Description

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 Objectives

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.

Target Audience

Beginners interested in learning about Generative AI and LLMs.

Developers and technologists 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 Understanding

Basic understanding of programming concepts (preferably Python).

Interest in AI and machine learning concepts.

Course Content

No sessions available.

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Fremont, CA 94539, USA

Generative AI Crash Course for Beginners

Session 1: Setup the Development Environment

  1. Learn How to Setup Your Development Environment

Session 2: Introduction to Generative AI and LLMs

  1. Learn Understanding what Generative AI is and how Large Language Models (LLMs) work.

Session 3: Exploring and comparing different LLMs

  1. Learn How to select the right model for your use case

Session 4: Using Generative AI Responsibly

  1. Learn How to build Generative AI Applications responsibly

Session 5: Understanding Prompt Engineering Fundamentals

  1. Learn Hands-on Prompt Engineering Best Practices

Session 6: Creating Advanced Prompts

  1. Learn How to apply prompt engineering techniques that improve the outcome of your prompts.

Session 7: Creating Advanced Prompts

  1. Learn How to apply prompt engineering techniques that improve the outcome of your prompts.

Session 8: Building Text Generation Applications

  1. Build A text generation app using Azure OpenAI / OpenAI API

Session 9: Building Chat Applications

  1. Build Techniques for efficiently building and integrating chat applications.

Session 10: Building Search Apps Vector Databases

  1. Build A search application that uses Embeddings to search for data.

Session 11: Building Image Generation Applications

  1. Build A image generation application

Session 12: Building Low Code AI Applications

  1. Build A Generative AI application using Low Code tools

Session 13: Integrating External Applications with Function Calling

  1. Build What is function calling and its use cases for applications

Session 14: Designing UX for AI Applications

  1. Build What is function calling and its use cases for applications

Session 15: Designing UX for AI Applications

  1. Learn How to apply UX design principles when developing Generative AI Applications

Session 16: Securing Your Generative AI Applications

  1. Learn The threats and risks to AI systems and methods to secure these systems.

Session 17: The Generative AI Application Lifecycle

  1. Learn The tools and metrics to manage the LLM Lifecycle and LLMOps

Session 18: Retrieval Augmented Generation (RAG) and Vector Databases

  1. Build An application using a RAG Framework to retrieve embeddings from a Vector Databases

Session 19: Open Source Models and Hugging Face

  1. Build An application using open source models available on Hugging Face

Session 20: AI Agents

  1. Build An application using an AI Agent Framework

Session 21: Fine-Tuning LLMs

  1. Learn The what, why and how of fine-tuning LLMs

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