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Catalyze AI:From Python to GenAI & Agentic AI with FastAPI

Program Details

Hands-on, Project-Driven

9 Months

Online/offline

Beginer/Intermediate

Catalyze AI is a comprehensive, project-driven program that takes you from Python fundamentals to building scalable AI-powered backend systems and multi-agent applications. You will learn how modern AI products are designed end-to-end — from APIs and databases to RAG pipelines and agentic workflows using tools like FastAPI, LangChain, LangGraph, and CrewAI.

This program is designed for developers who want to go beyond notebooks and build production-ready AI applications

Skills Covered:

  • Python Programming

  • Backend Development

  • Frontend Development

  • Database Design

  • API Integration

  • Large Language Models

  • Retrieval Augmented Generation

  • Prompt Engineering

  • Agentic AI Systems

  • Vector Databases

  • Multi-Agent Architectures

  • Git & Version Control

Career Outcome:

GENAI ENGINEER

Design, build, and deploy advanced AI models—primarily Large Language Models (LLMs) and Generative Adversarial Networks (GANs) transforming research findings into scalable, production-ready applications.

AI RESEARCH ENGINEER

 They are responsible for advancing state-of-the-art AI systems, conducting experiments, and transforming research findings into scalable, production-ready applications.

AI BACKEND DEVELOPER

Designing API backends, preprocessing data for AI models, building server-side logic, and integrating AI models into applications

Python-React Full Stack Developer

Designing, developing, and maintaining both the front-end (user interface) with React.js and the back-end (server-side logic and databases) with Python.

Backend Developer - Python

Builds and maintains the server-side logic, databases, and API integrations that power web application functionality. They write clean, secure, and scalable Python code using frameworks like Django or FastAPI to connect user-facing frontend elements to data storage solutions.

Frontend Developer - React

Developing reusable components, managing application state, integrating APIs, optimizing performance for speed, and collaborating with designers/backend teams to translate UI/UX designs into high-quality code.

Backend Engineer

 Builds and maintains the server-side logic, databases, and APIs that power web applications, ensuring high performance, scalability, and security

Program Outline:

Curriculam Road map

Epic - 1
Project Planning & Design

 

  • Understanding AI product architecture

     

  • Designing scalable backend systems

     

  • API-first development approach

     

  • Database schema design fundamentals

     

  • System design for AI-powered applications

     

  • Introduction to Agile & structured development workflow
Epic - 2
Web Development Fundamentals
  • How the web works (HTTP, REST, APIs)

     

  • Client-server architecture

     

  • JSON & data exchange formats

     

  • Introduction to API testing tools

     

  • Understanding authentication flows

     

Epic - 3
Frontend Development (React)
  • Introduction to React fundamentals

     

  • Components, props, and state

     

  • Calling backend APIs

     

  • Handling forms and authentication

     

  • Connecting React UI to FastAPI backend

     

  • Building simple AI-powered dashboards
Epic - 4
Python Fundamentals
  • Python Basics & Syntax

     

  • Control Flow & Loops

     

  • Functions & Modular Code

     

  • Python Collections & Comprehensions

     

  • Advanced Python Concepts

     

  • Async programming fundamentals

     

  • Database integration basics
Epic - 5
PostgreSQL
  • Database fundamentals

     

  • Working with PostgreSQL

     

  • SQL queries & joins

     

  • Database schema design

     

  • ORM with SQLAlchemy

     

  • Async database operations

     

  • Managing migrations

     

Epic - 6
Backend Development
  • Introduction to FastAPI

     

  • REST API development

     

  • Pydantic models & validation

     

  • Authentication & Authorization (JWT-based)

     

  • Error handling & middleware

     

  • Async API development

     

  • Production-ready backend structure

     

Epic - 7
Generative AI Basics
  • Introduction to Generative AI

     

  • Large Language Model landscape (OpenAI, Gemini, open-source models)

     

  • How LLMs work (tokens, embeddings, transformers)

     

  • Prompt Engineering techniques

     

  • API-based LLM integration

     

  • Using embeddings for semantic search
Epic - 8
Advanced GenAI – Multi-Agent Systems & AI Applications

Foundations of Agentic AI

  • What are AI agents?
  • Tool-using agents
  • Multi-agent system architecture

     

Embeddings & Vector Databases

  • Vector search fundamentals
  • Working with ChromaDB
  • Working with Qdrant
  • Semantic search pipelines

     

Retrieval Augmented Generation (RAG)

  • Building RAG systems
  • Chunking strategies
  • Hybrid retrieval
  • Memory & context management

     

LangChain & LangGraph

  • Building tool-using AI with LangChain
  • Designing stateful workflows with LangGraph
  • Agent memory & multi-step reasoning

     

CrewAI & Collaborative Agents

  • Building collaborative AI systems using CrewAI
  • Role-based agents
  • Task delegation & coordination

AI Application Layer

  • Building UI with Streamlit
  • Deploying multi-agent applications
  • Logging, monitoring & evaluation
Capstone Project
Multi-Agent GenAI System using FastAPI

You will build a production-ready multi-agent AI system that includes:

  • FastAPI backend
  • PostgreSQL database
  • RAG pipeline
  • Vector database integration
  • Multi-agent orchestration
  • AI-powered API endpoints
  • Frontend dashboard

Tools Covered:

Python Streamline Icon: https://streamlinehq.com
Chroma Streamline Icon: https://streamlinehq.com
Open Ai Logo Thin Streamline Icon: https://streamlinehq.com
Visual Studio Streamline Icon: https://streamlinehq.com
Google Gemini Streamline Icon: https://streamlinehq.com
Langchain Streamline Icon: https://streamlinehq.com LangChain
Trello Streamline Icon: https://streamlinehq.com
LangGraph
Streamlit Streamline Icon: https://streamlinehq.com
Git Streamline Icon: https://streamlinehq.com
Postgresql Streamline Icon: https://streamlinehq.com

TECH STACK YOU’LL MASTER

  • PROGRAMMING LANGUAGE:

    Python

  • AI FRAMEWORKS & CONCEPTS

    LANGCHAIN
    LANGGRAPH
    RAG (RETRIEVAL-AUGMENTED GENERATION)

  • DATABASES

    POSTGRESQL
    VECTOR DBS (CHROMADB, QDRANT)

  • TOOLS & PROJECT MANAGEMENT

    GIT
    TRELLO
    SCRUM (AGILE METHODOLOGY – SPRINTS, STAND-UPS, SPRINT PLANNING, RETROSPECTIVES)

Ready to Accelerate Your Career

Join the next cohort of Catalyze AI and transform from a coder to an AI Architect.

Catalyze AI: From Python to GenAI 9month pgm form

Congratulations!

Your Journey To Become A Tier-1 Software Engineer Starts Here

Contact Us : +91 88934 99100

We’re honored to be part of your journey. Your details are safe and will only be used to enhance your learning experience.

Congratulations!

Your Journey To Become A Tier-1 Software Engineer Starts Here

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We’re honored to be part of your journey. Your details are safe and will only be used to enhance your learning experience.

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