The Complete Generative Ai Bootcamp

From Fundamentals to Expertise: Mastering Generative AI for the Future

What you'll learn

Master the foundations and key concepts of Generative AI, including models like GANs, VAEs, and Transformers.

Develop hands-on skills in creating, fine-tuning, and deploying Generative AI applications

Craft effective prompts and build generative agents for creative and technical tasks

Understand ethical practices and tools for responsible and scalable AI deployment

Requirements

To make the most of this course, learners should have a basic understanding of programming, preferably in Python, as it will be used extensively for hands-on exercises. Foundational knowledge of linear algebra, calculus, and probability will also be helpful for grasping AI concepts. While prior exposure to machine learning is not mandatory, it can provide a smoother learning experience. An eagerness to explore AI and emerging technologies is essential, along with the ability to install tools like Python, TensorFlow, or PyTorch.

Description

Welcome to the GenAI - The Complete Bootcamp by ArkaTalent Tech, designed to take you on an exciting journey through the rapidly evolving field of Generative AI. Whether you're a complete beginner or someone with basic knowledge of AI, this course is built to take you from the fundamentals to an advanced level of expertise.In this comprehensive bootcamp, you’ll learn everything you need to know about Generative AI, including the core principles, models, and applications. Starting with the basics of AI and Generative AI, we’ll explore key concepts like Neural Networks, GANs, VAEs, and Transformer Models, and how they form the foundation of AI systems like ChatGPT, DALL-E, and MidJourney. The course emphasizes both theoretical understanding and practical, hands-on experience, giving you the skills to create your own AI applications.You will dive into real-world use cases across industries such as healthcare, art, customer support, and entertainment, while also gaining insights into ethical considerations and the societal impact of AI. With interactive exercises, quizzes, and guided projects, you’ll not only learn how to build and deploy AI models but also how to fine-tune them for specific tasks.By the end of the bootcamp, you’ll be equipped to use cutting-edge tools like GPT, BERT, and TensorFlow, and have a solid grasp on deploying scalable, responsible Generative AI models. Prepare to unlock your potential and gain the skills needed to thrive in the world of tomorrow’s AI.

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Module 1: Foundations of Generative AI

Lecture 2 What is Generative AI?

Lecture 3 Generative AI vs Traditional AI

Lecture 4 Models related to GenAI

Section 3: Module 2: Applications and Real-World Use Cases

Lecture 5 Important Applications

Lecture 6 State-of-the-Art Trends

Section 4: Module 3: Neural Networks and Training Basics

Lecture 7 Introduction to Neural Networks

Lecture 8 Understanding Forward Propagation

Lecture 9 Understanding Backpropagation

Lecture 10 Forward and Backpropagation Together

Lecture 11 Hyperparameter Tuning

Lecture 12 Tensorflow Playgroud

Section 5: Module 4 : Generative Models

Lecture 13 Types of Generative Models

Lecture 14 Deep Dive: Autoregressive Models

Lecture 15 Deep Dive: Variational Autoencoders (VAEs)

Lecture 16 Deep Dive: Generative Adversarial Networks (GANs)

Lecture 17 Hands-on: Generating images with GANs.

Lecture 18 Hands-on: Exploring MidJourney and DALL-E

Section 6: Module 5 : Transformer Architectures

Lecture 19 Introduction to Transformer Architecture

Lecture 20 GPT and BERT: Transformer-Based Models

Lecture 21 Hands-On: Fine-tuning BERT for Text Classification

Lecture 22 Hands-On: Fine-tuning GPT for Text Generation

Section 7: Module 6: Large Language Models (LLMs)

Lecture 23 Understanding LLMs

Lecture 24 Overview of tokenization and embeddings.

Lecture 25 Prominent LLMs: GPT, BERT, PaLM, LLaMA, and More

Lecture 26 Using LLM APIs

Lecture 27 Fine-Tuning LLMs

Section 8: Module 7: Prompt Engineering and Applications

Lecture 28 Prompt Engineering

Lecture 29 Hands-on: Creative Prompting

Lecture 30 Introduction to Generative Agents

Lecture 31 How Memory, Planning, and Workflows Work Together

Lecture 32 Practical Session: Building Your Own Generative Agent

Section 9: Module 8: Advanced Concepts in Generative AI

Lecture 33 Embeddings

Lecture 34 Vector Databases

Lecture 35 Getting Embeddings, Vector Databases and Semantic Search Work Together

Lecture 36 Practical Session: Building a Semantic Search System

Lecture 37 Improvement and Future Applications

Lecture 38 LangChain

Lecture 39 Retrieval-Augmented Generation (RAG)

Lecture 40 LangChain Workflow: Orchestrating Complex AI Pipelines

Section 10: Module 9: Deployment and Scalability

Lecture 41 Deploying Generative Models

Lecture 42 Docker: Containerization for Generative AI

Lecture 43 Kubernetes: Orchestrating Generative AI at Scale

Lecture 44 Cloud Platforms: Hosting Generative AI Models

Lecture 45 Cloud Deployment Workflow

Lecture 46 Scaling for Production

Lecture 47 Cost Optimization Tips

Lecture 48 Best Practices for Production Scaling

Section 11: Module 10: Responsible Generative AI

Lecture 49 Ethical AI Practices

Lecture 50 Introduction to Explainable AI (XAI)

Lecture 51 SHAP

Lecture 52 LIME

Lecture 53 Use Cases and Benefits of Explainable AI

Lecture 54 Differential Privacy and Watermarking Generative Outputs

Lecture 55 Key Takeways & Good Luck !!

This course is tailored for anyone eager to explore the world of Generative AI, whether you're a complete beginner or have some basic knowledge of AI and programming. It's ideal for tech enthusiasts, students, professionals looking to upskill, or even hobbyists curious about the cutting-edge capabilities of AI. With a step-by-step approach, the course starts with foundational concepts and gradually builds toward advanced topics, empowering learners to master Generative AI techniques and tools by the end.