Generative AI

Introduction

Get started for FREE with Generative AI and Large Language Models with our comprehensive curricula. Perfect for beginners, with hands-on examples and practical applications.

Course Curriculum

Our comprehensive and FREE curriculum covers everything from basic concepts to practical applications. Divided into five major lessons, each focusing on crucial aspects of Generative AI. See all examples and relevant links in this GitHub repository

  • Lesson 1: Foundations of Generative AI and LLMs
  • Lesson 2: Prompt Engineering Mastery
  • Lesson 3: Running LLMs locally
  • Lesson 4: Introduction to APIs
  • Lesson 5: Building AI Applications

Custom training for your company

We are ready to deliver this and other training to your group. We can usually accommodate different requirements and are flexible with the number of seats. Reach out to us at contact@paiml.com

  • Bulk pricing available
  • Customizable content
  • Ready to start on your schedule

Why Choose This Course?

Beginner Friendly

No prior AI knowledge required. Start from the basics and progress to advanced concepts.

Hands-on Learning

Practice with real-world examples using GitHub Copilot, Qdrant, and OpenAI.

Practical Applications

Build actual AI applications using Azure OpenAI and implement RAG systems.

Understanding GenAI

Generative AI represents a breakthrough in artificial intelligence technology, operating through an interconnected multi-model processing system that transforms user inputs into sophisticated outputs. At its core, the technology leverages deep learning models and neural networks to process various types of content, including text prompts, images, and audio data. These advanced AI models work in harmony through a central processing engine, coordinating multiple specialized algorithms to generate high-quality, context-aware responses. Through intuitive application interfaces, users can easily access these powerful capabilities, making generative AI an increasingly essential tool for content creation, data analysis, and creative expression. The seamless integration of multiple AI models demonstrates the dynamic and evolving nature of modern artificial intelligence systems.