学生日常生活、学习和工作的需求。语法内容涵盖了HSK 三、四、五级考纲中的所有语法重点及要点；语料新鲜而实用，以HSK三、四、五级词汇为主。学习结束后汉语能达到HSK四、五级的水平，并兼具生活和基本商务交际语言技能。

The MOOC of Intermediate Business Chinese is designed for the Chinese language learners who have reached HSK level 3. The MOOC presents lively, authentic, and up-to-date dialogues for daily conversations and business communications. The contents integrate trendy technologies with real-life situations that can be applied to everyday lives, language classrooms, and working places.  The course also covers all the key grammar points and patterns in HSK level 3-5. Students are expected to reach HSK level 4-5 when they complete the course and be able to effectively communicate in daily lives and professional settings from intermediate-mid to advanced-low levels.

5-6周的学习，5-8小时/周


I contenuti di questo corso sono pensati per permettere agli utilizzatori di Tableau di migliorare le proprie capacità sull’uso del tool, a un livello intermedio.

Spesso i dati provengono da fonti diverse; dobbiamo quindi essere in grado di stabilire tra questi delle relazioni che ci permettano di includere in un’analisi tutte le informazioni di cui abbiamo bisogno. Vedremo quindi come costruire queste relazioni su Tableau, ricorrendo a Join, Union e Data Blending.

Lavoreremo con i campi calcolati e i parametri. I primi sono nuovi campi (dimensioni e misure) che, a partire dalla logica utilizzata, aggiungono nuovi dati al data base di partenza. I secondi, invece, sono valori dinamici che possono essere impiegati in tantissimi modi per personalizzare i propri calcoli e la loro visualizzazione all’interno dello spazio di lavoro.

Vedremo come Tableau esegue le operazioni di calcolo secondo un ordine preciso, che influisce sui risultati dei calcoli che facciamo. Andremo infine a lavorare con i dati geografici. Nel processo analitico, sono diverse le domande che possiamo porci. Padroneggiando le conoscenze sulla manipolazione dei dati geografici possiamo rispondere al “dove”, un aspetto fondamentale da considerare nel processo analitico.

Data Visualization e manipolazione dei dati con Tableau


"In questo corso, ""Architecting with Google Kubernetes Engine: Foundations"", troverai un ripasso del layout e dei principi di Google Cloud, seguito da un'introduzione alla creazione e alla gestione dei container software, nonché all'architettura di Kubernetes.

 Si tratta del primo corso della serie Architecting with Google Kubernetes Engine. Dopo il completamento di questo corso, iscriviti al corso Architecting with Google Kubernetes Engine: Workloads."

Architecting Google Kubernetes Engine: Foundations in italiano


L’obiettivo del corso è formare professionisti della Business Intelligence attraverso l’apprendimento della piattaforma Tableau, strumento leader di questo settore. La mole di dati a disposizione è sempre più grande ed estrarre informazioni utili per sfruttare queste informazioni è compito degli analisti.
Un ruolo cruciale lo riveste la data visualization: il tassello del processo analitico che permette di capire come rappresentare al meglio i propri dati per elaborare strategie data-driven.
In questo corso verranno presentate tutte le funzionalità di Tableau Desktop, il tool dedicato alla costruzione delle analisi dei dati.
Introduciamo i diversi prodotti della suite Tableau, l’interfaccia grafica e gli ambienti di lavoro, per passare, infine, alla presentazione delle unità minime del lavoro su Tableau: dimensioni, misure e tipi di dato. Vengono illustrati i contenuti relativi ai modi e ai tipi di connessione ai dati, e le strategie di selezione e organizzazione dei dati. Infine tutti gli elementi necessari per imparare a combinare insieme i dati e lavorare con set, date e misure multiple.

Introduzione alla Data Visualization con Tableau


Questo corso introduce i concetti di AI responsabile e i principi dell'AI. Tratta le tecniche per identificare sostanzialmente l'equità e i bias e mitigare i bias nelle pratiche di AI/ML. Illustra metodi e strumenti pratici per implementare le best practice dell'AI responsabile utilizzando gli strumenti open source e i prodotti Google Cloud.

Responsible AI for Developers: Fairness & Bias - Italiano


I due componenti chiave di qualsiasi pipeline di dati sono costituiti dai data lake e dai data warehouse. In questo corso evidenzieremo i casi d'uso per ogni tipo di spazio di archiviazione e approfondiremo i dettagli tecnici delle soluzioni di data lake e data warehouse disponibili su Google Cloud. Inoltre, descriveremo il ruolo di un data engineer, illustreremo i vantaggi di una pipeline di dati di successo per le operazioni aziendali ed esamineremo i motivi per cui il data engineering dovrebbe essere eseguito in un ambiente cloud.

Questo è il primo corso della serie Data Engineering on Google Cloud. Dopo il completamento di questo corso, iscriviti al corso Building Batch Data Pipelines on Google Cloud.

Modernizing Data Lakes & Data Warehouses with GC - Italiano


L'elaborazione dei flussi di dati sta diventando sempre più diffusa poiché la modalità flusso consente alle aziende di ottenere parametri in tempo reale sulle operazioni aziendali. Questo corso tratta la creazione di pipeline di dati in modalità flusso su Google Cloud. Pub/Sub viene presentato come strumento per la gestione dei flussi di dati in entrata. Il corso spiega anche come applicare aggregazioni e trasformazioni ai flussi di dati utilizzando Dataflow e come archiviare i record elaborati in BigQuery o Cloud Bigtable per l'analisi. Gli studenti acquisiranno esperienza pratica nella creazione di componenti della pipeline di dati in modalità flusso su Google Cloud utilizzando QwikLabs.

Building Resilient Streaming Analytics Systems on GCP IT


Quali sono le radici più profonde di quel mix di culture che chiamiamo ‘civiltà mediterranea’? Quali commistioni e quali scambi hanno prodotto il suo frutto più completo, ossia la città, come luogo delle comunità che plasmano il loro territorio e i loro spazi? Quali elementi formarono il sostrato condiviso di usanze, tradizioni, idee, scoperte ed innovazioni che hanno messo a confronto e mischiato popoli diversi per millenni. Cosa ha fatto, dalla ceramica alla metallurgia, dalla gastronomia all’architettura, dall’arte alla religione di un mare una culla di civiltà? L’archeologia può servire a sviluppare queste domande e cercare delle risposte non scontate, toccando con mano quello che gli antichi popoli del Mediterraneo ci hanno lasciato. Punto di osservazione privilegiato del corso è l’antica città fenicia di Mozia, posta al centro del “mare di mezzo”. Attraverso l’esperienza diretta dello scavo, con immagini prese dal vivo, il corso vuole far toccare a chi vorrà parteciparvi le tessere del grande mosaico della civiltà mediterranea. Il diario dello scavo - il libro dell’archeologo - e la piccozzina usata per scavare saranno i due strumenti che ci condurranno attraverso il mare a scoprire cosa furono realmente queste antiche città, e come il loro contributo è ancora parte della nostra memoria condivisa.

Alle origini della civiltà  mediterranea: archeologia  della città dal Levante  all’Occidente - III-I millennio a.C.


Questo corso spiega agli studenti come creare soluzioni efficienti e ad alta affidabilità su Google Cloud utilizzando pattern di progettazione comprovati. È la continuazione del corso Architecting with Google Compute Engine o Architecting with Google Kubernetes Engine e presuppone che si abbia esperienza pratica con le tecnologie esaminate in uno dei due corsi. Attraverso una combinazione di presentazioni, attività di progettazione e lab pratici, i partecipanti impareranno a definire e bilanciare i requisiti aziendali e tecnici per progettare deployment Google Cloud estremamente affidabili, sicuri, economicamente convenienti e ad alta disponibilità.

Reliable Cloud Infrastructure: Design & Process italiano


Questo è un corso di microlearning di livello introduttivo volto a spiegare cos'è l'IA responsabile, perché è importante e in che modo Google implementa l'IA responsabile nei propri prodotti. Introduce anche i 7 principi dell'IA di Google.

Introduction to Responsible AI - Italiano


Google Cloud Fundamentals: Core Infrastructure introduce concetti e terminologia importanti per lavorare con Google Cloud. Attraverso video e lab pratici, questo corso presenta e confronta molti dei servizi di computing e archiviazione di Google Cloud, insieme a importanti strumenti di gestione delle risorse e dei criteri.

1 settimana di studio, 6-10 ore/settimana

Google Cloud Fundamentals: Core Infrastructure in italiano


Questo corso accelerato on demand illustra ai partecipanti l'infrastruttura completa e flessibile e i servizi di piattaforma forniti da Google Cloud. Attraverso una combinazione di videolezioni, demo e lab pratici, i partecipanti potranno esplorare gli elementi delle soluzioni, tra cui interconnessione sicura delle reti, bilanciamento del carico, scalabilità automatica, automazione dell'infrastruttura e servizi gestiti.

Elastic Cloud Infrastructure: Scaling & Automation italiano


Questo è un corso di microlearning di livello introduttivo volto a spiegare cos'è l'AI generativa, come viene utilizzata e in che modo differisce dai tradizionali metodi di machine learning. Descrive inoltre gli strumenti Google che possono aiutarti a sviluppare le tue app Gen AI.

Introduction to Generative AI - Italiano


Attention Mechanism - Italiano

Questo corso ti introdurrà al meccanismo di attenzione, una potente tecnica che consente alle reti neurali di concentrarsi su parti specifiche di una sequenza di input. Imparerai come funziona l'attenzione e come può essere utilizzata per migliorare le prestazioni di molte attività di machine learning, come la traduzione automatica, il compendio di testi e la risposta alle domande.


Python: Istruzioni per l’uso

Il Corso fornisce i principi di programmazione, le tecniche e gli strumenti di Python, linguaggio interpretato orientato agli oggetti molto utilizzato in molteplici contesti scientifici ed aziendali.
Python è un linguaggio di programmazione di alto livello, supporta diversi paradigmi di programmazione, come il paradigma object-oriented (con supporto all'ereditarietà multipla), imperativo e funzionale. Ha ottenuto un enorme successo nelle comunità dei programmatori grazie al connubio unico tra la semplicità di apprendimento e la potenza offerta dalle sue librerie.

Questo corso fa parte della Specialization in Data Science con Python e R, cui sarà possibile iscriversi non appena il corso sarà partito.


Questo corso vi insegna i semplici principi che usano i manager esperti per migliorare e motivare le prestazioni dei dipendenti. Non dovete mai evitare di dire a un dipendente "la verità" di nuovo, perché le sette tecniche che insegnamo non metteranno i dipendenti alla difensiva né li spaventeranno. Come manager, o se volete diventarlo, imparerete nello specifico cos'è un feedback, come il feedback negativo pesa di più di quello positivo e come il feedback positivo può migliorare comportamenti come la creatività o il lavoro in gruppo.

Dare feedback è un'abilità che si sviluppa con il tempo. Vi forniamo un processo che potete usare per migliorare le vostre abilità di feedback e per poterli fornire con sicurezza. Scoprirete che esiste una base scientifica per molte delle osservazioni e intuizioni relative ai feedback - come ad esempio, che è difficile darli correttamente, che alle persone non piacciono e altro ancora. Questo corso vi rassicurerà, poiché imparerete come superare queste difficoltà. Speriamo che vi divertirete diventando un manager migliore!

Fornire un feedback utile (Giving Helpful Feedback)


Gemini in Google Sheets - Italiano

Gemini per Google Workspace è un componente aggiuntivo che fornisce ai clienti funzionalità di AI generativa in Google Workspace. In questo mini corso imparerai le funzionalità principali di Gemini e come possono essere utilizzate per migliorare la produttività e l'efficienza in Fogli Google.


Questo corso introduce argomenti importanti relativi alla privacy e alla sicurezza dell'AI. Esplora metodi e strumenti pratici per implementare le pratiche consigliate per la privacy e la sicurezza dell'AI utilizzando gli strumenti open source e i prodotti Google Cloud.

Responsible AI for Developers: Privacy & Safety - Italiano


In questo corso, esploreremo come il debito e l'equità possono essere utilizzati per finanziare gli investimenti infrastrutturali e come gli investitori affrontano questi investimenti. Scopriremo l'importanza cruciale delle infrastrutture nelle economie moderne e l'evoluzione delle modalità di finanziamento nel contesto delle crescenti esigenze globali.

Il corso si articola in 5 moduli per la durata di circa 7 ore, distribuiti su 5 settimane. Tratteremo l'importanza delle infrastrutture, le fonti di finanziamento pubbliche e private, l'evoluzione delle infrastrutture e il project financing. Analizzeremo anche l'attenzione crescente verso la sostenibilità e i criteri ESG (Environmental, Social, Governance).

Il corso include video lezioni, letture e interventi di ospiti esperti. È presentato in un formato accessibile e semplificato, adatto a un pubblico generalista, incluse scuole superiori e neo-ingressi all'università. Disponibile in italiano e inglese con sottotitoli, è accompagnato da materiali in entrambe le lingue.

Finanziamento, sviluppo ed evoluzione delle infrastrutture


Questo corso è rivolto a tutti coloro che hanno maturato una conoscenza solida di Tableau. Dopo aver imparato a analizzare dati e costruire visualizzazioni è arrivato il momento di approfondire la conoscenza della Business Intelligence (BI) e andare oltre Tableau.
La week 1 è dedicata alle Dashboard e alle Story. Una volta create le visualizzazioni di dati, imparerai come combinarle in modo interattivo all’interno di questi due ambienti.
La week 2 si occuperà della rappresentazione dell’informazione non limitata ai soli aspetti puramente grafici ma a tutte le scelte che un analista deve fare per comunicare in modo efficace i propri risultati. Per questo il modulo mescola teoria e pratica dei principi della data visualization, fondamentali per la comunicazione dei dati in ambito BI.
Nella week 3 imparerai a costruire visualizzazioni avanzate su Tableau. Combinando creatività e una conoscenza approfondita dello strumento potrai costruire visualizzazioni originali ed efficaci.
La week 4  introduce Tableau Server e Tableau Online, estensioni che consentono di condividere le proprie analisi.
La week 5, infine, è indirizzata all’apprendimento di Tableau Prep, il prodotto della suite dedicato alla preparazione dei dati che permette agli utenti di disegnare una data source ottimizzata sulla base delle proprie necessità analitiche.

Business Intelligence con la Product Suite di Tableau


Questo corso adotta un approccio pratico reale al flusso di lavoro ML attraverso un case study. Un team ML è chiamato a rispondere a numerosi requisiti aziendali e ad affrontare vari casi d'uso ML. Deve comprendere gli strumenti necessari per la gestione e la governance dei dati e considerare l'approccio migliore per la pre-elaborazione dei dati.

Al team vengono presentate tre opzioni per creare modelli ML per due casi d'uso. Il corso spiega perché il team utilizzerà AutoML, BigQuery ML o l'addestramento personalizzato per raggiungere i propri obiettivi.

Machine Learning in the Enterprise - Italiano


Machine Learning e Data Mining in R

Il corso Machine Learning e Data Mining in R è rivolto a chiunque voglia avere una pratica panoramica delle tecniche di apprendimento automatico, dalle più interpretabili - come l’analisi di regressione, delle componenti principali e dei gruppi - a quelle più flessibili come le reti neurali artificiali, sia shallow che deep - e le più ricorrenti problematiche di analisi e modellazione di dati e problemi reali - come collinearità, overfitting, regolarizzazione e knowledge transfer.
La modalità di erogazione del corso è di tipo learning by doing, mediante una continua implementazione in R dei concetti esposti. Le diverse unità ti verranno prima illustrate a voce, per permetterti di ricordare e capire, e poi rese disponibili sotto forma di reading, per permetterti di analizzarne criticamente il contenuto. Alla fine di ogni unità, verrai messo alla prova attraverso open Lab in ambiente di sviluppo RStudio, che ti permetteranno di applicare i metodi trattati nel corso ai tanti data set reali che ti saranno forniti. Ti verrà infine richiesto di valutare i tuoi progressi mediante graded quiz contenenti domande a risposta multipla. Non rimandare: Machine Learning e Data Mining in R sono ora a portata di mano!

Antonio Lepore
Biagio Palumbo
Carlo Sansone


Questo corso introduce i modelli di diffusione, una famiglia di modelli di machine learning che recentemente si sono dimostrati promettenti nello spazio di generazione delle immagini. I modelli di diffusione traggono ispirazione dalla fisica, in particolare dalla termodinamica. Negli ultimi anni, i modelli di diffusione sono diventati popolari sia nella ricerca che nella produzione. I modelli di diffusione sono alla base di molti modelli e strumenti di generazione di immagini all'avanguardia su Google Cloud. Questo corso ti introduce alla teoria alla base dei modelli di diffusione e a come addestrarli ed eseguirne il deployment su Vertex AI.

Introduction to Image Generation - Italiano


Gemini in Google Docs - Italiano

Gemini per Google Workspace è un componente aggiuntivo che fornisce agli utenti accesso a funzionalità di AI generativa. Questo corso approfondisce le funzionalità di Gemini in Documenti Google utilizzando lezioni video, attività ed esempi pratici. Imparerai a utilizzare Gemini per generare contenuti scritti in base a dei prompt. Inoltre, esplorerai l'utilizzo di Gemini per modificare il testo che hai già scritto, aiutandoti a migliorare la tua produttività complessiva. Alla fine del corso avrai acquisito le conoscenze e le competenze necessarie per utilizzare con sicurezza Gemini in Documenti Google per migliorare la tua scrittura.


Gemini in Google Slides - Italiano

Gemini per Google Workspace è un componente aggiuntivo che fornisce ai clienti funzionalità di AI generativa in Google Workspace. In questo mini corso imparerai le funzionalità principali di Gemini e come possono essere utilizzate per migliorare la produttività e l'efficienza in Presentazioni Google.


Questo corso ti insegna come creare un modello per le didascalie delle immagini utilizzando il deep learning. Scoprirai i diversi componenti di un modello per le didascalie delle immagini, come l'encoder e il decoder, e imparerai ad addestrare e valutare il tuo modello. Alla fine di questo corso, sarai in grado di creare modelli personali per le didascalie delle immagini e utilizzarli per generare didascalie per le immagini.

Create Image Captioning Models - Italiano


"Ti diamo il benvenuto nel corso Getting Started with Google Kubernetes Engine. Se ti interessa Kubernetes, un livello software che si trova tra le tue applicazioni e la tua infrastruttura hardware, allora sei nel posto giusto. Google Kubernetes Engine ti offre Kubernetes come servizio gestito su Google Cloud.

L'obiettivo di questo corso è illustrare le nozioni di base di Google Kubernetes Engine, o GKE, come viene comunemente chiamato, e come containerizzare le applicazioni e farle funzionare su Google Cloud. Il corso inizia con un'introduzione di base a Google Cloud, seguita da una panoramica dei container e di Kubernetes, dell'architettura di Kubernetes e delle operazioni di Kubernetes."

Getting Started with Google Kubernetes Engine - Italiano


Feature Engineering - Italiano

Questo corso illustra i vantaggi dell'utilizzo di Vertex AI Feature Store, come migliorare l'accuratezza dei modelli di ML e come trovare le colonne di dati che forniscono le caratteristiche più utili. Il corso include inoltre contenuti e lab sul feature engineering utilizzando BigQuery ML, Keras e TensorFlow.


Questo corso accelerato on demand illustra ai partecipanti l'infrastruttura e i servizi di piattaforma flessibili e completi di Google Cloud con particolare attenzione a Compute Engine. Attraverso una combinazione di videolezioni, demo e lab pratici, i partecipanti potranno esplorare gli elementi delle soluzioni, tra cui i componenti dell'infrastruttura come reti, sistemi e servizi per applicazioni, ed eseguirne il deployment. Questo corso tratta inoltre del deployment di soluzioni pratiche quali, ad esempio, chiavi di crittografia fornite dal cliente, gestione di sicurezza e accessi, quote e fatturazione, monitoraggio delle risorse.

Essential Google Cloud Infrastructure: Core Service italiano


The purpose of this course is to help those who are qualified develop confidence to attempt the exam, and to help those not yet qualified to develop their own plan for preparation.

Preparing Cloud Professional Cloud Architect Exam italiano


Questo corso accelerato on demand illustra ai partecipanti l'infrastruttura e i servizi di piattaforma flessibili e completi di Google Cloud con particolare attenzione a Compute Engine. Attraverso una combinazione di videolezioni, demo e lab pratici, i partecipanti potranno esplorare gli elementi delle soluzioni, tra cui i componenti dell'infrastruttura come reti, macchine virtuali e servizi per applicazioni, ed eseguirne il deployment. Imparerai a utilizzare Google Cloud mediante la console e Cloud Shell. Scoprirai inoltre il ruolo del Cloud Architect, gli approcci alla progettazione dell'infrastruttura e la configurazione del networking virtuale con VPC (Virtual Private Cloud), progetti, reti, subnet, indirizzi IP, route e regole firewall.

2 settimane di studio, 3-5 ore/settimana

Essential Google Cloud Infrastructure: Foundation - Italiano


Questo corso illustra Generative AI Studio, un prodotto su Vertex AI che ti aiuta a prototipare e personalizzare i modelli di AI generativa in modo da poterne utilizzare le capacità nelle tue applicazioni. In questo corso imparerai cos'è Generative AI Studio, le sue funzionalità e opzioni e come utilizzarlo, esaminando le demo del prodotto. Alla fine, troverai un laboratorio pratico per mettere in pratica ciò che hai imparato e un quiz per testare le tue conoscenze.

Introduction to Generative AI Studio - Italiano


Ti diamo il benvenuto al corso Persone, tecnologia e futuro della mobilità. Questo corso fornisce un'introduzione non specialistica ad alcune delle principali innovazioni tecnologiche nello spazio della mobilità attualmente oggetto di studio e richiede agli studenti di applicare una varietà di concetti delle scienze sociali per comprendere i probabili impatti sociali di queste tecnologie. Il corso è adatto a studenti di ogni ambito di studi e non richiede una formazione preliminare in ingegneria o scienze sociali.

Il contenuto presentato in questo corso si basa su una serie di interviste e conferenze ed è stato creato attraverso una partnership con Siemens. Il corso include anche un'esperienza video interattiva a 360° che consente agli studenti di scoprire i componenti chiave di un veicolo autonomo, di guidarlo e di conoscere la nuova tecnologia di rilevamento che potremmo vedere nelle città intelligenti di oggi e domani.

Questo corso sfida gli studenti a immaginare una mobilità del futuro che sia più sicura, più pulita e più equa. Esamineremo i recenti progressi tecnologici, nonché le implicazioni socio-economiche e politiche, di due importanti spazi tecnologici in evoluzione legati alla mobilità: l'elettrificazione e l'automazione.


Il corso affronta le tematiche dell'elettromagnetismo e dell'ottica, fornendo le nozioni che risultano utili per affrontare insegnamenti di fisica di base, a partire dalla comprensione del metodo sperimentale per poi mostrare le grandezze fondamentali e loro relazioni in tali ambiti, imparando a identificarle, distinguerle e utilizzarle.

Gli argomenti affrontati relativamente all'elettromagnetismo sono, divisi per settimane:
· campo elettrico, conduttori, condensatori e materiali dielettrici
· corrente elettrica, campo magnetico e materiali magnetici

mentre per l'ottica si ha
· onde elettromagnetiche, ottica geometrica e ottica ondulatoria

con un'ultima settimana di accenno alla fisica moderna.

All’interno di ogni settimana si trovano video relativi a lezioni, esercizi ed approfondimenti su alcuni argomenti, nonché quiz a risposta chiusa allo scopo di fornire allo studente l’opportunità di un primo feedback di auto-valutazione. Ognuna delle tematiche si chiude poi con un quiz riepilogativo per verificare l’acquisizione delle nozioni presentate.

Introduzione alla fisica sperimentale: elettromagnetismo, ottica, fisica moderna