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Alfredo Deza
and
Noah Gift
Gain a solid foundation in generative AI with this beginner-friendly course.
- Understand what generative AI is and how it works through interactive lessons
- Master the art of effective prompting and iterative output refinement
- Dive deep into major generative models - capabilities and limitations
Course Highlights:
Read more
Gain a solid foundation in generative AI with this beginner-friendly course.
- Understand what generative AI is and how it works through interactive lessons
- Master the art of effective prompting and iterative output refinement
- Dive deep into major generative models - capabilities and limitations
Course Highlights:
Read more
Gain a solid foundation in generative AI with this beginner-friendly course.
- Understand what generative AI is and how it works through interactive lessons
- Master the art of effective prompting and iterative output refinement
- Dive deep into major generative models - capabilities and limitations
Course Highlights:
- Get a high-level overview of generative AI concepts and applications
- Learn through hands-on examples and practical exercises
- Develop core skills to experiment with generative AI responsibly
- Explore use cases across different domains like text, images, code etc.
- Ideal for beginners looking to kickstart their generative AI journey
This comprehensive introduction equips you with the essential knowledge to navigate the rapidly evolving generative AI landscape confidently.
Register for this course and see more details by visiting:
OpenCourser.com/course/3gnifd/introduction
What's inside
Learning objectives
- Learn to utilize generative ai for automation.
- Develop generative ai software solutions.
- Build solutions with prompt engineering to enhance generative ai output.
- Learn to utilize generative ai for automation.
- Develop generative ai software solutions.
- Build solutions with prompt engineering to enhance generative ai output.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for beginners, providing a solid foundation in generative AI
Provides practical exercises and hands-on examples for better understanding
Covers a wide range of use cases across different domains including text, images, and code
Emphasizes responsible experimentation with generative AI
Taught by recognized instructors in the field of generative AI
Could benefit from providing more advanced concepts and techniques
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:
Explore online tutorials on generative AI
Show steps
Familiarize yourself with the fundamentals of generative AI and its applications through structured tutorials.
Browse courses on
Generative AI
Show steps
-
Identify reputable platforms offering generative AI tutorials
-
Select tutorials aligned with your learning objectives
-
Follow the tutorials step-by-step and experiment with the code examples
-
Troubleshoot any errors and seek additional resources for clarification
Practice hands-on exercises with generative AI tools
Show steps
Deepen your understanding of generative AI techniques through practical implementation and experimentation.
Browse courses on
Hands-on Exercises
Show steps
-
Choose a generative AI platform and create an account
-
Explore the documentation and resources provided by the platform
-
Follow guided tutorials or create your own experiments
-
Analyze the results and identify areas for improvement
-
Share your findings and collaborate with others in online communities
Develop a generative AI project
Show steps
Apply your generative AI skills to solve real-world problems and demonstrate your understanding of the technology.
Browse courses on
Project Development
Show steps
-
Brainstorm a problem or idea that can be addressed with generative AI
-
Design a solution using generative AI techniques
-
Implement your solution and test its performance
-
Document your project and share it with others
-
Seek feedback and iterate on your project to improve its effectiveness
Show all three activities
Explore online tutorials on generative AI
Show steps
Familiarize yourself with the fundamentals of generative AI and its applications through structured tutorials.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Identify reputable platforms offering generative AI tutorials
- Select tutorials aligned with your learning objectives
- Follow the tutorials step-by-step and experiment with the code examples
- Troubleshoot any errors and seek additional resources for clarification
Practice hands-on exercises with generative AI tools
Show steps
Deepen your understanding of generative AI techniques through practical implementation and experimentation.
Browse courses on
Hands-on Exercises
Show steps
Show steps
Show steps
- Choose a generative AI platform and create an account
- Explore the documentation and resources provided by the platform
- Follow guided tutorials or create your own experiments
- Analyze the results and identify areas for improvement
- Share your findings and collaborate with others in online communities
Develop a generative AI project
Show steps
Apply your generative AI skills to solve real-world problems and demonstrate your understanding of the technology.
Browse courses on
Project Development
Show steps
Show steps
Show steps
- Brainstorm a problem or idea that can be addressed with generative AI
- Design a solution using generative AI techniques
- Implement your solution and test its performance
- Document your project and share it with others
- Seek feedback and iterate on your project to improve its effectiveness
Show all three activities
Career center
Learners who complete Introduction to Generative AI will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists discover business opportunities from both structured and unstructured data, analyze data to develop solutions, and build and maintain predictive models.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers work in the field of computer science. They apply artificial intelligence tools to real-world problems and design different algorithms for the training of models.
Software Developer
Software Developer
Software Developers build and maintain software for applications, websites, and software packages.
Data Analyst
Data Analyst
Data Analysts collect, clean, and organize data for reporting and analysis.
Product Manager
Product Manager
Product Managers research, design, build, and market new products, and they manage their life cycles.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze and forecast financial information to help make sound investment decisions.
Robotics Engineer
Robotics Engineer
Robotics Engineers design, build, and test robots.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design and develop computer vision systems to allow computers to see and interpret images.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers work on the theoretical foundations of machine learning and develop new machine learning algorithms.
Artificial Intelligence Specialist
Artificial Intelligence Specialist
Artificial Intelligence Specialists work on the design, development, and deployment of artificial intelligence systems.
Natural Language Processing Specialist
Natural Language Processing Specialist
Natural Language Processing Specialists design and develop models and algorithms that allow computers to understand and generate human language.
Business Analyst
Business Analyst
Business Analysts gather, analyze, and synthesize data in order to resolve problems and improve operations.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to aid decision-making and optimize business efficiency.
Data Architect
Data Architect
Data Architects design and build data management systems.
Data Engineer
Data Engineer
Data Engineers design and build data pipelines to collect, store, and process data.
For more career information including salaries, visit:
OpenCourser.com/course/3gnifd/introduction
Featured in The Course Notes
This course is mentioned in our blog,
The Course Notes. Read
one article that features
Introduction to Generative AI:
To read more articles from OpenCourser, visit:
OpenCourser.com/notes
Reading list
We've selected 16 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.
Delves into the technical details of generative deep learning models, providing a hands-on guide to building and training your own generative AI systems.
Teaches you how to build and train deep learning models using Fastai and PyTorch, two popular deep learning libraries. It good choice for those who want to learn how to apply generative AI in their own projects.
Save
A reference book on deep learning techniques used in generative AI, providing a solid foundation for understanding and implementing models.
Save
Explores the history and future of AI, providing a comprehensive overview of the field and its potential impact on society.
Save
Explores the potential risks and benefits of superintelligence, providing a thought-provoking examination of the future of AI and its implications for humanity.
Save
Explores the potential future of humanity in the age of AI, providing insights into the challenges and opportunities that lie ahead.
Explores the impact of AI on the workplace, providing insights into how organizations can use AI to augment human capabilities and drive productivity.
Explores the potential for AI to lead to a technological singularity, providing a provocative and challenging perspective on the future of humanity.
Provides a gentle introduction to machine learning, making it accessible to beginners with no prior knowledge of the field. It covers the basics of machine learning algorithms and how they can be used to solve real-world problems.
Save
Analyzes different thinking styles and their impact on perception and understanding.
Save
Explores consciousness, self-awareness, and the nature of the mind.
Save
Weaves together mathematics, music, art, and philosophy, exploring patterns and self-reference.
Save
Examines consciousness in relation to computation and the limits of artificial intelligence.
Delves into the strange loop of self-reference in consciousness and the brain.
Save
Challenges traditional notions of consciousness and selfhood, suggesting a more distributed and interactive view.
Explores the philosophical question of why there is something rather than nothing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3gnifd/introduction
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Generative AI in Education
Effort
3 to 6 hours per week for 3 weeks
Level
Introductory
Via
edX
Institution
Pragmatic AI Labs
Instructors
Alfredo Deza
Noah Gift
Session
March 15, 2024
- March 23, 2028
Language
English
Transcript
English
Good to know
Suitable for beginners, providing a solid foundation in generative AI
Provides practical exercises and hands-on examples for better understanding
Covers a wide range of use cases across different domains including text, images, and code
Emphasizes responsible experimentation with generative AI
Taught by recognized instructors in the field of generative AI
Could benefit from providing more advanced concepts and techniques
Featured in The Course Notes
Read
one article that features
this course,
Introduction to Generative AI
from our blog, The Course Notes:
To read more articles from OpenCourser, visit:
OpenCourser.com/notes
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