A Complete Professional Certification Course

AI FOR PROFESSIONALS: THE GENERATIVE & AGENTIC AI STACK

From data to intelligent actions. The complete architect's guide to the autonomous enterprise using Artificial Intelligence.

Apply Now Course Fees: 10,000 Botswana Pula

Introduction

Launch your career in the cutting-edge world of Artificial Intelligence with our intensive "AI for Professionals: The Generative & Agentic AI Stack" certification. Designed for students and industry professionals, this 4-month weekend program delivers 100 hours of comprehensive online and classroom training. You will master the complete AI pipeline, progressing from core Python and NLP to building advanced RAG applications and autonomous Multi-Agent systems. Through practical capstone projects like creating "Smart Enterprise Bots" and autonomous analysts, you will gain the hands-on experience needed to thrive in the IT industry. Join MITU Skillologies to bridge the gap between theory and real-world deployment with the industry's most in-demand Agentic AI skills.

Why to Enrol?

This course offers a direct pathway into the IT industry by mastering the most in-demand skills: Generative AI, RAG, and Agentic systems.

  • Unlike theoretical programs, you will build a job-ready portfolio through five robust projects, such as creating autonomous business analysts and enterprise bots.
  • The curriculum is specifically designed for career transition, featuring dedicated modules on resume building and mock interviews to ensure you are market-ready.
  • With a flexible weekend schedule, you gain expert-level proficiency in cutting-edge tools like LangChain and Docker without disrupting your current commitments.

Program Highlights

Our course is best suited for professionals looking to change their current domain and start a new career in Artificial Intelligence.

  • 100% Practical Based Training
  • Case Studies and Videos
  • Weekly Assignments
  • Daily Activity Based
  • 6 Months Project Internship at MITU Research, AI Company
  • Get 2 Course Completion Certificate
  • Assistance in Global Certification
  • Opt for Multiple Certification
  • 100% Job Assistence
  • Special Assistence for Job Changers and people having gap

Prerequisites

  • Basic Coding Knowledge: Familiarity with variables and logic to support the Python refresher.
  • Math Fundamentals: Basic algebra and statistics concepts for understanding data manipulation and embeddings.
  • File Management: Proficiency in handling files and data formats like CSV and JSON.
  • Web Basics: Understanding how the web works to effectively use REST APIs and requests.
  • System Access: A personal computer capable of installing software like Python and Docker.

Scheduling

  • Timings: 6 Hrs per Week (Saturday and Sunday). Probable Timings: 10.00 am to 01.00 pm or 02.00 pm to 05.00 pm.
  • Weekly Assignments: After every weekend session you need to solve assignments until next week.
  • Final Exam: A duration of 15 days, will be given after completion of Course. The Final exam will be a conducted once, in case of Failure; exam can be reappeared after another 1 month.
  • Opportunities: As first opportunity before passing exams, you will deployed on a well monitored Live Project.

The Learning Journey

1
Build the Foundation: You will start by mastering the essential Python stack and API integrations to establish a robust technical base for AI development.
2
Master Language Models: Next, you advance to the modern NLP stack, learning to fine-tune Transformer models like BERT for intelligent text classification.
3
Unlock Generative AI: You then dive into the core of GenAI, mastering RAG and vector databases to connect LLMs securely with private enterprise data.
4
Engineer Autonomy: Moving to the agentic paradigm, you will build autonomous agents and multi-agent teams capable of planning and executing complex workflows.
5
Deploy and Launch: Your journey concludes by deploying your applications to the cloud and refining your portfolio with a capstone project to become job-ready.

Program Modules

A structured breakdown of what you will learn and build throughout the course.

Module 1: The AI Professional's Toolkit (The Foundation)

Objective: Achieve fluency in the core Python stack and API-first principles essential for building and integrating modern AI systems.

  • Core Python (Practical Refresher): Data Structures (deep dive into Dictionaries and Lists) and Functions & OOP Basics (reusable functions and classes).
  • Essential AI & Data Libraries: Pandas (DataFrames, reading/writing CSV/JSON, data cleaning) and NumPy (Numerical computing).
  • The API & Data Bridge: Understanding JSON, Consuming REST APIs (requests library), and Environment Variables (securely managing API keys).
  • Project 1: Automated Data Aggregation Script

Module 2: The Modern NLP Stack (The Language Engine)

Objective: Master the techniques to turn unstructured text into data, moving from classic methods to the transformer models that power all modern GenAI.

  • Text Preprocessing (The Basics): Techniques (Tokenization, Stop-Word Removal, Lemmatization) and Libraries (spaCy or NLTK).
  • Text Vectorization: Classic (TF-IDF) and Modern (Word Embeddings like Word2Vec and Sentence Embeddings).
  • The Transformer Era: Hugging Face transformers Library, Core Concepts (BERT vs. GPT), and fine-tuning a pre-trained model on a custom dataset.
  • Project 2: Automated Support Ticket Classifier

Module 3: Generative AI & RAG (The Knowledge Core)

Objective: Master the most in-demand generative AI skills: prompt engineering and building systems that connect LLMs to private data.

  • Large Language Models (LLMs): Prompt Engineering (Zero-shot, One-shot, Few-shot) and Designing Prompts for business tasks (summarization, extraction, classification, marketing copy).
  • The RAG Stack: Vector Databases (ChromaDB or FAISS), Application Frameworks (LangChain), and Workflow (Connecting Gemini API or OpenAI's API to a private knowledge base).
  • Project 3: "Chat with Your Enterprise Data" (RAG Application)

Module 4: The Agentic Paradigm (The Action Layer)

Objective: Build autonomous AI agents that can reason, plan, and use tools to interact with data and systems to accomplish goals.

  • Understanding the Agentic Paradigm: Core Concepts (Autonomy, goal-oriented behavior, planning) and Tool Usage (giving agents tools like calculators or APIs).
  • The Model Context Protocol (MCP): Understanding MCP as the open standard for connecting AI models to external data securely, Client-Server Architecture, and Building an MCP Server.
  • Building Agents with LangChain: Agent Architectures (loops and decision-making) and Defining Custom Tools (Python functions).
  • Practical Agents for Business Automation: CSV Agent (analyze business data), SQL Agent (query enterprise databases), and API Agent (interact with live web services).
  • Project 4: Autonomous Business Analyst Agent

Module 5: Multi-Agent Systems (The Collaborative Team)

Objective: Design and orchestrate collaborative AI teams where multiple, specialized agents work together to solve complex problems.

  • Multi-Agent Concepts: Collaborative problem-solving and Agent Roles (Planner, Researcher, Code Executor, Critic).
  • Frameworks for Orchestration: High-level understanding of AutoGen or LangGraph to manage agent-to-agent communication and state.
  • Applications: Process Automation (generating reports, writing/testing code) and Automated Research (web browsing and information synthesis).
  • Project 5: Automated Research & Report Writing Team

Module 6: Capstone, Deployment & Career Prep (The Job)

Objective: Package your advanced AI skills into a single, impressive project and prepare for the job market.

  • Capstone Project (Choose One): Option 1: The "Smart Enterprise Bot" | Option 2: The "Email Automation Agent".
  • Model Deployment: API Building (FastAPI or Flask), Containerization (Docker), and Cloud Deployment (Streamlit Cloud, Hugging Face Spaces).
  • Career Prep: GitHub Portfolio structuring, Resume Building highlighting LangChain/RAG/Agents, and Technical Mock Interviews for GenAI.

Know Your Trainers

They will be for you...

Aditya Thakare

Aditya is a dedicated researcher, trainer, and avid open-source enthusiast. With a background in engineering from Pune University, he honored his skills further by completing a PG Diploma in Artificial Intelligence from ACTS, CDAC, Pune.

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Rahul Temkar

Rahul is AI engineer and Data Scientist, experienced in Machine Learning, NLP and Generative to solve real world problems. With a background in engineering from Pune University. He is working in Generative and Agentic AI from 5 years for research and development.

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MITU Skillologies Central Office

Address

208, Adi Prime, Moshi, Pune, Maharashtra, INDIA 411070.

Phone

996 016 3010
758 859 4665

Digital

contact@mitu.co.in
https://mitu.co.in