Reinforcement Learning from Human Feedback (RLHF) from Pluralsight

In this course we explore one corner of the expanding AI universe, and review some of the basic principles found in reinforcement learning from human feedback (RLHF), the technology underlying great AI tools such as ChatGPT, Bard, and more.

Have you ever wondered how tools like ChatGPT and Bard are able to generate great responses to the questions we pose? How they can respond to a prompt like “Plan a trip to Italy this fall and suggest great things to see,” and produce a response containing a full itinerary with places to see, the best time to visit, and the sites you shouldn't miss?

In this course, Reinforcement Learning from Human Feedback (RLHF), you’ll gain the ability to understand what is going on behind the scenes to create responses to your prompts.

First, you’ll explore why having all the information available is not enough to create a great response.

Next, you’ll discover how we teach a machine learning model to handle all that data and craft a response that people like.

Finally, you’ll learn how none of it is magic, just some really great engineering by some bright people.

When you’re finished with this course, you’ll have the skills and knowledge of reinforcement learning with human feedback needed to understand how this great engineering works and produces its amazing results.

What's inside

Syllabus

Course Overview

Understanding Text-generative Applications

What Is Wrong with the Pre-trained GPT Model?

Supervised Fine-tuning

Reward Model Training

Fine-tuning via Reinforcement Learning

Implementing RLHF

Challenges and Limitations of RLHF

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Specifically explores reinforcement learning from human feedback (RLHF), a technology that underlies tools such as ChatGPT and Bard

Demonstrates how to understand the inner workings of AI tools like ChatGPT and Bard

Develops an understanding of the principles and challenges involved in RLHF

Shares insights into the engineering processes behind the creation of these AI tools

Applicable to learners interested in understanding the inner workings of AI language generation models

Taught by Jerry Kurata, an experienced instructor in the field of AI and machine learning

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 Reinforcement Learning from Human Feedback (RLHF) with these activities:

Review Course Syllabus

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Read the syllabus thoroughly and highlight the important sections
Check the prerequisites to ensure you have the required knowledge

Review Mathematics Concepts for Reinforcement Learning

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Ensure a solid mathematical foundation for reinforcement learning

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Review the basics of calculus, including derivatives and integrals
Familiarize yourself with linear algebra concepts, such as vectors and matrices

Follow Pre-recorded Tutorials on Reinforcement Learning

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Enhance your understanding of the concepts by leveraging pre-recorded tutorials

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Identify and select reputable tutorials that cover the core concepts
Dedicate time to go through the tutorials, taking notes of key points

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Solve Reinforcement Learning Exercises

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Reinforce your understanding by applying the concepts to practical exercises

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Find online platforms or textbooks that provide exercises
Attempt to solve exercises, focusing on understanding the problem-solving process
Review your solutions and identify areas for improvement

Organize a Study Group with Peers

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Collaborate with peers to enhance understanding and engage in discussions

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Connect with classmates or fellow students
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Discuss course topics, share insights, and work on assignments together

Summarize Key Concepts in Own Words

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Deepen your understanding by explaining concepts to yourself or others

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Identify a specific topic or concept
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Attend Industry Webinars or Conferences on Reinforcement Learning

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Research and identify upcoming webinars or conferences
Register and attend the selected events

Assist a Fellow Student with Reinforcement Learning Concepts

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Reinforce your own understanding by teaching and explaining concepts to others

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Identify a fellow student who could benefit from your assistance
Offer your support and collaborate on understanding concepts
Provide guidance and feedback as the student works through problems

Career center

Learners who complete Reinforcement Learning from Human Feedback (RLHF) will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use machine learning and other techniques to extract insights from data. This course, Reinforcement Learning from Human Feedback, may be useful to Data Scientists who want to gain a deeper understanding of how reinforcement learning can be used to improve the performance of data-driven models.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers are responsible for developing, deploying, and maintaining machine learning models. This course, Reinforcement Learning from Human Feedback, may be useful to Machine Learning Engineers who want to gain a deeper understanding of how reinforcement learning can be used to improve the performance of machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Research Scientist

Research Scientists conduct research in a variety of fields, including machine learning, data science, and artificial intelligence. This course, Reinforcement Learning from Human Feedback, may be useful to Research Scientists who want to gain a deeper understanding of how reinforcement learning can be used to improve the performance of their research.

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Artificial Intelligence Engineer

Artificial Intelligence Engineers design and develop artificial intelligence systems. This course, Reinforcement Learning from Human Feedback, may be useful to Artificial Intelligence Engineers who want to gain a deeper understanding of how reinforcement learning can be used to improve the performance of artificial intelligence systems.

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Software Engineer

Software Engineers design, develop, and maintain software systems. This course, Reinforcement Learning from Human Feedback, may be useful to Software Engineers who want to gain a deeper understanding of how reinforcement learning can be used to improve the performance of software systems.

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Interaction Designer

Interaction Designers design and develop the interactions between users and software products. This course, Reinforcement Learning from Human Feedback, may be useful to Interaction Designers who want to gain a deeper understanding of how reinforcement learning can be used to improve the interactions between users and their products.

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Product Manager

Product Managers are responsible for developing and managing products. This course, Reinforcement Learning from Human Feedback, may be useful to Product Managers who want to gain a deeper understanding of how reinforcement learning can be used to improve the performance of their products.

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User Experience Designer

User Experience Designers design and develop user interfaces for software products. This course, Reinforcement Learning from Human Feedback, may be useful to User Experience Designers who want to gain a deeper understanding of how reinforcement learning can be used to improve the user experience of their products.

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Scrum Master

Scrum Masters are responsible for facilitating Scrum teams. This course, Reinforcement Learning from Human Feedback, may be useful to Scrum Masters who want to gain a deeper understanding of how reinforcement learning can be used to improve the performance of their Scrum teams.

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Business Analyst

Business Analysts analyze business processes and identify opportunities for improvement. This course, Reinforcement Learning from Human Feedback, may be useful to Business Analysts who want to gain a deeper understanding of how reinforcement learning can be used to improve the efficiency of their business processes.

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Data Analyst

Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course, Reinforcement Learning from Human Feedback, may be useful to Data Analysts who want to gain a deeper understanding of how reinforcement learning can be used to improve the accuracy of their data analysis.

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Technical Writer

Technical Writers write documentation for software products. This course, Reinforcement Learning from Human Feedback, may be useful to Technical Writers who want to gain a deeper understanding of how reinforcement learning can be used to improve the quality of their documentation.

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Agile Coach

Agile Coaches help organizations adopt and implement agile practices. This course, Reinforcement Learning from Human Feedback, may be useful to Agile Coaches who want to gain a deeper understanding of how reinforcement learning can be used to improve the adoption and implementation of agile practices within their organizations.

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Product Owner

Product Owners are responsible for defining and managing the product backlog. This course, Reinforcement Learning from Human Feedback, may be useful to Product Owners who want to gain a deeper understanding of how reinforcement learning can be used to improve the quality of their product backlog.

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Project Manager

Project Managers are responsible for planning, organizing, and executing projects. This course, Reinforcement Learning from Human Feedback, may be useful to Project Managers who want to gain a deeper understanding of how reinforcement learning can be used to improve the success of their projects.

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