Zero To Generative Ai Application Development Mastery

Zero To Generative Ai Application Development Mastery
Published 5/2025
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz

Master GenAI and Large Language Models from Scratch with Step by Step approach and Practical Hands-on based learning

What you’ll learn

Understand the Fundamentals of Generative AI

Set Up and Configure a Generative AI Development Environment

Explore and Utilize Pre-trained Generative Models

Integrate Generative AI Capabilities into Real-world Applications

Understand about Large Language Models

Run Large Language Models locally or on servers

You will get learning materials

You will get the source code

Requirements

Basics of Python Programming Language

Description

Overview

Lecture 2 What is Machine Learning

Lecture 3 Relationship between AL ML DL LLM

Lecture 4 Supervised and Unsupervised Learning

Lecture 5 Reinforcement learning and LLM

Section 2: Fundamentals of Generative AI and Large Language Models

Lecture 6 What is Generative AI

Lecture 7 What is Large Language Model

Lecture 8 Different types of LLMs

Lecture 9 Parameters , Tokens, Context window in LLMs

Lecture 10 Chunks in LLM

Lecture 11 Embeddings in LLM

Section 3: Environment Setup and Popular GenAI Assitants

Lecture 12 Python local development environment setup

Lecture 13 What is LLM and ChatGPT with Practical Handson

Lecture 14 DeepSeek, Google Gemini, Claude, Grok

Lecture 15 Different ways to Interact with any LLM models

Section 4: Using LLMs from Custom Application via API and SDK

Lecture 16 Exploring OpenAI Platform for API Key and Docs

Lecture 17 Calling OpenAI API via Python Code Practical Handson

Lecture 18 Calling Google Gemini API via Python Code Practical Handson

Lecture 19 Calling DeepSeek API via Python Code Practical Handson

Section 5: Hosted Options for LLMs and their Pricing

Lecture 20 Hosting options for LLM models

Lecture 21 Hosting LLAMA models on Cloud and calling it via Code

Lecture 22 Using cloud hosted LLM Model for text to speech application

Lecture 23 Significance of Temparature parameter in LLM

Lecture 24 Using cloud hosted LLM for OCR and Vision capability

Section 6: Running LLMs on Local Computer

Lecture 25 How to run LLM on Local Computer

Lecture 26 Installing LLM Model on Local CPU based computer

Lecture 27 Calling locally installed LLM models from code

Section 7: Fullstack App Development with multiple LLMs

Lecture 28 Real world fullstack LLM applications