• Strong understanding of AI and machine learning concepts
  • Proficiency in Python programming
  • Familiarity with natural language processing (NLP) techniques and tools is recommended but not mandatory

Skills Gained

  • Understand the principles and applications of large language models like ChatGPT in building AI-driven applications
  • Select and integrate large language models into Python applications using APIs
  • Design and refine prompts for AI-generated content tailored to specific use cases
  • Optimize AI-driven applications for performance, content safety, and fairness
  • Develop practical, real-world applications using large language models like ChatGPT

Who Can Benefit?

Python developers, software engineers, AI/ML engineers, and professionals interested in building applications using large language models like ChatGPT

    Outline for Building Applications with Large Language Models Training

    Day 1

    Module 1: Introduction to Large Language Models and Python Integration

    • Overview of large language models (e.g., GPT-3, ChatGPT)
    • Principles of integrating large language models into Python applications
    • Introduction to available APIs and libraries for working with large language models

    Module 2: Model Selection and API Integration

    • Criteria for selecting appropriate models and architectures for specific use cases
    • Best practices for API integration and handling rate limits
    • Hands-on exercise: Integrating ChatGPT or a similar large language model into a Python application

    Module 3: Prompt Engineering for AI-Driven Applications

    • Principles of prompt design for AI-generated content
    • Techniques for creating and refining prompts for various use cases
    • Hands-on exercise: Designing and refining prompts for a specific AI-driven application

    Day 2

    Module 4: Optimizing AI-Driven Applications for Performance and Safety

    • Techniques for improving AI-generated content quality, relevance, and novelty
    • Ensuring content safety and adherence to ethical guidelines
    • Hands-on exercise: Optimizing an AI-driven application for performance and safety

    Module 5: Addressing Biases and Fairness in AI-Driven Applications

    • Identifying and mitigating biases in AI-generated content
    • Best practices for promoting fairness and inclusivity in AI-driven applications
    • Hands-on exercise: Evaluating and improving an AI-driven application for fairness

    Module 6: Capstone Project

    • Participants will apply the concepts and techniques learned throughout the course to build a custom AI-driven application using a large language model like ChatGPT
    • Presentation and discussion of capstone projects

    Throughout the course, participants will engage in hands-on exercises, case studies, and group discussions to reinforce learning and encourage collaboration among peers. The capstone project at the end of the course will provide an opportunity for participants to showcase their skills by developing a custom AI-driven application using a large language.