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Noah Gift,
Alfredo Deza,
and
Derek Wales
This introductory course is designed for beginners with no prior knowledge of generative AI. You will start by gaining a high-level understanding of what generative AI is and how it works. Through interactive lessons and hands-on examples, you will learn fundamental skills like providing effective prompts and iteratively improving the generated outputs. As the course progresses, you will dive deeper into specific major generative AI models, including their unique capabilities and limitations. Finally,, you will get practical experience using leading systems like GitHub Copilot, DALL-E, and OpenAI to generate code, images, and text. By the end, you will have developed core knowledge to start experimenting with generative AI in a responsible and effective way for a variety of applications. This course aims to provide a friendly introduction to prepare complete beginners for further exploration of this rapidly evolving technology.
Register for this course and see more details by visiting:
OpenCourser.com/course/l2hsm1/introduction
What's inside
Syllabus
Introduction to Generative AI
This week, you will learn what generative AI is and how it has evolved from early AI to the large language models used today. You'll understand how these models work in applications by learning about model architectures and the training process. The week provides an overview of major foundation models like ChatGPT and Hugging Face, highlighting their capabilities and limitations. You'll explore the generative AI landscape, comparing options like open source models, local models, and cloud APIs. By the end, you'll have a solid base of knowledge about the foundations of this technology and options for accessing and leveraging different AI systems.
Read more
Syllabus
Introduction to Generative AI
This week, you will learn what generative AI is and how it has evolved from early AI to the large language models used today. You'll understand how these models work in applications by learning about model architectures and the training process. The week provides an overview of major foundation models like ChatGPT and Hugging Face, highlighting their capabilities and limitations. You'll explore the generative AI landscape, comparing options like open source models, local models, and cloud APIs. By the end, you'll have a solid base of knowledge about the foundations of this technology and options for accessing and leveraging different AI systems.
Read more
Interacting with models
This week, you will learn the fundamentals of prompt engineering to interact effectively with generative AI models. You'll understand the concept of few-shot prompting and practice basic prompting techniques using context and examples. Building on this, you'll learn methods for improving prompts through personas, detailed instructions, and iteration based on feedback. Finally, you'll explore more advanced skills like breaking down tasks, chaining prompts, and other useful techniques to overcome context limitations.
Building robust Generative AI systems
This week, you will explore different types of generative AI applications, including API-based, embedded model, and multi-model systems. You'll learn the fundamentals of building robust applications using techniques like Retrieval Augmented Generation (RAG) to improve context. Through hands-on exercises, you'll gain experience testing an application locally and deploying it on the cloud.
Applications of LLMs
Here, you will learn the key capabilities of the OpenAI API. You will generate images with OpenAI’s DALL-E, “fine tuning” LLM models to Reddit questions and answers and summarize videos with OpenAI’s Whisper Model.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a comprehensive introduction to generative AI, from foundational concepts to practical applications
Taught by experienced instructors with expertise in generative AI
Offers hands-on experience with leading generative AI systems like GitHub Copilot, DALL-E, and OpenAI
Develops core skills in prompt engineering, enabling learners to effectively interact with generative AI models
Covers a wide range of generative AI applications, from image generation to text summarization
Suitable for beginners with no prior knowledge of generative AI
Save this course
Save Introduction to Generative AI to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Generative AI with these
activities:
Review Probability and Statistics
Show steps
Review the basics of probability and statistics to strengthen your foundation for generative AI.
Browse courses on
Probability
Show steps
-
Go over your notes or textbook from previous probability and statistics courses.
-
Practice solving problems related to probability and statistics.
Review prerequisite math concepts for generative AI
Show steps
Reviewing prerequisite math concepts will strengthen your foundational understanding and help you grasp the mathematical underpinnings of generative AI models.
Browse courses on
Math
Show steps
-
Identify the math concepts used in generative AI, such as linear algebra, calculus, and probability
-
Review the relevant concepts from your previous coursework or textbooks
-
Solve practice problems to test your understanding
Practice prompt engineering for generative AI models
Show steps
Practicing prompt engineering will enhance your ability to effectively interact with generative AI models and obtain desired outputs.
Browse courses on
Prompt Engineering
Show steps
-
Familiarize yourself with different prompt engineering techniques, such as context establishment, fine-tuning, and chaining
-
Use online tools or platforms to practice prompt engineering
-
Experiment with different prompts and observe the corresponding model outputs
-
Iteratively refine your prompts based on feedback from the model or human evaluators
Two other activities
Expand to see all activities and additional details
Show all five activities
Volunteer as a mentor or tutor for aspiring generative AI learners
Show steps
Mentoring or tutoring others will reinforce your understanding of generative AI and help you develop your communication skills.
Browse courses on
Community Involvement
Show steps
-
Reach out to organizations or platforms that offer mentoring or tutoring programs related to generative AI
-
Share your knowledge and expertise with aspiring learners
-
Provide guidance, feedback, and encouragement to help others succeed
Participate in hackathons or competitions focused on generative AI
Show steps
Participating in competitions will push your generative AI skills to the limit and provide opportunities to learn from others.
Show steps
-
Identify upcoming hackathons or competitions related to generative AI
-
Form a team or collaborate with others
-
Develop a creative and impactful project or solution
-
Present your project and compete against other teams
-
Network with other participants and industry professionals
Review Probability and Statistics
Show steps
Review the basics of probability and statistics to strengthen your foundation for generative AI.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Go over your notes or textbook from previous probability and statistics courses.
- Practice solving problems related to probability and statistics.
Review prerequisite math concepts for generative AI
Show steps
Reviewing prerequisite math concepts will strengthen your foundational understanding and help you grasp the mathematical underpinnings of generative AI models.
Browse courses on
Math
Show steps
Show steps
Show steps
- Identify the math concepts used in generative AI, such as linear algebra, calculus, and probability
- Review the relevant concepts from your previous coursework or textbooks
- Solve practice problems to test your understanding
Practice prompt engineering for generative AI models
Show steps
Practicing prompt engineering will enhance your ability to effectively interact with generative AI models and obtain desired outputs.
Browse courses on
Prompt Engineering
Show steps
Show steps
Show steps
- Familiarize yourself with different prompt engineering techniques, such as context establishment, fine-tuning, and chaining
- Use online tools or platforms to practice prompt engineering
- Experiment with different prompts and observe the corresponding model outputs
- Iteratively refine your prompts based on feedback from the model or human evaluators
Two other activities
Expand to see all activities and additional details
Show all five activities
Volunteer as a mentor or tutor for aspiring generative AI learners
Show steps
Mentoring or tutoring others will reinforce your understanding of generative AI and help you develop your communication skills.
Browse courses on
Community Involvement
Show steps
Show steps
Show steps
- Reach out to organizations or platforms that offer mentoring or tutoring programs related to generative AI
- Share your knowledge and expertise with aspiring learners
- Provide guidance, feedback, and encouragement to help others succeed
Participate in hackathons or competitions focused on generative AI
Show steps
Participating in competitions will push your generative AI skills to the limit and provide opportunities to learn from others.
Show steps
Show steps
Show steps
- Identify upcoming hackathons or competitions related to generative AI
- Form a team or collaborate with others
- Develop a creative and impactful project or solution
- Present your project and compete against other teams
- Network with other participants and industry professionals
Career center
Learners who complete Introduction to Generative AI will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying machine learning models to improve business outcomes. This course can help you build a foundation in generative AI, which is a rapidly growing field with applications in various industries. You will learn how to interact with generative AI models effectively, build robust generative AI systems, and apply these models to solve real-world problems. With the skills gained from this course, you will be well-positioned to succeed as a Machine Learning Engineer and drive innovation through the use of generative AI.
Data Scientist
Data Scientist
Data Scientists are responsible for extracting insights from data to improve decision-making. This course can help you develop the skills needed to use generative AI models for data analysis and prediction. You will learn how to interact with these models effectively, build robust systems, and apply them to a variety of data-driven tasks. With the knowledge gained from this course, you will be well-equipped to succeed as a Data Scientist and leverage generative AI to drive data-driven decision-making.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help you build a foundation in generative AI, which is becoming increasingly important in software development. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to various software development tasks. With the skills gained from this course, you will be well-positioned to succeed as a Software Engineer and drive innovation through the use of generative AI.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. This course can help you develop the skills needed to use generative AI to enhance product development. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to a variety of product development tasks. With the knowledge gained from this course, you will be well-equipped to succeed as a Product Manager and leverage generative AI to drive innovation and improve product outcomes.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course can help you build a foundation in generative AI, which is increasingly being used in quantitative analysis. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to a variety of financial analysis tasks. With the skills gained from this course, you will be well-positioned to succeed as a Quantitative Analyst and leverage generative AI to drive innovation in financial analysis.
Research Scientist
Research Scientist
Research Scientists conduct research in various fields, including computer science, engineering, and medicine. This course can help you build a foundation in generative AI, which is rapidly growing in research. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to a variety of research projects. With the skills gained from this course, you will be well-positioned to succeed as a Research Scientist and drive innovation through the use of generative AI.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. This course can help you build a foundation in generative AI, which can be used to automate data analysis tasks. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to a variety of data analysis tasks. With the skills gained from this course, you will be well-positioned to succeed as a Data Analyst and leverage generative AI to drive efficiency and improve data-driven decision-making.
Business Analyst
Business Analyst
Business Analysts identify and solve business problems using data and technology. This course can help you build a foundation in generative AI, which has applications in various business domains. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to identify opportunities, solve problems, and improve business outcomes. With the skills gained from this course, you will be well-positioned to succeed as a Business Analyst and leverage generative AI to drive innovation and improve business performance.
UX Designer
UX Designer
UX Designers design user interfaces that are both functional and enjoyable to use. This course can help you build a foundation in generative AI, which can be used to enhance the user experience. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to generate ideas, design prototypes, and improve user interfaces. With the skills gained from this course, you will be well-positioned to succeed as a UX Designer and leverage generative AI to create innovative and user-centric designs.
Content Creator
Content Creator
Content Creators develop and publish content for various platforms, including websites, social media, and video channels. This course can help you build a foundation in generative AI, which can be used to create engaging and informative content. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to generate ideas, write text, and create images and videos. With the skills gained from this course, you will be well-positioned to succeed as a Content Creator and leverage generative AI to produce high-quality and engaging content that resonates with your audience.
Technical Writer
Technical Writer
Technical Writers create documentation and other materials that explain technical concepts. This course can help you build a foundation in generative AI, which can be used to improve the quality and efficiency of technical writing. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to generate documentation, create training materials, and translate technical content. With the skills gained from this course, you will be well-positioned to succeed as a Technical Writer and leverage generative AI to create clear and concise technical communication.
Digital Marketer
Digital Marketer
Digital Marketers use digital technologies to promote products and services. This course can help you build a foundation in generative AI, which can be used to enhance digital marketing campaigns. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to generate ad copy, create social media content, and optimize marketing campaigns. With the skills gained from this course, you will be well-positioned to succeed as a Digital Marketer and leverage generative AI to drive innovation and improve marketing outcomes.
Educator
Educator
Educators teach students at all levels, from elementary school to university. This course can help you build a foundation in generative AI, which can be used to enhance teaching and learning experiences. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to create lesson plans, generate teaching materials, and provide personalized feedback to students. With the skills gained from this course, you will be well-positioned to succeed as an Educator and leverage generative AI to create engaging and effective learning environments for your students.
Consultant
Consultant
Consultants provide advice and guidance to businesses and organizations. This course can help you build a foundation in generative AI, which can be used to enhance consulting services. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to generate reports, presentations, and other materials for clients. With the skills gained from this course, you will be well-positioned to succeed as a Consultant and leverage generative AI to provide innovative solutions and drive value for your clients.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. This course can help you build a foundation in generative AI, which can be used to enhance project management processes. You will learn how to interact with generative AI models effectively, build robust systems, and apply them to generate project plans, track progress, and communicate with stakeholders. With the skills gained from this course, you will be well-positioned to succeed as a Project Manager and leverage generative AI to improve project efficiency and outcomes.
For more career information including salaries, visit:
OpenCourser.com/course/l2hsm1/introduction
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Generative AI.
Comprehensive textbook on deep learning. It covers the fundamentals, architectures, and applications of deep learning models, providing a solid foundation for understanding and applying generative AI techniques.
Save
Provides a comprehensive overview of computer vision, which key field related to generative AI. It covers topics such as image processing, feature detection, and object recognition, providing a foundation for understanding how generative AI models generate images.
Introduces the fundamentals of deep learning using the Fastai library and PyTorch framework. It covers basic concepts like neural networks, convolutional neural networks, and natural language processing, which are essential for understanding generative AI.
Classic introduction to reinforcement learning, which type of machine learning that is used in generative AI models. It provides a comprehensive overview of the theory and algorithms, helping readers understand how generative AI models can learn from feedback and improve their performance.
Covers the theory and methods of statistical learning with sparsity. It provides a deep dive into the mathematical underpinnings of generative AI models, helping readers understand how they learn from data and make predictions.
Provides a theoretical foundation for machine learning. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning, helping readers understand the mathematical underpinnings of generative AI.
Concise introduction to machine learning and deep learning. It provides a quick overview of the core concepts and algorithms, making it a good starting point for learners who are new to the field.
While not specifically focused on generative AI, this book offers a comprehensive introduction to deep learning, providing a solid foundation for understanding and working with generative AI models.
Examines the role of humans in the development and deployment of machine learning systems, including generative AI models, providing insights into responsible and effective use of these technologies.
Save
Explores the theory and practice of generative adversarial networks (GANs), a type of generative AI model, providing in-depth knowledge for those interested in the technical aspects of GANs.
Explores the theory and algorithms of convex optimization, which is used in some generative AI models, providing a solid mathematical foundation for understanding and working with these models.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/l2hsm1/introduction
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Effort
5 hours/week for 4 weeks
Level
Introductory
Via
Coursera
Institution
Duke University
Instructors
Noah Gift
Alfredo Deza
Derek Wales
Language
English
Good to know
Provides a comprehensive introduction to generative AI, from foundational concepts to practical applications
Taught by experienced instructors with expertise in generative AI
Offers hands-on experience with leading generative AI systems like GitHub Copilot, DALL-E, and OpenAI
Develops core skills in prompt engineering, enabling learners to effectively interact with generative AI models
Covers a wide range of generative AI applications, from image generation to text summarization
Suitable for beginners with no prior knowledge of generative AI
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