Developing Applications with AI and AUTO-GPT
An intermediate-level course helping students gain technical expertise in development with AI technologies and Auto-GPT. The course also covers Langchain and its integration with AI technologies.
Prerequisites
- A basic appreciation of AI technology
Contents
Introduction to AI Development
- Review of AI and Machine Learning concepts
- The role of a developer in AI projects
- The AI development process
- Overview of AI development tools and libraries
Deep Dive into GPT Models
- Understanding transformer architectures
- The mechanics of GPT models
- The role of attention in GPT models
- Use-cases and applications of GPT models
Introduction to AUTO-GPT
- Understanding AUTO-GPT
- AUTO-GPT vs. traditional GPT models
- Building applications with AUTO-GPT
- Handling challenges and limitations of AUTO-GPT
Langchain in AI Development
- Introduction to Langchain Python library
- Integrating Langchain with GPT and AUTO-GPT models
- Use-cases and applications of Langchain
- Best practices when using Langchain
Practical AI Development
- Building a simple application using GPT and AUTO-GPT
- Exploring different use-cases: text generation, question answering, and more
- Debugging and optimizing your AI applications
- Ensuring the reliability and robustness of AI applications
Prompt Engineering for GPT and AUTO-GPT
- Understanding the importance of prompt engineering
- Techniques for effective prompt design
- Mitigating model biases through prompt engineering
- Practical exercises in prompt engineering
Introduction to AI Ethics and Fairness
- Understanding bias and fairness in AI
- Techniques for ensuring fairness in AI applications
- Ethical considerations in AI development
Deploying AI Applications
- Understanding the deployment process for AI applications
- Challenges in deploying AI applications
- Best practices for deployment and maintenance
