Generative AI Crash Course for Beginners
Learn the fundamentals of Generative AI and Large Language Models (LLMs) in this beginner-friendly bootcamp.
Duration: 3 Days
Hours: 6 Hours
Training Level: All Levels
About the Course:
This crash course provides an intensive introduction to Generative AI for beginners, covering 18 essential topics over 3 days. You’ll learn the basics of AI, prompt engineering, and how to build practical applications like chatbots, text and image generation tools, and more. The sessions will combine theory and practice, offering hands-on exercises to help you understand and apply the key concepts. By the end of the course, you’ll be equipped to start developing your own AI-powered applications and understand the principles behind using AI responsibly.
Course Objective:
- Understand the basics of Generative AI and LLMs
- Explore different AI models and their applications
- Learn prompt engineering fundamentals and advanced techniques
- Build various AI applications, including text, chat, image generation, and search apps
- Understand how to use AI responsibly and securely
- Learn the lifecycle management of AI applications and techniques like Retrieval Augmented Generation (RAG)
- Gain insights into integrating external applications, designing UX, and using low-code tools
Who is the Target Audience?
- Beginners are interested in learning about Generative AI and LLMs
- Developers and technologists are looking to enhance their skills in AI
- Product managers and UX designers interested in AI applications
- Anyone with a passion for exploring AI technologies and their applications
Basic Knowledge:
- Basic understanding of programming concepts (preferably Python)
- Interest in AI and machine learning concepts
Curriculum
Total Duration: 6 Hours
Setup the Development Environment
- Learn How to Setup Your Development Environment
Introduction to Generative AI and LLMs
- Learn to understand what Generative AI is and how Large Language Models (LLMs) work.
Exploring and comparing different LLMs
- Learn How to select the right model for your use case
Using Generative AI Responsibly
- Learn How to build Generative AI Applications responsibly
Understanding Prompt Engineering Fundamentals
- Learn Hands-on Prompt Engineering Best Practices
Creating Advanced Prompts
- Learn How to apply prompt engineering techniques that improve the outcome of your prompts.
Creating Advanced Prompts
- Learn How to apply prompt engineering techniques that improve the outcome of your prompts.
Building Text Generation Applications
- Build A text generation app using Azure OpenAI / OpenAI API
Building Chat Applications
- Build Techniques for efficiently building and integrating chat applications.
Building Search Apps Vector Databases
- Build A search application that uses Embeddings to search for data.
Building Image Generation Applications
- Build An image-generation application
Building Low Code AI Applications
- Build A Generative AI application using Low Code tools
Integrating External Applications with Function Calling
- Build What is the function calling and its use cases for applications
Designing UX for AI Applications
- Build What is the function calling and its use cases for applications
Designing UX for AI Applications
- Learn How to apply UX design principles when developing Generative AI Applications
Securing Your Generative AI Applications
- Learn The threats and risks to AI systems and methods to secure these systems.
The Generative AI Application Lifecycle
- Learn The tools and metrics to manage the LLM Lifecycle and LLMOps
Retrieval Augmented Generation (RAG) and Vector Databases
- Build An application using a RAG Framework to retrieve embeddings from Vector Databases
Open Source Models and Hugging Face
- Build An application using open-source models available on Hugging Face
AI Agents
- Build An application using an AI Agent Framework
Fine-Tuning LLMs
- Learn The what, why and how of fine-tuning LLMs