This course opens with an exploration of the social context and aims of literacy teaching and learning. It goes on to describe a range of historical and contemporary approaches to literacy pedagogy, including didactic, authentic, functional, and critical approaches. The course takes has a 'Multiliteracies' perspective, which aims to expand the definition of literacy to encompass today's multimodal communications, and the diversity of literacies across different social and culltural contexts. A Multiliteracies approach also suggests a broad range of activity types—experiential, conceptual, analytical and critical.

--------------------------------
Recommended Background
--------------------------------

This course is designed for people interested in literacy teaching and learning, including people who may wish to join education as a profession, practicing teachers interested in exploring future directions for a vocation that is currently undergoing transformation, and community and workplace leaders who regard their mission to be in part "educative."

--------------------------------
Related Resources
--------------------------------

Online resources are available here:
https://newlearningonline.com

Book:
https://www.amazon.com/Literacies-Mary-Kalantzis/dp/1107578698/ref=sr_1_1?qid=1661288799&refinements=p_27%3ABill+Cope&s=books&sr=1-1&text=Bill+Cope

--------------------------------
Join our Online Communities!
--------------------------------

CGScholar (Create an account and join the New Learning community)
https://cgscholar.com/community/community_profiles/new-learning/community_updates

Facebook
https://www.facebook.com/newlearningonline

Twitter
https://twitter.com/neolearning

--------------------------------
Take this Course for Credit at the University of Illinois
--------------------------------

This course has the same content and anticipates the same level of contribution by students in the Assessment for Learning course offered to graduate certificate, masters, and doctoral level students in the Learning Design and Leadership Program in the College of Education at the University of Illinois.

Of course, in the nature of MOOCs many people will just want to view the videos and casually join some of the discussions. Some people say that these limited kinds of participation offer evidence that MOOCs suffer from low retention rates. Far from it – we say that any level of engagement is good engagement.

On the other hand, if you would like to take this course for credit at the University of Illinois, you will find more information about our program here:
https://ldlprogram.web.illinois.edu/overview/

And you can apply here:
https://education.illinois.edu/epol/programs-degrees/ldl

--------------------------------
The Learning Design and Leadership Series of MOOCs
--------------------------------

This course is one of a series of eight MOOCs created by Bill Cope and Mary Kalantzis for the Learning Design and Leadership program at the University of Illinois. If you find this MOOC helpful, please join us in others!

e-Learning Ecologies: Innovative Approaches to Teaching and Learning for the Digital Age
https://www.coursera.org/learn/elearning

New Learning: Principles and Patterns of Pedagogy
https://www.coursera.org/learn/newlearning

Assessment for Learning
https://www.coursera.org/learn/assessmentforlearning

Learning, Knowledge, and Human Development
https://www.coursera.org/learn/learning-knowledge-human-development

Ubiquitous Learning and Instructional Technologies
https://www.coursera.org/learn/ubiquitouslearning

Negotiating Learner Differences: Towards Productive Diversity in Learning
https://www.coursera.org/learn/learnerdifferences

Literacy Teaching and Learning: Aims, Approaches and Pedagogies
https://www.coursera.org/learn/literacy-teaching-learning

Multimodal Literacies: Communication and Learning in the Era of Digital Media
https://www.coursera.org/learn/multimodal-literacies


Formal Financial Accounting

This course builds upon what you learned in Financial Accounting: Foundations and Financial Accounting: Advanced Topics and introduces you to formal foundations of financial accounting. The main purpose of the course is to familiarize you with technical terms in financial accounting, such as debit, credit and T-account. While knowledge on technical aspects of financial accounting is not necessary to understand and interpret financial statements, this knowledge is critical to be able to understand advanced topics in accounting. Formal Financial Accounting is a prerequisite course for the University of Illinois' iMSA program and the terminology we will cover will be used throughout the courses in iMSA program.

The University of Illinois at Urbana-Champaign, consistently ranked as one of the nation's top three accounting programs, now offers a master’s in accounting at a very affordable tuition rate and is completely online. The iMSA is a full Master of Accountancy program and students graduate with a highly recognized master degree. Try an open course or two, then apply for admission into the credit-bearing version, as you may be eligible to take credit-bearing courses during the application process. If you are missing any prerequisites for the full degree, you can complete Coursera courses to demonstrate readiness and strengthen your application for the iMSA. For more information on this exciting online master's in accounting program, refer to this link: https://www.coursera.org/university-programs/imsa


Dieser Kurs bietet einen analytischen Rahmen zur strukturierten Beurteilung von Schlüsselproblemen und gibt Ihnen Tools an die Hand, mit denen Sie die Unsicherheiten besser in den Griff bekommen, die in Geschäftsprozessen auftreten und diese komplizieren. Sie werden insbesondere in die Statistik eingeführt und in die Art und Weise, wie man Daten zusammenfasst. Sie erfahren etwas über Häufigkeitskonzepte, Normalverteilung, statistische Untersuchungen, Stichproben und Konfidenzintervalle.

Sie werden zwar in einige Gebiete der didaktischen Wissenschaft eingeführt, der Schwerpunkt liegt jedoch auf der Anwendung von Methoden. Dies geschieht mittels Excel und Datensätzen aus vielen verschiedenen Fachrichtungen und ermöglicht Ihnen, etwas über die Anwendung von Statistik in sehr unterschiedlichen Situationen zu lernen. Schwerpunkte des Kurses sind nicht allein die Erklärung dieser Konzepte, sondern ebenfalls das Verständnis der Bedeutung erzielter Resultate.

Wenn Sie diesen Kurs erfolgreich absolviert haben, werden Sie in der Lage sein:

•	umfangreiche Datensätze in grafischer, tabellarischer und numerischer Form zusammenzufassen.
•	zu verstehen, welche Bedeutung ordnungsgemäße Stichprobenverfahren haben und warum Sie sich auf Stichprobendaten verlassen können.
•	zu verstehen, warum Normalverteilung in so vielen Situationen angewandt werden kann.
•	Stichprobeninformationen zu verwenden, um mit einem gewissen Grad an Sicherheit im Hinblick auf die Genauigkeit der Schätzungen Rückschlüsse auf die Population zu ziehen.
•	Excel für statistische Analysen einzusetzen.

Dieser Kurs ist Teil des von der University of Illinois angebotenen iMBA, einem flexiblen, voll anerkannten Online-MBA zu einem unglaublich günstigen Preis. Ausführliche Informationen erhalten Sie auf der Seite „Resources“ in diesem Kurs sowie unter onlinemba.illinois.edu.

Untersuchen und Erstellen von Daten für Unternehmen

Fataneh Taghaboni-Dutta, Ph.D., PMP, CSM, CSPO


The Theory of the Firm

In this course, we will begin covering the theory of the firm. Economists call this "The Economics of the Lemonade Stand." And that title makes perfect sense, since the concepts we cover can be used by anyone, from someone owning a lemonade stand, to a car manufacturing company, to a hair salon, to a burrito stand, etc. We will continue our discussion of the firm by focusing on those firms working in a perfectly competitive (or competitive) environment.

Also, why is it that when you fly, the person sitting next to you in the plane probably paid a different price for the ticket than what you paid for it? And why does Starbucks charge so much for its coffee even though you can buy coffee at Dunkin’ Donuts for almost half of that price? We will finish our discussion of the firm by focusing on cases that should be more familiar to you than the perfect competition examples we have been using.

Customizable based on your level of interest


Wetland Delineation Fundamentals

In this course, learners will get familiarized with the major components of wetland delineation, including the steps involved and the resources available for remote identification. They will explore the field indicators for hydrology, hydric soils, and vegetation, essential for accurate wetland delineation. The course will cover the best practices for writing wetland delineation reports and the differences between wetland delineation and jurisdictional determination. By the end of the course, learners will have a comprehensive understanding of the processes and indicators used in wetland delineation, enabling them to conduct accurate and effective assessments.

This course is part of the College of ACES suite of online programs, including the graduate-level certificate, "Wetland Science and Conservation" that can be stacked toward an online master's degree in Natural Resources and Environmental Sciences. To learn more about online programs from the College of ACES and explore ways to apply your Coursera work toward a degree program at the University of Illinois, visit ACES Online at acesonline.illinois.edu.


This course, Instructional Design Foundations, introduces learners to the conceptual and theoretical foundations of instructional design as well as the analysis aspect of instructional systems design in order to create an innovative instructional solution to performance problems in organizations. This particular course also introduces learners to concepts covered in the Instructional Design MasterTrack Certificate.
Upon successful completion of this course, you will be able to:
●Describe the major concepts of instructional systems design
●Describe the major learning and instructional theories
●Describe the process of instructional design and instructional design models
●Describe various analysis activities for instructional design

Instructional Design Foundations and Applications


Discover how fermentation is transforming industries and driving a sustainable future. This course begins by exploring the evolution of fermentation—from ancient food traditions to modern precision techniques—and why it matters today. You’ll dive into the science behind fermentation, including microbes, synthetic biology, and feedstocks, before examining the innovative products shaping global markets in food, beauty, and industrial materials. Finally, you’ll tackle one of the biggest challenges: scaling fermentation from lab to commercial production.

This course is part of the College of ACES suite of online programs and is supported by the Integrated Bioprocessing Research Lab (IBRL), a pilot plant facility focused on bioprocessing technologies located at the University of Illinois in Urbana-Champaign. The IBRL was built with the needs of industry projects and customers in mind, supporting over 1,000 scale-up projects for our clients since opening in 2018.

 Learn more about online programs from the College of ACES:  https://acesonline.illinois.edu
 Learn more about IBRL: https://ibrl.aces.illinois.edu

New Fermentation Markets and How They Scale


Assessment for Learning

For several decades now, assessment has become an increasingly pressing educational priority. Teacher and school accountability systems have come to be based on analysis of large-scale, standardized summative assessments. As a consequence, assessment now dominates most conversations about reform, particularly as a measure of teacher and school accountability for learner performance. Behind the often heated and at times ideologically gridlocked debate is a genuine challenge to address gaps in achievement between different demographically identifiable groups of students. There is an urgent need to lift whole communities and cohorts of students out of cycles of underachievement. For better or for worse, testing and public reporting of achievement is seen to be one of the few tools capable of clearly informing public policy makers and communities alike about how their resources are being used to expand the life opportunities for their children. This course is an overview of current debates about testing, and analyses the strengths and weaknesses of a variety of approaches to assessment. The course also focuses on the use of assessment technologies in learning. It will explore recent advances in computer adaptive and diagnostic testing, the use of natural language processing technologies in assessments, and embedded formative assessments in digital and online curricula. Other topics include the use of data mining, learning analytics and artificial intelligence in learning management systems and educational technology platforms. Participants will be required to consider issues of data access, privacy and the challenges raised by ‘big data’ including data persistency and student profiling.

--------------------------------
Recommended Background
--------------------------------

This course is designed for people interested in the future of education and the "learning society," including people who may wish to join education as a profession, practicing teachers interested in exploring future directions for a vocation that is currently undergoing transformation, and community and workplace leaders who regard their mission to be in part "educative."

--------------------------------
Related Resources
--------------------------------

Online resources are available here:
https://newlearningonline.com

--------------------------------
Join our Online Communities!
--------------------------------

CGScholar (Create an account and join the New Learning community)
https://cgscholar.com/community/community_profiles/new-learning/community_updates

Facebook
https://www.facebook.com/newlearningonline

Twitter
https://twitter.com/neolearning

--------------------------------
Take this Course for Credit at the University of Illinois
--------------------------------

This course has the same content and anticipates the same level of contribution by students in the Assessment for Learning course offered to graduate certificate, masters, and doctoral level students in the Learning Design and Leadership Program in the College of Education at the University of Illinois.

Of course, in the nature of MOOCs many people will just want to view the videos and casually join some of the discussions. Some people say that these limited kinds of participation offer evidence that MOOCs suffer from low retention rates. Far from it – we say that any level of engagement is good engagement.

On the other hand, if you would like to take this course for credit at the University of Illinois, you will find more information about our program here:
https://ldlprogram.web.illinois.edu/overview/

And you can apply here:
https://education.illinois.edu/epol/programs-degrees/ldl

--------------------------------
The Learning Design and Leadership Series of MOOCs
--------------------------------

This course is one of a series of eight MOOCs created by Bill Cope and Mary Kalantzis for the Learning Design and Leadership program at the University of Illinois. If you find this MOOC helpful, please join us in others!

e-Learning Ecologies: Innovative Approaches to Teaching and Learning for the Digital Age
https://www.coursera.org/learn/elearning

New Learning: Principles and Patterns of Pedagogy
https://www.coursera.org/learn/newlearning

Assessment for Learning
https://www.coursera.org/learn/assessmentforlearning

Learning, Knowledge, and Human Development
https://www.coursera.org/learn/learning-knowledge-human-development

Ubiquitous Learning and Instructional Technologies
https://www.coursera.org/learn/ubiquitouslearning

Negotiating Learner Differences: Towards Productive Diversity in Learning
https://www.coursera.org/learn/learnerdifferences

Literacy Teaching and Learning: Aims, Approaches and Pedagogies
https://www.coursera.org/learn/literacy-teaching-learning

Multimodal Literacies: Communication and Learning in the Era of Digital Media
https://www.coursera.org/learn/multimodal-literacies


Business Analytics Executive Overview

Businesses run on data, and data offers little value without analytics. The ability to process data to make predictions about the behavior of individuals or markets, to diagnose systems or situations, or to prescribe actions for people or processes drives business today. Increasingly many businesses are striving to become “data-driven”, proactively relying more on cold hard information and sophisticated algorithms than upon the gut instinct or slow reactions of humans.

This course will focus on understanding key analytics concepts and the breadth of analytic possibilities. Together, the class will explore dozens of real-world analytics problems and solutions across most major industries and business functions. The course will also touch on analytic technologies, architectures, and roles from business intelligence to data science, and from data warehouses to data lakes. And the course will wrap up with a discussion of analytics trends and futures.


This course is the first in the Customer Insights and New Product Development (CIPD) specialization. It will introduce learners to the tools and process of gathering customer insights for identifying and developing new product opportunities. Through an integrated set of five modules and hands-on project experiences, learners will acquire the knowledge and skills to turn their ideas gained from understanding customer needs into innovative new products.

Customer Insights: New Product Development Orientation


Agriculture as an Asset Class

Modern agriculture has evolved into an accessible and lucrative asset class for a wide range of investors. Gain insights into the financial performance of this capital-intensive industry, anchored in valuable real estate assets and agricultural investments. Learners who enroll in this course will examine the scale, structure, and capital frameworks of the agricultural sector, explore the innovative channels emerging for investment, and explore the dynamics of agricultural financing.

This course is part of the College of ACES suite of online programs, including the 4-week graduate-level course that can be stacked toward the Agribusiness and Sustainable Food Production Economics graduate certificate and a graduate degree. To learn more about online programs from the College of ACES and explore ways to apply your Coursera work toward a degree program at the University of Illinois, visit ACES Online at acesonline.illinois.edu.


Marketing no mundo digital

Este curso analisa como ferramentas digitais, por exemplo, a Internet, os smartphones e a impressão 3D, estão revolucionando o mundo do marketing ao mudar as funções e práticas das empresas e dos consumidores. O Marketing no mundo digital é um dos cursos mais procurados da Coursera com mais de 250 mil alunos e ele foi classificado pela Class Central como um dos 50 melhores cursos on-line abertos e massivos (MOOCs, na sigla em inglês) de todos os tempos (https://www.class-central.com/report/top-moocs/).
Este curso foi lançado inicialmente em 2015 e atualizado em abril de 2020.

Este curso faz parte do iMBA oferecido pela Universidade de Illinois, que é um MBA on-line, flexível e credenciado, a um preço incrivelmente competitivo. Para obter mais informações, consulte a página Recurso neste curso e o site onlinemba.illinois.edu.

4 semanas de estudo, de 6 a 8 horas/semana


This course offers a comprehensive exploration of dairy cow health and nutrition, focusing on physiological changes around calving and their impact on nutrient needs. Students will learn about production diseases, major metabolic changes, and key biomarkers of health and disease. The course addresses common health problems in dairy cows and the role of biomarkers in diagnosis and management. A systems approach to nutritional management is emphasized, exploring how genetics, cellular networks, and dietary components influence cow health and productivity. Expert instructors will guide learners through practical applications to optimize dairy cow health and production

This course is part of the College of ACES suite of online programs, including the graduate certificate, "Dairy Nutrition for Udder Success" that can be stacked toward an advanced degree in the College of ACES. To learn more about online programs from the College of ACES and explore ways to apply your Coursera work toward a degree program at the University of Illinois, visit ACES Online @ aces.illinois.edu/online.

Dairy Nutrition & Health: Analyzing Cow Wellness


This course is an introduction to 3D scientific data visualization, with an emphasis on science communication and cinematic design for appealing to broad audiences. You will develop visualization literacy, through being able to interpret/analyze (read) visualizations and create (write) your own visualizations.

By the end of this course, you will:
-Develop visualization literacy.
-Learn the practicality of working with spatial data.
-Understand what makes a scientific visualization meaningful.
-Learn how to create educational visualizations that maintain scientific accuracy.
-Understand what makes a scientific visualization cinematic.
-Learn how to create visualizations that appeal to broad audiences.
-Learn how to work with image-making software. (for those completing the Honors track)

3D Data Visualization for Science Communication


This course sets out to provide an understanding of theories of learning and development and how these theories relate to educational technology. It has two components. The first is theoretical, in which we attempt to develop an overall frame of reference, locating approaches to the psychology of learning in terms of large paradigm shifts, from ‘behaviorism’ to ‘brain developmentalism’ to ‘social cognitivism’. The second component is practical, in which we will use these theoretical concepts to ‘parse’ a technology-mediated learning environment for its underlying presuppositions.

--------------------------------
Recommended Background
--------------------------------

This course is designed for people interested in the future of education and the "learning society," including people who may wish to join education as a profession, practicing teachers interested in exploring future directions for a vocation that is currently undergoing transformation, and community and workplace leaders who regard their mission to be in part "educative."

--------------------------------
Related Resources
--------------------------------

Online resources are available here:
https://newlearningonline.com

--------------------------------
Join our Online Communities!
--------------------------------

CGScholar (Create an account and join the New Learning community)
https://cgscholar.com/community/community_profiles/new-learning/community_updates

Facebook
https://www.facebook.com/newlearningonline

Twitter
https://twitter.com/neolearning

--------------------------------
Take this Course for Credit at the University of Illinois
--------------------------------

This course has the same content and anticipates the same level of contribution by students in the Assessment for Learning course offered to graduate certificate, masters, and doctoral level students in the Learning Design and Leadership Program in the College of Education at the University of Illinois.

Of course, in the nature of MOOCs many people will just want to view the videos and casually join some of the discussions. Some people say that these limited kinds of participation offer evidence that MOOCs suffer from low retention rates. Far from it – we say that any level of engagement is good engagement.

On the other hand, if you would like to take this course for credit at the University of Illinois, you will find more information about our program here:
https://ldlprogram.web.illinois.edu/overview/

And you can apply here:
https://education.illinois.edu/epol/programs-degrees/ldl

--------------------------------
The Learning Design and Leadership Series of MOOCs
--------------------------------

This course is one of a series of eight MOOCs created by Bill Cope and Mary Kalantzis for the Learning Design and Leadership program at the University of Illinois. If you find this MOOC helpful, please join us in others!

e-Learning Ecologies: Innovative Approaches to Teaching and Learning for the Digital Age
https://www.coursera.org/learn/elearning

New Learning: Principles and Patterns of Pedagogy
https://www.coursera.org/learn/newlearning

Assessment for Learning
https://www.coursera.org/learn/assessmentforlearning

Learning, Knowledge, and Human Development
https://www.coursera.org/learn/learning-knowledge-human-development

Ubiquitous Learning and Instructional Technologies
https://www.coursera.org/learn/ubiquitouslearning

Negotiating Learner Differences: Towards Productive Diversity in Learning
https://www.coursera.org/learn/learnerdifferences

Literacy Teaching and Learning: Aims, Approaches and Pedagogies
https://www.coursera.org/learn/literacy-teaching-learning

Multimodal Literacies: Communication and Learning in the Era of Digital Media
https://www.coursera.org/learn/multimodal-literacies


This course introduces several tools for processing business data to obtain actionable insight. The most important tool is the mind of the data analyst. Accordingly, in this course, you will explore what it means to have an analytic mindset. You will also practice identifying business problems that can be answered using data analytics. You will then be introduced to various software platforms to extract, transform, and load (ETL) data into tools for conducting exploratory data analytics (EDA). Specifically, you will practice using Python to conduct the ETL and EDA processes.

The learning outcomes for this course include:
1.	Development of an analytic mindset for approaching business problems.
2.	The ability to appraise the value of datasets for addressing business problems using summary statistics and data visualizations.
3.	The ability to competently operate business analytic software applications for exploratory data analysis.

Tools for Exploratory Data Analysis in Business


Global Impact: Multiculturalism

This course embarks on the journey of understanding multicultural marketing's essentials. It elaborates on how culture influences consumer behavior and decision-making, and it explores the roles of multicultural consumer segments, generational and regional subcultures. The course imparts knowledge of various advertising strategies tailored for multicultural markets and discusses concepts like bilingual use, frame-switching, and communication channels' significance.

Upon successful completion of this course, you will be able to:
- understand how culture influences consumer behavior and decision-making processes,
- identify and describe the roles of multicultural consumer segments, generational, and regional subcultures in marketing,
- analyze and apply various advertising strategies tailored for multicultural markets,
- recognize the effects of bilingual use and frame-switching in advertising communication,
- appreciate the importance of different communication channels in multicultural marketing campaigns,
 -evaluate real-world multicultural marketing campaigns, identifying their strengths and areas for improvement,
- develop skills to create culturally responsive marketing strategies that acknowledge and appeal to the cultural backgrounds of diverse consumer segments, and
- enhance your multicultural marketing acumen, preparing you for leadership roles in culturally diverse business environments.


Managing Professional Work Teams

We often think that managing people looks like a charismatic and courageous person effective enough to be in front pointing out to everyone the direction the group should take, while others follow behind. However, in today’s world (where the difference between supervisors and employees is smaller than ever), leaders are just as often teammates and collaborators as they are supervisors and managers who can hire and fire their team at will. This course is an introduction for how managers can construct and supervise individuals who work as a team to get their work done quickly and effectively – where all individuals add unique value and skill.

Taught by an internationally recognized expert in leadership and team development, this course is helpful to anyone interested in the basics of supervising other humans in work and community settings. If you already consider yourself more advanced, this short course might help to remind you of basic strategies and concepts you may have gotten away from. Each short video and reading is designed to be practical, clear, and backed by the latest research in management and leadership development.


A “one size fits all” approach to nutrition may not work for everyone. We each have unique variations in our genome, epigenome and microbiome, which interact with our external environment to affect how our bodies respond to dietary intake. Learners will exam the basic principles of nutrition, explore the foundational aspects of personalized nutrition, and analyze the research about the roles of genetics and microbiomes in our personalized nutrition journey.

This course is part of the College of ACES suite of online programs, including the graduate-level certificate, "Food Regulations, Nutrition Policy, and Personalized Nutrition" that can be stacked toward an online master's degree. To learn more about online programs from the College of ACES and explore ways to apply your Coursera work toward a degree program at the University of Illinois, visit ACES Online at acesonline.illinois.edu.

Putting the Personal in Personalized Nutrition


RiskWise: Insurance and Your Financial Future introduces learners to the fundamentals of risk management and insurance as essential tools for financial planning. Whether you're exploring a career in insurance or seeking to strengthen your personal financial strategy, this course offers practical insights into risk types, human capital, insurance operations, and the roles of professionals in the field.

Through real-world examples, interactive activities, and expert interviews, you’ll learn how to evaluate personal risks, understand insurance products, and apply risk management strategies to build financial resilience. Designed for a broad audience—including aspiring and current insurance professionals—this course empowers you to make informed decisions and better serve clients or your own household.

This course is part of the College of ACES suite of online programs. To learn more about online programs from the College of ACES and explore ways to apply your Coursera work toward a degree program at the University of Illinois, visit ACES Online. @ aces.illinois.edu/online


Global Impact: Cultural Psychology

Globalization has brought dramatic changes to the marketplace. A proliferation of global brands brings diverse cultures to a consumer population that is also culturally diverse. This course enables students to understand how globalization changes consumers at a psychological level and provides tools for infusing  brands with cultural meaning that can resonate with global consumers. The focus is on understanding that culture exists in the mind as well as in the environment, and that globalization creates multi-cultural spaces in contemporary societies. Consumers can use the cultural meaning of a brand to build their identities or reject the brand’s cultural meaning.

The course will help students identify when assimilation vs. exclusionary reactions are more likely to occur and to devise strategies for imbuing brands with cultural meanings that can elevate them to the status of cultural icons.

You will be able to:

• Understand how globalization impacts the psychological responses of consumers in global markets
• Explain  what culture is and how it manifests itself in business environments
• Understand how brands acquire cultural meanings and predict consumers’ responses to the cultural meanings in brands
• Identify strategies to win-over multi-cultural consumers in globalized markets
• Practice the fundamentals of  how to build an iconic brand

This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.


Le marketing dans un monde numérique

Ce cours aborde la manière dont les nouveaux outils numériques (Internet, smartphones, impression 3D) révolutionnent le monde du marketing en modifiant les rôles et les habitudes des entreprises comme des clients. Avec plus de 500 000 étudiants, le cours « Le marketing dans un monde numérique » est l’un des plus populaires de Coursera, et Class Central le considère comme l’un des 50 meilleurs MOOC de tous les temps (https://www.class-central.com/report/top-moocs/).

Vous pourrez :
•	Comprendre comment les outils numériques modifient la nature du marketing
•	Expliquer comment les outils numériques permettent aux clients de jouer un rôle plus actif dans le développement, la promotion, le placement et le prix des produits
•	Acquérir un nouvel ensemble de concepts, d’outils et de récits pour améliorer vos activités de marketing digital

Ce cours fait partie de la suite de programmes en ligne du Gies College of Business, notamment l’iMBA et l’iMSM. Pour en savoir plus sur l’inscription à ces programmes et découvrir comment utiliser votre travail Coursera en cas d’admission dans un programme diplômant, consultez le site https://degrees.giesbusiness.illinois.edu/idegrees/.


Dive into the transformative world of blockchain with our course, designed to navigate the complexities of digital currencies, smart contracts, and decentralized applications. Whether you're intrigued by Bitcoin, Ethereum, or the broader implications of blockchain for industries and governance, this course offers deep insights and practical knowledge to leverage blockchain technology for innovation and problem-solving. Perfect for both beginners and seasoned enthusiasts, it's your gateway to mastering the blockchain ecosystem and its burgeoning impact on the digital age.

Blockchains, Tokens, and The Decentralized Future


This course will highlight the potential of quantitative marketing research for assessing new product opportunities. In addition to focusing on the skills and practices for a successful New Product Development (NPD), the course will illustrate the multi-faceted challenges of NPD using authentic business situations. The first module will provide business practice foundations to help learners devise creative solutions to problems using a design-thinking framework. Learners will experience the idea creation process and then apply the role of surveys for evaluating consumer responses to an idea before introducing a product to market. The second module will explore the technique of conjoint analysis for quantifying the customer benefits, customer values, and the trade-off he or she is willing to make between the price of the product and desired features of the product or service. Concept testing identifies perceptions, wants, and needs of a product or service as the foundation of targeting and positioning a product in the marketplace. The third module will describe a multitude of tools for assessing technology readiness and defining the product features to target the key customer need requirements. Learners will hear an in-depth interview with one of the leading U.S. business executives on the management challenges of innovation. Learners will develop a survey (with appropriate data privacy agreements) and analyze the data for decisions about the pricing and positioning a new product into a focused market. The fourth module will illustrate the use of the tools to create a sales and pricing forecast for a new product. Three new product ideas representing three different types of market unknowns will be analyzed using market research tools. Upon completion of this course, the learner will have defined and redefined their product idea and created a credible sales forecast for use in an overall business case.

Customer Insights: Quantitative Techniques


This course, Machine Learning for Accounting with Python, introduces machine learning algorithms (models) and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses model evaluation and model optimization. This course provides an entry point for students to be able to apply proper machine learning models on business related datasets with Python to solve various problems.

Accounting Data Analytics with Python is a prerequisite for this course. This course is running on the same platform (Jupyter Notebook) as that of the prerequisite course. While Accounting Data Analytics with Python covers data understanding and data preparation in the data analytics process, this course covers the next two steps in the process, modeling and model evaluation. Upon completion of the two courses, students should be able to complete an entire data analytics process with Python.

Eight weeks of study, eight hours per week.


This course provides an analytical framework to help you evaluate key problems in a structured fashion and will equip you with tools to better manage the uncertainties that pervade and complicate business processes. Specifically, you   will learn how to summarize data and learn concepts of frequency, normal distribution, statistical studies, sampling, and confidence intervals.

While you will be introduced to some of the science of what is being taught, the focus will be on applying the methodologies. This will be accomplished through the use of Excel and data sets from different disciplines, allowing you to see the use of statistics in a range of settings. The course will focus not only on explaining these concepts, but also understanding and interpreting the results obtained.

You will be able to:

• Summarize large data sets in graphical, tabular, and numerical forms
• Understand the significance of proper sampling and why one can rely on sample information
• Understand why normal distribution can be used in a wide range of settings
• Use sample information to make inferences about the population with a certain level of confidence about the accuracy of the estimations
• Use Excel for statistical analysis

This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.

Exploring and Producing Data for Business Decision Making


Trabajo en equipo y creatividad

En este curso, mejorarás tu capacidad y tus oportunidades para trabajar de manera creativa dentro de cualquier organización, aprenderás a comprender la importancia y la función del trabajo en equipo dentro de la organización, y desarrollarás habilidades que te diferenciarán como participante influyente del equipo. Las habilidades comerciales profesionales relacionadas con el trabajo en equipo y la creatividad que obtendrás en este curso te ayudarán a tener éxito en tu trabajo en cualquier organización.

Gies College of Business, University of Illinois


Introduction to Programming with MATLAB

This course teaches computer programming to those with little to no previous experience. It uses the programming system and language called MATLAB to do so because it is easy to learn, versatile and very useful for engineers and other professionals. MATLAB is a special-purpose language that is an excellent choice for writing moderate-size programs that solve problems involving the manipulation of numbers. The design of the language makes it possible to write a powerful program in a few lines. The problems may be relatively complex, while the MATLAB programs that solve them are relatively simple: relative, that is, to the equivalent program written in a general-purpose language, such as C++ or Java. As a result, MATLAB is being used in a wide variety of domains from the natural sciences, through all disciplines of engineering, to finance, and beyond, and it is heavily used in industry. Hence, a solid background in MATLAB is an indispensable skill in today’s job market.

Nevertheless, this course is not a MATLAB tutorial. It is an introductory programming course that uses MATLAB to illustrate general concepts in computer science and programming. Students who successfully complete this course will become familiar with general concepts in computer science, gain an understanding of the general concepts of programming, and obtain a solid foundation in the use of MATLAB.

Students taking the course will get a MATLAB Online license free of charge for the duration of the course. The students are encouraged to consult the eBook that this course is based on. More information about these resources can be found on the Resources menu on the right.


AI Agent Skills for Leaders

AI is not just a tool. It is becoming your team.

The leaders who win in the next decade will not be the ones who “use AI occasionally.” They will be the ones who know how to deploy it—to turn a simple idea, question, or conversation into fully realized outputs: dashboards, reports, systems, analyses, and decisions that would normally require entire teams to produce.

This course teaches you how to do exactly that with AI Agent Skills that anyone can deploy in ChatGPT, Claude, and Gemini.

AI Agent Skills are a new way of working with AI. Instead of starting from scratch every time you ask for something, you create reusable “skills” that act like on-demand training manuals for your AI—teaching it how to think, how to structure work, and how to produce outputs the way you want them done.

But the real breakthrough is not just automation—it is transformation.

Most people use AI to generate text. Leaders use AI to generate artifacts.

Instead of getting an explanation, you get an interactive dashboard.
Instead of a summary, you get a decision framework.
Instead of a pile of files, you get a fully organized system packaged and ready to use.

You are not just getting answers—you are getting work done.

This course will teach you how to think like a CEO assigning work to a team: how to design AI Agent Skills that take the raw intelligence of a conversation and turn it into outputs that are structured, tailored, visually polished, and immediately actionable.

You will learn how to take something that would normally require hours—or days—of effort and compress it into a single interaction. How to turn a few lines of instruction into dashboards, PDFs, spreadsheets, file systems, and tools that live beyond the chat and create real-world value.

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

- Turn any conversation into an interactive HTML dashboard you can download and share
- Create AI-powered file organization systems that rename, categorize, and package messy data into structured archives
- Build reusable AI Agent Skills that perform complex workflows on demand
- Generate decision frameworks with scoring models, tradeoffs, and recommendations
- Produce executive-ready reports, PDFs, and slide decks automatically
- Design custom tools and systems (not just text) tailored to your work, team, or business
- Transform raw ideas into structured plans with timelines, dependencies, and execution steps
- Convert explanations into visualizations, simulations, and learning systems
- Capture your best workflows and turn them into repeatable, high-quality outputs every time
- Think like a leader who doesn’t just ask for answers—but deploys AI to produce outcomes

This is not a course about prompts.

This is a course about leverage.

Once you understand how to build and use AI Agent Skills, you stop interacting with AI like a chatbot—and start operating it like a team that can produce high-quality work on demand.

Almost every task you do today can be upgraded.

This course shows you how.


Master the Art of Building Intelligent Python Agents That Think, Reason, and Act

Unlock the full potential of Python for creating autonomous AI agents that solve complex problems without constant human direction. In this comprehensive course on AI Agents and Agentic AI with Python & Generative AI, you'll learn how to architect sophisticated agent systems that leverage Python's robust ecosystem and industry-standard capabilities.

This course takes you beyond the foundations covered in the AI Agents and Agentic AI with Python & Generative AI course to explore advanced patterns for building truly intelligent agents in Python. You'll delve into specialized techniques like self-prompting, expert personas, document-as-implementation, and multi-agent orchestration - all implemented with Python's powerful frameworks and libraries.

What You'll Learn:

- Self-Prompting Patterns in Python: Build agents that dynamically adopt different thinking modes to handle specialized tasks, transforming unstructured data into structured formats with clean Python implementations

- Python-Based Expert Persona Systems: Implement consultation frameworks where agents can invoke domain experts for specialized knowledge while maintaining clean architecture

- Document-as-Implementation: Use Python's powerful file handling to create systems where human-readable documents become executable business logic

- Multi-Agent Collaboration with Python: Design sophisticated memory sharing and coordination mechanisms between specialized Python agents

- Progress Tracking & Planning: Implement robust planning and reflection capabilities using Python's comprehensive tooling

- Python Agent Safety & Trust Systems: Build transaction management and safety mechanisms that leverage Python's exception handling and security features

By the end of this course, you'll be equipped to build complex, production-ready agent systems in Python that can reason across multiple domains, handle complex workflows, and safely interact with real-world systems.

Whether you're building productivity tools, automating complex business processes, or creating intelligent assistants, you'll have the Python-specific knowledge to implement agentic AI solutions that provide genuine business value.

This course will teach you these concepts using OpenAI's APIs, which require paid access, but the principles and techniques can be adapted to other LLMs.

AI Agents and Agentic AI Architecture in Python


Unlock the power of automation with ChatGPT + Zapier: From Email Inbox to Excel Spreadsheet! This hands-on course teaches you how to streamline workflows by extracting valuable information from your email inbox and effortlessly organizing it into spreadsheets. Whether you want to track expenses, log action items, collect customer reviews, or manage follow-ups, this course gives you the skills to automate tedious tasks and turn unstructured email content into structured data.

Imagine transforming your Gmail inbox—or any other email provider supported by Zapier—into a dynamic source of insights. Learn how to automate data extraction and integration with thousands of popular apps in Zapier, such as Salesforce, Office365, HubSpot, Notion, and more. With detailed, step-by-step guidance, you’ll create “Zaps” that connect email providers, ChatGPT, and various apps to build seamless, automated workflows. Each lesson builds your automation skills, from setting up your data destinations and labeling emails, to configuring Zapier actions and leveraging ChatGPT’s natural language processing capabilities to extract actionable information.

What You’ll Learn:

	•	Automate Your Data Collection: Build Zaps that automatically extract key information from labeled emails and store it in tools like Google Sheets.
	•	Customize Prompts for ChatGPT: Master the art of prompt engineering to extract structured data like dates, vendors, amounts, and categories from email bodies.
	•	Use Code by Zapier to Process Data: Add custom JavaScript to parse ChatGPT’s responses and format them for various app integrations.
	•	Expand and Tailor Your Automation: Clone and customize your Zap workflows to track different types of information, such as project tasks, customer feedback, or event dates.

Key Course Highlights:

	•	From Email to Apps in Minutes: Quickly set up Zaps that move data from your inbox into Google Sheets, freeing up time and reducing manual data entry.
	•	Hands-On Projects: Follow along with practical examples, like automating expense tracking, to learn real-world applications of ChatGPT and Zapier.
	•	Scalable Solutions: Discover how to adapt your workflows for various use cases by changing prompts, labels, or data formats.

Go Beyond the Course:

While this course teaches you how to integrate Gmail and Google Sheets, the skills you’ll learn can be applied to other email providers supported by Zapier and thousands of connected apps, such as Salesforce, Office365, HubSpot, Notion, and more. The techniques covered will empower you to extend your automations to a variety of tools and platforms—from CRM systems to project management apps—giving you the flexibility to target different data sources and destinations with your new automation expertise.

By the end of the course, you’ll be equipped to automate data extraction from emails, save time, and boost your productivity. Let ChatGPT and Zapier work together to transform your everyday tasks—taking you from email overload to organized data and seamless app integrations with the click of a button!


Generative AI for Legal Services Primer

This course covers what Generative AI is and its applications to a variety of tasks in the legal field. The course will cover ethics and privacy, basic prompt engineering strategies for legal use cases, and how to leverage Generative AI to augment your legal expertise. This is a rapidly advancing area and a primary goal of this course is to prepare everyone for the pace of change that is taking place and to develop a mindset of continuous curiosity that will enable lawyers to adapt along with the technology


This MOOC describes by example how to build cloud services via the use of object-oriented design techniques; Java programming language features; Java Servlets, the Java Spring Framework; and cloud computing platforms, such as Amazon Web Services.  Due to the importance of building secure and scalable mobile/cloud platforms, this MOOC will not only show you how to build cloud services, but how to do so securely, scalably, and efficiently. Security and scalability topics will be woven into discussions of cloud service creation so that students learn, from the start, how to create robust cloud services.

Building Cloud Services with the Java Spring Framework


Generative AI and Model Selection

Dive into the world of generative AI and learn how to select the right model for your needs in this practical course. You'll gain a solid understanding of how generative AI models work and compare deployment options like web APIs, hosted solutions, and local installations.

By the end of this course, you will be able to:
•	Describe the basic architecture of generative AI models
•	Compare different AI model deployment options
•	Evaluate AI models using benchmarks and custom assessments
•	Troubleshoot and improve model performance
•	Determine when to use in-context learning vs. retrieval augmented generation

Through hands-on exercises, you'll learn to evaluate models using industry benchmarks and create custom assessments for your specific use cases. You'll also master techniques to troubleshoot and enhance model performance.

What sets this course apart is its focus on real-world application - you'll leave equipped to make informed decisions about AI model selection and optimization for your projects. Whether you're new to AI or looking to deepen your knowledge, this course will empower you to leverage generative AI effectively.

One week of study, one week for hands-on project


Imagine designing databases that evolve with your business, anticipate future needs, and solve problems you haven't even encountered yet. This course teaches you to use AI as your intelligent design partner—creating database architectures neither human nor AI could achieve alone. You'll master AI-powered design techniques that transform traditional database development, leveraging generative AI for schema simulation, automated gap analysis, and AI-facilitated requirement discovery. Together with your AI collaborator, you'll craft schemas that reduce technical debt, minimize migrations, and maintain peak performance through AI-optimized design choices.

What You'll Learn:

•	Test queries against AI-simulated databases before writing any code
•	Identify design blind spots using AI-powered gap analysis techniques
•	Have AI interview you with intelligent questions to uncover critical data insights
•	Convert spreadsheets or photographs into AI-optimized database schemas
•	Use AI to simulate database performance under various usage scenarios
•	Create AI-enhanced design packages that document both implementation and reasoning

Skills That Will Transform Your Work:

•	Generate thousands of rows of AI-crafted realistic test data in seconds
•	Create AI-designed dashboards to validate your design's reporting capabilities
•	Design AI-optimized migration paths for evolving database needs
•	Build AI-documented databases that new team members can understand immediately
•	Explore multiple AI-generated design alternatives to find optimal solutions

This course is for anyone who designs or maintains databases—from beginners to seasoned architects. You'll learn practical AI collaboration techniques that dramatically enhance your ability to create systems that are adaptable, resilient, and perfectly aligned with business needs.

Join us to master the art of human-AI collaborative database design and create systems that truly stand the test of time.

Generative AI Database Design & Management with ChatGPT


Leading Innovation in Arts and Culture

Developed by David Owens at Vanderbilt University and customized for the cultural sector with National Arts Strategies, this course is designed to help arts and culture leaders create an environment where new ideas are constantly created, shared, evaluated and the best ones are successfully put to work.

One of the toughest challenges for any leader is getting traction for new ideas. Winning support can be a struggle. As a result, powerful new ideas often get stuck. This is especially true in the cultural sector. People involved in arts and culture often have little time and even less money for experimentation and risks. This course will help those in the performing arts, museums, zoos, libraries and other cultural organizations build environments where new management and program ideas flourish.

Leading Innovation in Arts & Culture will teach you how to make an "innovation strategy" a fundamental component of your organization's overall strategy. In this seminar you will learn to:

- Analyze constraints on innovation in your organization, foresee obstacles and opportunities, and develop a shared vision
- Develop a process to manage the demands of multiple stakeholders, shifting priorities and the uncertainty inherent in new initiatives
- Create a culture for innovation and risk-taking that generates new perspectives and challenges existing practice
- Create a strong customer focus within your organization that anticipates customer needs

National Arts Strategies worked with David Owens to customize this course for those working in the cultural sector. They based their work on David Owens’ Leading Strategic Innovation in Organizations course. This highly interactive 8-week course will engage you in a series of class discussions and exercises.

Vanderbilt University
National Arts Strategies


Unlock the full potential of generative AI and become a master of prompt engineering. Dive deeper into how you can use In-context Learning to build better and more reliable prompts. See how Retrieval Augmented Generation (RAG) works and what can go wrong that you can counteract with fact-checkable prompt formats. Overcome your struggles in getting the right output from generative AI models with template-based output formats to achieve precision in your interactions with AI models. Tap into powerful AI capabilities for tasks ranging from social media comment analysis to survey results interpretation and beyond. This course will empower you with the skills needed to build exceptional prompts, using simple techniques, such as preference-driven refinement, and become and expert in leveraging generative AI for productivity and creativity.

What You Will Learn:

In-Context Learning: Understand how to provide context within prompts to guide AI models towards more accurate and relevant outputs. Learn techniques to embed contextual information that enhances the model’s understanding and performance.

Retrieval Augmented Generation (RAG): Explore how to integrate retrieval systems with generative models to provide more precise and informed responses. This module covers the mechanisms to combine the strengths of both retrieval and generation.

Template Pattern and Examples: Master the art of crafting template-based prompts to achieve consistent and desired outputs. Learn how to tell generative AI to fit its output into your format and overcome struggles with getting exactly what you want.

Tapping Into AI Capabilities for Everyday Use: Delve into practical applications such as analyzing social media comments, interpreting survey results, and other everyday tasks where generative AI can make a significant impact. Gain hands-on experience with real-world examples.

Building Great Prompts: Discover simple methods for constructing effective prompts. Learn how preference-driven refinement can elevate your prompt engineering skills, ensuring that outputs meet your exact needs and preferences.

Advanced Prompt Engineering for Everyone


This course is intended for individuals who'd like to work with data from their organization  but don't know where to start. We'll combine generative AI and your insights to structure research questions, understand the variables in your dataset, and begin describing the data for the purpose of generating insights into better decisions.  After taking this course, learners will know how to identify the outcomes and predictors in a dataset and how to summarize different types of variables in a dataset using generative AI.

From Data to Decisions: Getting Started with AI


Agentic AI is a type of AI that combines Generative AI with tools and actions, allowing us to build "agents" to assist us with everyday tools like Gmail, Office365, Google Sheets, Salesforce, etc. These agents can perform tasks on our behalf, such as updating a spreadsheet or sending an email. There are classes that teach these Agentic AI concepts, but they are geared towards programmers. If you aren't a programmer, they won't teach you how to build agents to help with your daily tasks.

This class will teach you how to use ChatGPT and Zapier to build your own agents to help prioritize tasks, keep track of expenses, plan meals and shopping lists, etc. These won't be tools that require you to cut and paste the results back into an email; these will be tools that can directly create a draft email and put it into your email account or allow you to snap a picture of a receipt on the go and have it show up in a spreadsheet. These agents can automate and take action for you.

By the end of this class, not only will you understand state-of-the-art aspects of Agentic AI, but you will have built your own Travel Expense Agent. Your agent will be able to take a picture of a receipt or a description of an expense and catalog it into a Google Sheet. It will check your expense with another agent for completeness, ensure the expense isn't already in the spreadsheet, and even draft an email to your administrator with a simple reimbursement report.

This course will transform the way you work.

ChatGPT & Zapier: Agentic AI for Everyone


Forget everything you know about traditional artificial intelligence. Generative AI and Agentic AI aren’t just new tools—they’re a new form of cognitive labor. They don’t simply analyze information; they take action, execute multi-step workflows, and deliver outcomes that once required teams of experts. From diagnosing equipment failures with a single photo to autonomously building full-stack software applications in minutes, AI labor is redefining what organizations can achieve.

This course shows leaders how to harness it strategically—before their competitors do.

In Generative AI & AI Agent Organizational Strategy for Leaders, you’ll learn why AI is no longer an IT initiative, a technical experiment, or a siloed innovation project. It is now a strategic workforce capability—a new category of labor that every employee can deploy through conversation, creativity, and problem-solving. You’ll discover how AI agents unlock 100x–1000x productivity gains, why vendor-locked “AI add-ons” can cripple your innovation capacity, and how organizations must rethink procurement, capability development, and labor strategy to stay competitive.

You’ll see firsthand how simple inputs—a photo, a document, a spreadsheet, a menu, a policy—can instantly become powerful AI-driven systems that perform tasks previously impossible or cost-prohibitive. Leaders will explore how employees at every level can use AI to enhance decision-making, compress time, and scale expertise, not replace roles. The real competitive advantage comes from teaching your workforce to think in conversations, design AI workflows, and orchestrate these new digital laborers effectively.

By the end of this course, you won’t just understand what agentic AI is—you’ll know how to operationalize it. You’ll learn how to:
	•	Build an organizational AI labor strategy that attracts the “best and brightest” models and keeps you vendor-independent.
	•	Identify high-value starting points using simple but transformational use cases.
	•	Train your workforce to solve problems through conversational design rather than code.
	•	Foster innovation by enabling teams to experiment rapidly with documents, images, and real-world workflows.
	•	Differentiate meaningful strategic AI capability from hype, gimmicks, and tools that limit your future.

Whether you lead a large enterprise, a fast-growing team, or a mission-driven organization, this course will give you a powerful framework for navigating the AI revolution. You’ll learn how to scale AI labor across your workforce, unlock new forms of value, and build an organization that moves faster, thinks smarter, and out-innovates the competition.

The future belongs to leaders who understand AI not as technology—but as labor. This course will teach you how to lead in that future.


Your AI can write the perfect email, but can it actually send it? It can analyze your calendar, but can it schedule the meeting? The gap between AI's intelligence and its ability to take action has been the biggest barrier to true automation—until Model Context Protocol (MCP) broke it wide open.
MCP is the revolutionary protocol that gives AI agents actual agency—the power to discover, select, and use your business tools autonomously. When you tell an AI agent to "add this travel expense," MCP enables it to list your spreadsheet rows, identify what's missing, and add the expense directly—no human intervention required. It's the difference between an AI that tells you what to do and one that does it for you.

Think of MCP as the universal translator between AI intelligence and your computer systems. It allows AI agents to automatically discover available tools—from email senders to CRM updaters to database queries—and use them in intelligent sequences to solve complex problems. The AI enters a powerful loop: assess the task, select a tool, execute through MCP, evaluate results, and repeat until the job is done. You provide the goal; the AI handles the execution.

This course teaches anyone—regardless of technical background—how Model Context Protocol actually works. We skip the technical minutiae and focus on the concepts that matter: how MCP enables AI autonomy, how it uses tools, and why it's transformative. You'll learn to integrate MCP into the AI tools you already use, like ChatGPT and Claude, transforming them from smart assistants into autonomous agents that can check your calendar, update your spreadsheets, send your emails, and manage your workflows. This isn't about becoming a programmer; it's about understanding the technology well enough to design solutions, lead implementations, and strategize competitive advantages.

By the end of this course, you'll possess the knowledge to evaluate MCP solutions, identify automation opportunities, and lead your organization's transition to autonomous AI. You'll understand not just what MCP can do, but how to harness it strategically—turning AI from a productivity tool into a force multiplier.

Model Context Protocol for Leaders: Generative AI Agents


Case Studies in Personalized Medicine

Learn how advances in biomedicine hold the potential to revolutionize drug development, drug treatments, and disease prevention: where are we now, and what does the future hold? This course will present short primers in genetics and mechanisms underlying variability in drug responses. A series of case studies will be used to illustrate principles of how genetics are being brought to bear on refining diagnoses and on personalizing treatment in rare and common diseases. The ethical and operational issues around how to implement large scale genomic sequencing in clinical practice will be addressed.

After completing this course, learners will understand
1. The ways in which genetic variants can contribute to human disease susceptibility
2. How to choose among drug therapies based on genetic factors
3. That the functional consequences of the vast majority of genetic variants discovered by modern sequencing are unknown.

This course is targeted primarily at physicians 5+ years out of training. Other healthcare providers, medical/health sciences students, and members of the public may also be interested.

Course launches January 15, 2016.

* The information presented in “Case Studies in Personalized Medicine” is offered for educational and informational purposes only, and should not be construed as personal medical advice. If you have questions or concerns about a medical matter, please consult your doctor or other professional healthcare provider.


My son is going to grow up in a completely different world that is filled with generative AI (e.g., ChatGPT, Claude, LLama, etc.). I think this is a world of possibility, creativity, and deep thought that will enrich the way we think and solve problems. I want to make sure that my son is set up for success in this new world and understands how to use generative AI in a way that helps him learn, create, and solve problems.

Even though generative AI seems obvious to use, it isn't. Really learning to innovate and succeed with generative AI requires a change in mindset about the way we use it and how we solve problems. We have to teach people to think more, not less about what they are doing.

I spent the last year working with my son to empower him with the skills to use generative AI to augment and amplify his critical thinking and creativity. I distilled this teaching into a series of courses that you can use to help teach your kids, either at home or in the classroom, these same skills. This is the first of these courses.

Some of the things that we have done that you will learn to do with your kids:

- Take pictures of anything and have generative AI turn the photos into world records that you can fact check
- Interactively brainstorm how to build anything out of any material using generative AI as your partner
- Invent new games from photos of everyday objects

I teach a course on Prompt Engineering, which is the study of how you converse and solve problems with generative AI that 100,000s of people have enrolled in. I have gotten to hear about how companies all over the world are changing the future of work with generative AI. These courses are specifically designed to help you teach kids to succeed in this new world.

This course is meant for parents and teachers to do with kids. You watch the videos, preview the exercises, and then lead kids through the fun activities. You decide what to show and how to best communicate with your kids. Along the way, not only will your kids learn to innovate with generative AI, but it will reshape how you use it personally.

Generative AI for Kids, Parents, and Teachers


Are you ready to lead your organization into the future of cybersecurity while safeguarding privacy in an increasingly AI-driven world? This primer provides an essential foundation in generative AI, exploring its transformative potential and the specific cybersecurity and privacy risks it introduces. Learn to embrace AI’s capabilities while maintaining trust, compliance, and security in your organization.

What You'll Learn:

- Safeguard Organizational Privacy: This primer will help you understand the privacy implications of AI systems and the risks posed by data fusion across platforms.

- Address Emerging AI-Specific Threats: Develop a clear understanding of vulnerabilities like prompt injection, deepfakes, AI-enhanced phishing, and adversarial text in AI deployments.

- Build Confidence in AI Adoption: Gain the foundational tools and techniques to implement secure environments for AI development and responsible usage.

Who Is This Course For?

- Cybersecurity and Privacy Leaders: Seeking a primer to harness AI while preserving organizational integrity.

- IT Professionals: Interested in responsibly implementing AI within technical infrastructures.
Business Executives: Looking for a foundational understanding of AI integration without compromising compliance or ethics.

- Policy Makers: Aspiring to shape legislation around AI and privacy with a deep technical primer.

Why Take This Course?

Generative AI offers unmatched opportunities to enhance security and privacy, but it also brings novel challenges. From adversarial risks to complex data privacy concerns, leaders need a clear and concise primer to navigate these complexities effectively.

This course provides the essential knowledge and skills to balance innovation with protection. By the end, you’ll be empowered to lead AI initiatives that drive progress while mitigating the unique cybersecurity risks posed by generative AI. With this primer, you’ll confidently lay the groundwork for safe and responsible AI adoption.

Generative AI Cybersecurity & Privacy for Leaders: A Primer


Dive into the fascinating journey of artificial intelligence, from its theoretical beginnings to today's powerful generative models. This course offers a unique perspective on how AI has transformed over decades, highlighting the crucial developments in deep learning that paved the way for modern AI breakthroughs.

After completing this course, you will be able to:
- Trace the evolution of AI from its early concepts to modern generative models
- Identify key technological breakthroughs that enabled the rise of generative AI
- Understand the fundamental differences between traditional AI and generative AI
- Recognize potential applications and impacts of generative AI across various fields

You'll gain insights into the game-changing advancements—like self-supervised learning and transformers—that propelled generative AI to its current prominence. By understanding this history, you'll be better equipped to anticipate future trends and applications in AI.

Whether you're an AI enthusiast, a professional looking to leverage AI in your field, or simply curious about the technology shaping our future, this course provides valuable context to help you navigate the exciting world of generative AI.

One week of learning, one day for hands-on projects

The History and Relevance of the Rise of Generative AI


AI Agents with Model Context Protocol

Build AI Agents That Actually Work

AI agents are everywhere—but most of them fail in frustrating, unpredictable ways. They get confused, waste tokens, hit dead ends, and require constant babysitting. This course teaches you the patterns and architectures that separate agents that struggle from agents that succeed.

Using Python and the Model Context Protocol (MCP), you'll learn to build AI agents from the ground up—and more importantly, you'll learn why certain designs work while others fall apart.

What You'll Learn:

- Build MCP Tool Servers — Create the bridge that lets AI agents interact with any system: filesystems, databases, APIs, or your own custom tools

- Build a Research Agent - Create your own research agent that can explore your computer and help answer questions with documents, find that missing data, or explain how code works.

- Master the Agent Loop — Understand the universal pattern every AI agent follows: PERCEIVE → DECIDE → ACT → OBSERVE → REPEAT

- Connect agents to tools — Wire up LLMs to discover, select, and execute tools autonomously

The Patterns That Make Agents Reliable:

- Response-as-Instruction — Your tools don't just return data—they guide agent behavior in real-time. Learn to design tool responses that teach the agent what to do next, when to stop, and how to communicate results.

- Failing Forward — Turn errors from dead ends into stepping stones. Design error messages that teach agents how to recover—automatically, without human intervention. For the first time in computing history, your error messages have a reader that can actually do something about them.

- Intelligence Budget — Every token in the context window is precious attention. Learn to maximize signal and minimize noise—pre-digesting data in tools, using scripted orchestration for mechanical work, and reserving the agent's cognitive resources for decisions that actually require intelligence.


Forget everything you know about traditional AI. Agentic AI doesn’t just analyze data; it acts on it. From drafting sales emails to updating CRMs, it’s not just a tool—it’s a game-changer. Are you ready to harness its power?

Agentic AI combines Generative AI with tools and actions, enabling the creation of "agents" that revolutionize how work is done. Unlike tools that simply generate static outputs, these agents take action—drafting emails directly in your inbox, updating a CRM with client meeting notes, or analyzing sales data and producing a PowerPoint presentation.

In the fast-paced world of AI-enhanced work, understanding Agentic AI isn’t optional—it’s your competitive advantage. These intelligent agents are reshaping how tasks are executed, decisions are made, and value is created across industries. By automating repetitive workflows and enhancing high-value tasks, they empower teams to focus on innovation and strategy. Agentic AI is transforming industries, and this course will ensure you’re leading the charge, not playing catch-up. Understanding their capabilities and limitations is essential for staying competitive in this rapidly evolving landscape.

This course demystifies Agentic AI, teaching you how these agents work and how to design them to suit your needs. By the end, you’ll not only know how to differentiate genuine AI innovation from overhyped gimmicks but also be equipped to build tools that deliver tangible value. Whether you’re in business, technology, or leadership, this course will help you stay ahead of the curve.

Agentic AI and AI Agents: A Primer for Leaders


This 4 week MOOC builds upon the core Android app components and concurrency frameworks covered in Course 2 by focusing on started and bound services, local inter-process communication (IPC), and content providers. Case study apps will be examined from multiple perspectives to learn how to program these app components using Android's material design paradigm. Students will work incrementally on a hands-on project involving a material design-based RSS reader app. Each week you will add additional capabilities to the project, based on material covered in the lecture videos. You'll spend roughly 4 hours per week watching video lectures, taking quizzes, and programming assignments with Java and Android.

Android App Components - Services, Local IPC, and Content Providers


AI Agents in Java with Generative AI

AI Agents Are the Next Leap in Software. Learn to Build Them in Java.

AI agents aren’t passive tools. They think, act, and solve problems—without waiting for instructions. That’s the future of software. And in this course, you’ll learn how to build it.

Frameworks come and go. Principles last. This course cuts through the noise to teach you how AI agents really work—using rock-solid Java.

Forget tutorials on trendy APIs that’ll be dead by next quarter. You’ll learn to build AI agents from the ground up. No fluff. No shortcuts. Just the core architecture that powers intelligent systems—knowledge that stays useful no matter how fast the landscape shifts.

In this course, you will:

- Master Java-based agent architectural fundamentals - Understand the core GAME components (Goals, Actions, Memory, Environment) that make AI agents tick and how they work together in a cohesive Java system

- Leverage Java's strengths for efficient agent development - Use Java's reflection, annotation processing, and strong typing to create robust, maintainable agent frameworks with minimal boilerplate code

- Rapidly prototype and implement Java agents - Learn techniques to quickly design Java agent capabilities with prompt engineering before writing a single line of code, then efficiently translate your designs into working Java implementations

- Connect Java AI agents to real-world systems - Build Java agents that can interact with file systems, APIs, and other external services

- Create Java-powered tool-using AI assistants - Develop Java agents that can analyze files, manage data, and automate complex workflows by combining LLM reasoning with Java's extensive libraries and functionality

- Build Java developer productivity agents - Create specialized Java agents that help you write code, generate tests, and produce documentation to accelerate your software development process

Why Principles Matter More Than Frameworks

The AI landscape is changing weekly, but the core principles of agent design remain constant. By understanding how to build agents from scratch, you'll gain:

- Transferable knowledge that works across any LLM or AI technology

- Deep debugging skills because you'll understand what's happening at every level

- Framework independence that frees you from dependency on third-party libraries and allows you to succeed with any of them

- Future-proof expertise that will still be relevant when today's popular tools are long forgotten

By the end of this course, you won't just know how to use AI agents—you'll know how to build them in Java, customize them, and deploy them to solve real business problems.

This course will teach you these concepts using OpenAI's APIs, which require paid access, but the principles and techniques can be adapted to other LLMs.


Programming for a Networked World

Want to learn the basics of computer programming in a fun and innovative way? This course introduces computer programming using an educational block-based visual programming environment called NetsBlox (https://editor.netsblox.org/), emphasizing modern computer science concepts like networking, the internet, and distributed computing. The curriculum is hands-on, focusing on translating ideas into working computer programs and developing a mastery of practical computational literacy. After completing this course, you will have a solid foundation to learn professional languages like Python, Java, etc.

The course is especially suitable for K12 teachers and students who want to get a gentle introduction to computer science.

Akos Ledeczi
Brian Broll
Clifford B Anderson


Mastering Programming with MATLAB

The course builds on the foundation laid by the first course of the Specialization called “Introduction to Programming with MATLAB.” It covers more advanced programming concepts such as recursion, vectorization, function handles, algorithm efficiency and others. At the same time, it presents many features that make MATLAB a powerful programming environment for engineering and scientific computing, such as  its support for object oriented programming, the new user interface design environment and Live Scripts.

By the end of this course, you will be familiar with more advanced computer programming concepts, able to write more efficient code, and able to create object oriented MATLAB applications with graphical user interfaces.


Transform Your Decision-Making with AI Deep Research.

While your competitors spend weeks gathering information through traditional research methods, you'll master cutting-edge agentic AI tools that conduct comprehensive, autonomous investigations in minutes. This advanced course teaches executives and strategic leaders how to leverage generative AI's most powerful research capabilities to create sustainable competitive advantages.

What is Deep Research? Deep research is an advanced AI capability that works like hiring a team of PhD researchers who autonomously investigate complex topics for 10-15 minutes, gathering information from multiple sources, cross-referencing findings, and producing comprehensive 10-20 page reports with proper linked citations. Unlike standard AI chat where you get instant but limited responses with potentially incorrect citations, deep research agents conduct extended self-dialogue, adapt their search strategies based on what they discover, and synthesize vast amounts of current information into cohesive analysis—delivering the depth and rigor of professional consulting work in a fraction of the time and cost. Best of all, they provide fact checkable citations and links.

What You'll Master:

Instant Strategic Consulting: Deploy AI agents that deliver PhD-level analysis in 15 minutes instead of hiring consultants for weeks. Get comprehensive market assessments, competitive intelligence, and strategic recommendations when traditional consulting isn't feasible, affordable, or fast enough.

Elite Talent Discovery: Systematically identify and evaluate top performers across any domain with AI Deep Research—from "Java AI developers in Nashville" to "automotive specialists for vintage Toyotas." Move beyond superficial LinkedIn searches to evidence-based expertise verification that reveals genuine competence.

Advanced Procurement Intelligence: Generate detailed buying or procurement guides tailored to your specific situation and constraints with AI Deep Research. From HVAC systems for century-old homes to enterprise software for your industry, get expert-level purchasing recommendations with vendor comparisons, pricing strategies, and negotiation tactics.

Cross-Domain Team Assembly: Solve complex problems requiring interdisciplinary expertise by automatically identifying and connecting specialists across multiple fields with AI Deep Research. Perfect for research initiatives, strategic projects, or any challenge that spans technical domains.

Rapid Due Diligence: Compress weeks of research into hours for investment decisions, partnership evaluations, technology assessments, and market entries. Get comprehensive intelligence that traditional research timelines can't accommodate.

Actionable Intelligence Architecture: Design research tasks that deliver immediately implementable recommendations rather than abstract analysis. Learn to structure investigations that produce specific action plans, vendor contact lists, implementation roadmaps, and decision frameworks—transforming research from information gathering into strategic execution guidance that drives immediate business value.

What You Need: All you need is a generative AI account with Deep Research capabilities, such as ChatGPT Deep Research, Claude Research, or Gemini Deep Research.

The leaders who master these AI research capabilities today will dominate their markets tomorrow. While your competitors are still scheduling meetings to plan their research, you'll already have the intelligence you need to make winning decisions. Information velocity isn't just an advantage anymore—it's the ultimate competitive differentiator.

Generative AI Deep Research: Strategic AI Edge for Leaders


ChatGPT Advanced Data Analysis

ChatGPT Advanced Data Analysis is going to transform tasks by helping amplify your productivity and supporting your creativity. ChatGPT Advanced Data Analysis can help you augment your intelligence and automate tasks, such as:

1. Turning an Excel file into visualizations and then slides inside a PowerPoint presentation; extracting data from a series of PDFs
2. Answering questions about what is in the PDFs, and visualizing the data; automatically determining if a receipt complies with a travel policy captured in a PDF
3. Transforming a document into a training presentation and associated quizzes; reading and reorganizing a set of documents based on what they contain
4. Producing social media and marketing content from a series of documents or video transcripts
5. Automating resizing and editing of videos/images while also cataloging them in a CSV

Anyone with ChatGPT Advanced Data Analysis can tap into these capabilities without any prior experience in programming. The course teaches you how to converse with ChatGPT Advanced Data Analysis to accomplish these tasks, how to think about problem solving, and what types of tasks are good fits for the tool. You will learn a wide range of building blocks that you can apply in your own work and life.

Large language models respond to instructions and questions posed by users in natural language statements, known as “prompts”. Although large language models will disrupt many fields, most users lack the skills to write effective prompts. Expert users, who understand how to write good prompts, are orders of magnitude more productive and can unlock significantly more creative uses for these tools. This course will introduce you to prompt writing skills that target ChatGPT Advanced Data Analysis.


In the era of Generative AI, the demand for personalized and specialized Generative AI assistants is skyrocketing. Large language models like GPTs have demonstrated their remarkable capabilities, but what if you could harness their power to create custom AI assistants tailored to your specific needs? Welcome to the world of custom GPTs, where you can build intelligent systems that understand your domain, speak your language, and solve your unique challenges.

This cutting-edge course will guide you through the exciting journey of creating and deploying custom GPTs that cater to diverse industries and applications. Imagine having a virtual assistant that can tackle complex legal document analysis, streamline supply chain logistics, or even assist in scientific research and hypothesis generation. The possibilities are endless!

Throughout the course, you'll delve into the intricacies of building GPTs that can use your documents to answer questions, patterns to create amazing human and AI interaction, and methods for customizing the tone of your GPTs. You'll learn how to design and implement rigorous testing scenarios to ensure your AI assistant's accuracy, reliability, and human-like communication abilities.

Prepare to be amazed as you explore real-world examples built around a GPT for Travel and Business Expense Management. The examples show how a GPT can help users book flights, hotels, and transportation while adhering to company policies and budgets. Additionally, the GPT can help streamline expense reporting and reimbursement processes, ensuring compliance and accuracy.

Whether you're a business leader, entrepreneur, developer, or educator, this course will equip you with the skills to harness the transformative potential of custom GPTs. Unlock new realms of productivity, innovation, and personalized experiences by building AI assistants that truly understand and cater to your unique needs.

Enroll now and join the forefront of AI revolution, where you'll learn to create intelligent systems that not only comprehend but also anticipate and exceed your expectations.

OpenAI GPTs: Creating Your Own Custom AI Assistants


AI Agents Are the Next Leap in Software. Learn to Build Them in TypeScript.

AI agents aren't passive tools. They think, act, and solve problems—without waiting for instructions. That's the future of software. And in this course, you'll learn how to build it.

Frameworks come and go. Principles last. This course cuts through the noise to teach you how AI agents really work—using TypeScript and JavaScript.

Forget tutorials on trendy APIs that'll be dead by next quarter. You'll learn to build AI agents from the ground up. No fluff. No shortcuts. Just the core architecture that powers intelligent systems—knowledge that stays useful no matter how fast the landscape shifts.

In this course, you will:

- Master TypeScript-based agent architectural fundamentals - Understand the core GAME components (Goals, Actions, Memory, Environment) that make AI agents tick and how they work together in a cohesive TypeScript system

- Leverage TypeScript's strengths for efficient agent development - Use TypeScript's type system, decorators, and modern JavaScript features to create robust, maintainable agent frameworks with excellent developer experience and type safety

- Rapidly prototype and implement TypeScript agents - Learn techniques to quickly design agent capabilities with prompt engineering before writing a single line of code, then efficiently translate your designs into working TypeScript implementations

- Connect TypeScript AI agents to real-world systems - Build agents that can interact with file systems, APIs, databases, and other external services using Node.js and the rich npm ecosystem

- Create TypeScript-powered tool-using AI assistants - Develop agents that can analyze files, manage data, and automate complex workflows by combining LLM reasoning with TypeScript's extensive libraries and functionality

- Build TypeScript developer productivity agents - Create specialized agents that help you write code, generate tests, and produce documentation to accelerate your software development process

Why Principles Matter More Than Frameworks:

The AI landscape is changing weekly, but the core principles of agent design remain constant. By understanding how to build agents from scratch, you'll gain:

Transferable knowledge that works across any LLM or AI technology

Deep debugging skills because you'll understand what's happening at every level

Framework independence that frees you from dependency on third-party libraries and allows you to succeed with any of them

Future-proof expertise that will still be relevant when today's popular tools are long forgotten

By the end of this course, you won't just know how to use AI agents—you'll know how to build them in TypeScript, customize them, and deploy them to solve real business problems.

You will need an OpenAI API Key or equivalent API keys from Anthropic, Google, etc.

AI Agents in Typescript/Javascript with Generative AI


Imagine if your documents—policies, procedures, or even meeting notes—could magically transform into fully functional Excel spreadsheets. What used to take hours of manual labor, deciphering complex rules, and building formulas can now be done in minutes with the help of ChatGPT.  This course is your gateway to unlocking that magic, turning the impossible into the achievable.

Through hands-on videos, practical assignments, and real-world analogies, you'll learn how to design, prototype, and populate Excel spreadsheets like never before. For instance, think of ChatGPT as your personal assistant who not only listens to your requests but also drafts Excel formulas, creates VBA scripts, and generates polished visualizations—all while making sure everything works perfectly through robust two-sided accuracy checks.

Here’s what you’ll achieve:

- Transform Policies into Spreadsheets: Imagine taking a dense HR policy document and converting it into a sleek, interactive tool for tracking leave requests—all by simply chatting with ChatGPT.

- Prototyping on the Fly: Like sketching ideas on a napkin, ChatGPT helps you rapidly prototype Excel sheets and populate them with dummy data, giving life to your ideas in moments. Snap a picture of the inside of your pantry and have it turned into an inventory tracking system.

- Excel Formula Wizardry: Tame the most complex formulas with ChatGPT’s guidance, from financial models to error-proofed calculations, ensuring you can solve problems without breaking a sweat.

- Visualizations that Wow: Snap a picture of a graph or describe a chart, and ChatGPT will help you replicate or design it in Excel with precision and flair.

- Automate with VBA: Automate repetitive tasks by learning how ChatGPT can craft VBA scripts tailored to your unique needs—no programming experience required.

By the end of this course, you’ll have the skills to turn everyday challenges into Excel solutions, unlocking newfound productivity and creativity. Whether you’re a professional, a student, or simply someone who wants to do more with less effort, this course equips you to create, innovate, and excel like never before.

ChatGPT + Excel: Master AI-driven Formulas & Visualizations


Struggling to prepare your team for unexpected cybersecurity threats? Imagine having an AI partner that can help you build hyper-realistic tabletop scenarios, practice decision-making under pressure, and uncover blind spots—all while saving time and resources. This course will guide you on a journey to revolutionize your approach to cybersecurity training by integrating ChatGPT into your tabletop exercises, ensuring your organization is ready for the real game.

What You'll Learn:

Create Dynamic and Realistic Cybersecurity Scenarios: Use ChatGPT to design interactive scenarios with branching decision trees. Craft exercises that adapt to participants’ choices, pushing them to think critically about complex challenges while uncovering new angles of attack.

Perform Individualized, Targeted Practice with Micro-Tabletops: Learn how to use ChatGPT to create "micro-tabletops," small-scale exercises that allow individual team members or small groups to focus on their specific responsibilities and tools. These targeted simulations enable frequent practice, iterative hardening of specific domains (e.g., Active Directory or Okta), and integration with broader team exercises to ensure overall organizational preparedness.

Master the Flipped Interaction Pattern for Training: Discover how to let AI take the lead in tabletop facilitation. This unique approach allows ChatGPT to simulate evolving incidents, ask probing questions, and dynamically adapt based on your team’s responses—making every session a tailored learning experience.

Inject Real-World Pressure into Your Scenarios: Learn how to add authentic tension to decision-making exercises. With ChatGPT, you can create scenarios that mimic the real-world ripple effects of cybersecurity breaches, such as regulatory deadlines, stakeholder complaints, or operational disruptions.

Optimize Your Team’s Response Through Iterative Practice: Transform the way your organization practices cybersecurity. Generate instant feedback, identify critical gaps, and refine responses—all in a fraction of the time and cost of traditional tabletop methods.

Build Collaborative Decision-Making Skills Across Departments: Train technical, legal, and communications teams to coordinate effectively during crises. Use ChatGPT to highlight each group’s unique pressure points, ensuring all stakeholders are prepared for their roles in an incident response.

Who Is This Course For?

Cybersecurity Professionals: Overwhelmed by the time and cost of creating tabletops? Learn to streamline the process with AI.

IT and Security Teams: Want to simulate realistic, high-pressure incidents? Use ChatGPT to craft exercises that build confidence and capability.

Business Leaders and Decision Makers: Need to ensure your organization is ready for the unexpected? Gain insights into how AI can enhance readiness.

Educators and Facilitators: Interested in teaching cybersecurity skills interactively? Master tools and techniques to engage participants in novel and impactful ways.

Why Take This Course?

Cybersecurity breaches are inevitable, but unpreparedness doesn’t have to be. With ChatGPT, you can democratize access to high-quality training, creating customized, realistic exercises that challenge your team to respond effectively. Whether simulating a phishing attack, addressing regulatory fallout, or handling complex stakeholder dynamics, this course empowers you to enhance your incident response capabilities.

Imagine transforming your tabletops into immersive learning experiences—without the time, cost, and complexity of traditional methods. By the end of this course, you’ll have the skills to use generative AI for designing, facilitating, and iterating on exercises that keep your team sharp and ready for anything.

Join the growing number of professionals revolutionizing cybersecurity readiness with AI. Don’t get caught unprepared—enroll today and start building stronger defenses with ChatGPT!

ChatGPT + Cybersecurity: AI-Powered Tabletops & Training