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Full Stack Agentic AI and Generative AI with Python Bootcamp

Name: Full Stack Agentic AI and Generative AI with Python Bootcamp
Rating: 4.5 (29 reviews)

Learn Modern Full Stack Agentic AI & Generative AI and RAG with Python and Hands-on Projects

Created byLakshmana Rao Karrothu

Last updated 9/2026

English

English [Auto],

What you'll learn

Build a strong foundation in Python programming and learn to use essential libraries and frameworks for developing Generative AI and Agentic AI applications.
Learn to work with Large Language Models, prompt engineering, embeddings, vector databases, RAG, and AI APIs to create practical Generative AI solutions.
Design and build intelligent AI agents that can reason, use tools, access external data, execute tasks, collaborate with other agents, and automate complex wor
Develop and deploy end-to-end AI applications using Python, APIs, databases, backend technologies, and modern frontend integration through hands-on projects and

Course content

80 sections • 402 lectures • 101h 23m total length

Introduction6:32
Highlight the importance of removing pauses in video editing, and show how placing pauses at the end of a clip creates a tighter, smoother viewer experience.

Getting Started With VS Code10:36
Master efficient video editing by refining the a cut with trim to end of clip, snapping, and keyboard shortcuts like alt+left bracket and comma to remove pauses.
Python Basics-Syntax And Semantics20:17
master Final Cut Pro shortcuts like W, E, and Q to insert, append, and connect clips at the playhead or above the main storyline, leveraging a magnetic timeline.
Variables In Python18:55
Learn the marker technique to save time by planning B-roll and onscreen elements during the A-roll. Use in-scene markers to cue edits and streamline the filming and editing process.
Basics DataTypes In Python9:52
Shows how to add text overlays and titles in video editing, using fonts, lower thirds, sound effects, and keyboard shortcut to enhance narration with Ready Player One as an example.
Operators In Python16:16
Explore practical video editing techniques using videohive infographics builder to add and position lower thirds, titles, and markers, and adjust text using the video inspector with x and y coordinates.

Conditional Statements in Python21:03
Demonstrates adding images in Final Cut Pro ten, using slide transitions, adjusting timing and sound effects, and organizing media and b-roll for polished video storytelling.
Loops In Python28:02
Explore how to enhance video storytelling by applying Ken Burns effects to images, curating b-roll, and integrating concept art to convey a future, polluted cityscape with crowded slums.

Lists In Python37:07
Record your iPhone screen with go record, synchronize audio from the microphone with the camera, then import to Final Cut Pro for alignment, trimming, and glitch transitions.
Tuples In Python22:34
Discover how to create and customize video timestamps and on-screen bullet points using the Infographics Builder plugin, including markers, text alignment, timing, and asset workflows.
Dictionaries In Python38:18
Use Audition to remix a track for video, set a precise target duration, create cut points, and align the ending with markers and sound effects for a seamless finale.
Real World Use cases Of List9:50
Explore how to enhance video transitions with subtle sound effects, adjust music levels, and time endings for a polished viewing experience.

Getting Started With Functions24:21
Master retiming music in video projects by creating artificial cuts, fading overlaps, and aligning end beats to markers for a polished ending. Balance volume and vocal levels for clarity.
More Coding Examples With Functions28:03
Boost vocal levels with a limiter in Final Cut Pro, aiming for peaks around -4.5 dB, adjust gain carefully, and use a compressor and EQ presets for clear, distortion-free audio.
Lambda Function In Python9:44
Explore color grading and color correction with luts and custom luts, using adjustment layers and color curves to achieve teal and orange, subtle, cinematic looks.
Map Function In Python11:08
Export your final cut as a master file with h264 video and audio, preserving full 4k or 1080p, then upload to YouTube after backing up on an external hard drive.
Filter Functions In Python9:00

Classes And Objects In Python22:55
Single And Multiple Inheritance19:00
Polymorphism In OOPS19:08
Encapulation In OOPS22:12
Abstraction In OOPS9:08
Magic Methods In Python8:03
Operator Overloading In Python8:31
Custom Exception Handling7:05
Iterators In Python6:25
Generators In Python11:06
Fucntion Copy.Closures and Decorators21:15
Numpy In Python28:16
Pandas-DataFrame And Series29:09
Data Manipulation With Pandas And Numpy24:38
Reading Data From Various Data Source Using Pandas15:04
Logging Practical Implementation In Python14:37
Logging With Multiple Loggers4:40
Logging With A Real World Examples7:43
Introduction To Pydantic14:07
Pydantic Practical Implementation21:38

Getting Started With Langchain And Open AI11:08
Creating Virtual Environment7:12
Important Components Of LangChain13:09
Data Ingestion With Documents Loaders22:43
Recursive Character Text Splitter12:56
Character Text Splitter With Langchain3:53
HTML Header Text Splitter7:01
Recursive Json Text Splitter6:48
Introduction To OPENAI Embeddings22:20
Ollama Embeddings15:43
HuggingFace Embeddings10:20
Vector Stores-FAISS16:34
Vector Store And Retriever- Chroma DB9:32

Requirements

No Prerequisites

Description

Step into the future of AI development with the Full Stack Agentic AI & Generative AI with Python Bootcamp, a practical and comprehensive learning journey designed to help you build intelligent AI applications from the ground up.

This bootcamp takes you beyond basic chatbot development and simple API integration. You will learn how to combine Python programming, Large Language Models, Generative AI, Agentic AI, Retrieval-Augmented Generation, databases, APIs, automation, backend development, and modern web technologies to create complete AI-powered applications.

You will begin by strengthening your Python foundations and gradually move into the world of Generative AI and LLM-powered applications. You will understand how modern AI models work, how to communicate effectively with LLMs, and how to design reliable prompts and structured AI workflows.

The course then progresses into practical Agentic AI development. You will learn how AI agents can reason through tasks, use tools, interact with external systems, maintain context, make decisions, and execute multi-step workflows. You will explore agent architectures, tool calling, memory, workflow orchestration, and multi-agent concepts.

A major focus of the bootcamp is building knowledge-aware AI applications using RAG. You will learn how to process documents, create embeddings, work with vector databases, perform semantic search, retrieve relevant information, and connect retrieved knowledge with LLMs to build intelligent applications.

You will also learn how to develop full-stack AI solutions by connecting Python-based backend services with databases, APIs, and interactive user interfaces. Through practical projects, you will understand how individual AI components come together to form complete applications.

Throughout the bootcamp, the emphasis is on hands-on development rather than memorizing concepts. You will work on practical projects that help you understand AI application architecture, debugging, integration, deployment, and real-world development practices.

By the end of this course, you will have the skills to design, develop, integrate, and deploy modern Generative AI and Agentic AI applications using Python. You will also have practical project experience that can help you build an AI portfolio and prepare for opportunities in Generative AI, AI Engineering, Python development, and intelligent application development.

Who This Course Is For

Python developers who want to enter Generative AI and Agentic AI

Software developers interested in building AI-powered applications

Students and professionals looking to develop practical AI engineering skills

AI and ML enthusiasts who want to move from theory to real projects

Backend developers who want to integrate LLMs and AI agents into applications

Aspiring Generative AI and Agentic AI engineers

Anyone who wants to learn how modern AI applications are built from end to end

No matter whether you are starting your AI journey or already have programming experience, this bootcamp provides a structured path from Python fundamentals to advanced full-stack Agentic AI and Generative AI application development.

Who this course is for:

If you want to learn Agentic AI and Generative AI with Python Programming, This course is for you

Full Stack Agentic AI and Generative AI with Python Bootcamp

What you'll learn

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Course content

Introduction1 lecture • 7min

Basics of Python for Agentic AI and Generative AI5 lectures • 1hr 16min

Python Control Flow for Agentic AI and Generative AI2 lectures • 49min

Data Structures Using Python for Agentic AI and Generative AI4 lectures • 1hr 48min

Functions In Python for Agentic AI and Generative AI5 lectures • 1hr 22min

Importing, Creating Modules in Python for Agentic AI and Generative AI2 lectures • 35min

File Handling In Python for Agentic AI and Generative AI3 lectures • 51min

OOPS Classes And Objects for Agentic AI and Generative AI20 lectures • 5hr 15min

Langchain Hands On13 lectures • 2hr 39min

Getting Started With OpenAI And Ollama6 lectures • 1hr 21min

Requirements

Description

Who this course is for: