Generative AI with Python
Published 7/2025
Duration: 9h 41m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 3.90 GB
Genre: eLearning | Language: English
LLMs, Vector DBs, RAG, Agentic Systems, and more
What you'll learn
- Go beyond basic chatbots and learn to harness the intelligence of Large Language Models (LLMs) using Python.
- Discover how to create and leverage Vector Databases to store and efficiently retrieve information for your AI applications.
- Learn the cutting-edge technique that allows your AI to answer complex questions using your own data sources, making it smarter and more accurate.
- Explore the fascinating world of Agentic Systems and build autonomous AI agents that can perform tasks, make decisions, and interact with their environment.
- Get hands-on experience building practical projects that showcase the power and versatility of generative AI.
- Understand the fundamental concepts behind generative AI and gain the practical Python skills to bring your ideas to life.
- Acquire a deep understanding of the core technologies driving the next generation of intelligent applications.
Requirements
- Basic Python knowledge is required - you should know about basic data types, how to implement loops, or how to write functions.
Description
Unlock the transformative power of Generative AI with Python!This comprehensive course equips you with the essential knowledge and practical Python skills to master the core technologies driving this revolution, enabling you to build intelligent applications that understand, generate, and interact with language remarkably.
You'll delve into the fundamentals of Large Language Models (LLMs) and the crucial role of Vector Databases for efficient information retrieval. Discover the power of Retrieval-Augmented Generation (RAG), which allows your AI to answer complex questions using your own data, making it smarter and more contextually aware.
Furthermore, you'll explore the exciting domain of Agentic Systems, learning how to design and build autonomous AI agents capable of performing tasks and making decisions.
In my course I will teach you:
Large-Language Models
Classical NLP vs. LLM
Narrow AI Achievements
Model Performance and Achievements
Model Training Process
Model Improvement Options
Model Providers
Model Benchmarking
Interaction with LLMs
Message Types
LLM Parameters
Local Use of Models
Large Multimodal Models
Tokenization
Reasoning Models
Small Language Models
JailBreaking
Working with Chains
Parallel Chains, Router Chains, .
Vector Databases
Data Ingestion Pipeline
Data source and data loading
data chunking
embeddings
data storage
data querying
Retrieval-Augmented Generation
Baseline RAG
Context Enrichment
Corrective RAG
Hybrid RAG
Query Expansion
Speculative RAG
Agentic RAG
Agentic Systems
crewAI
Google ADK
OpenAI Agents SDK
AG2
Agent Interactions
MCP
ACP
A2A
Who this course is for:
- Python Programmers who want to expand their knowledge into the rapidly growing field of artificial intelligence and generative models.
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