ChatGPT Prompt Engineering for Developers: A short course from OpenAI and DeepLearningAI

Course Feature
  • Cost
    Free
  • Provider
    Youtube
  • Certificate
    No Information
  • Language
    English
  • Start Date
    2023-04-27
  • Learners
    No Information
  • Duration
    No Information
  • Instructor
    DeepLearningAI
Next Course
2.5
88,324 Ratings
ChatGPT Prompt Engineering for Developers is a free course from OpenAI and DeepLearningAI that teaches developers how to use large language models (LLMs) to quickly build powerful applications. In this course, taught by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI), you will learn how to use the OpenAI API to build capabilities that innovate and create value, as well as two key principles for writing effective prompts, how to systematically engineer good prompts, and how to build a custom chatbot. With only a basic understanding of Python, you can learn to use LLMs for summarizing, inferring, transforming text, and expanding. Get hands-on experience with prompt engineering and take advantage of the revolutionary new capabilities of generative AI.
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Course Overview

❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 18th, 2023]

ChatGPT Prompt Engineering for Developers is a short course from OpenAI and DeepLearningAI that teaches developers how to use a large language model (LLM) to quickly build new and powerful applications. In this course, taught by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI), participants will learn how LLMs work, best practices for prompt engineering, and how to use LLM APIs in applications for a variety of tasks, such as summarizing, inferring, transforming text, and expanding. Participants will also learn two key principles for writing effective prompts, how to systematically engineer good prompts, and how to build a custom chatbot. All concepts are illustrated with numerous examples, which can be explored in a Jupyter notebook environment. This course is beginner-friendly and requires only a basic understanding of Python. It is also suitable for advanced machine learning engineers wanting to approach the cutting-edge of prompt engineering and use LLMs.

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Pros & Cons
  • Practical and high-quality materials
  • Efficient and structured understanding
  • Lack of eye contact in the video
  • Limited scope of applications
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