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CoursesAgentic Ai
Master In Agentic AI
Agentic Ai
Master In Agentic AI

Master Program in Applied & Agentic AI builds hands-on expertise in real-world AI and autonomous agents, covering design, deployment, and scalable solutions for modern industry needs.

5/5(4,890 Reviews)

Level

Advanced

Duration

8 weeks

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Capgemini Logo
Deloitte Logo
Genpact Logo
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Intel Logo
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Zoho Logo
Zelis Logo
Wipro Logo
Saint Gobain Logo
ONX Logo
Nava Logo
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About Master In Agentic AI

Master Program in Applied & Agentic AI by Tech Pratham is a career-focused, industry-aligned program designed to help learners master applied artificial intelligence and next-generation agentic AI systems. This program is built to meet the growing demand for professionals who can design, deploy, and scale intelligent AI solutions in real-world business environments.

The curriculum covers essential applied AI concepts, including machine learning, deep learning, large language models (LLMs), data-driven decision-making, and AI model deployment. In addition, the program offers in-depth training in agentic AI, focusing on autonomous agents, multi-agent systems, workflow orchestration, and AI-driven automation used in modern enterprises. Learners gain practical exposure to tools, frameworks, and architectures that are widely adopted across industries.

Training Plan

01

About trainer

Working professional who is carrying more then 10 years of industry experience.

02

Decks & Updated Content

Access to updated presentation decks shared during live training sessions.

03

e-Book

E-book provided by TechPratham. All rights reserved.

04

Assignments & MCQs

Module-wise assignments and MCQs provided for practice.

05

Video Recording

Daily Session would be recorded and shared to the candidate.

06

Projects

Live projects will be provided for hands-on practice.

07

Resume Building

Expert-guided resume building with industry-focused content support.

08

Interview Preparation

Comprehensive interview preparation with real-time scenario practice.

Master In Agentic AI Course Curriculum

Python for AI & Automation (Foundation Layer)

Python for AI & Automation (Foundation Layer) builds core Python skills to automate tasks and create a strong base for AI and machine learning development.

Module 1: Python Essentials for AI
 Python syntax, data types, control flow
 Functions, modules, virtual environments
 OOP concepts (important for agents)
Module 2: Python for Automation & AI
 File handling, APIs, JSON
 Web requests, REST API consumption
 Async programming basics
 Logging, exception handling
Module 3: AI-Ready Python Libraries
 NumPy, Pandas
 Requests, FastAPI (intro)
 LangChain utilities (preview)

Introduction to Agentic AI & LLM Ecosystem 

A foundational overview of how autonomous AI agents work with large language models to plan, reason, and execute tasks across modern AI systems.

What is Agentic AI?
Role of LangGraph, AutoGen, CrewAI in the ecosystem
OpenAI vs Azure OpenAI vs AWS Bedrock
Introduction to foundational concepts: Agents, Tasks, Graphs

 Basics of LangChain and LangGraph

An introductory overview of using LangChain and LangGraph to build, connect, and orchestrate intelligent, multi-step AI workflows.

LangChain recap: Chains, Tools, Memory
LangGraph architecture and why it matters
Installation, environment setup, and first LangGraph DAG

Exploring LangGraph Core Concepts 

A concise introduction to building stateful, multi-step AI workflows using LangGraph for agent orchestration and decision-making.

Nodes, Edges, State Machines
Understanding transitions and handlers
Building a simple agentic task flow

Python SDK and Node Configuration

 An overview of setting up the Python SDK and configuring nodes to build, connect, and manage scalable AI workflows efficiently.

Deep dive into LangGraph Python SDK
Defining nodes and reactive transitions
Testing individual components with unit test strategy

Multi-Agent Setup with LangGraph

A practical introduction to designing and orchestrating multiple AI agents that collaborate and share state using LangGraph.

Multi-agent interaction via graph state
Introducing dynamic task allocation
Conditional logic and loops in graphs

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Additional Program Highlights

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Resume Writing
Interview Preparation
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Who Should Take Master In Agentic AI

IT Professionals

Non-IT Career Switchers

Fresh Graduates

Job Roles For Master In Agentic AI

Agentic AI Engineer

AI Workflow Architect

Autonomous Systems Developer

Key Projects

Master In Agentic AI

Workday

WorkdayAutonomous HR AI Agent


Scenario: Agentic AI built to autonomously resolve HR queries by understanding intent, triggering workflows, updating records, and learning from feedback to enhance experience

Live Work:

  • Designed intent driven AI task flows
  • Automated HR actions via smart agents
  • Tuned AI responses using feedback loops
Outcome: Faster HR resolution with minimal human effort
Microsoft

MicrosoftSelf Acting IT Support AI


Scenario: Agentic AI solution enabling proactive IT support by predicting issues, automating fixes, orchestrating tools, and continuously optimizing service delivery.

Live Work:

  • Built AI agents for issue prediction
  • Automated incident resolution steps
  • Integrated tools for end to end actions
Outcome: Reduced downtime and improved IT efficiency
Salesforce

Salesforce Intelligent Sales AI Agent


Scenario: Agentic AI designed to manage sales operations by analyzing leads, executing actions, coordinating agents, and adapting strategies to maximize efficiency gains daily

Live Work:

  • Created AI agents for lead handling
  • Automated follow ups and task actions
  • Optimized sales flows using AI logic
Outcome: Higher conversion with optimized sales flow
UiPath

UiPath Autonomous Process AI Bot


Scenario: Agentic AI platform automating business processes by sensing events, making decisions, executing bots, and self optimizing workflows across systems seamlessly now.

Live Work:

  • Designed decision based AI agents
  • Integrated bots with agentic logic
  • Enabled self learning workflows
Outcome: Smarter automation with adaptive execution

Placement Process

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What Makes TechPratham Training Different?

Real-World Implementation
Live enterprise tenant access for 24/7 practice on real-world, enterprise-grade scenarios.
Restricted or simulation-based access that lacks real-world complexity.
Subject Matter Experts
Mentorship from certified professionals with 15+ years of global industry experience.
Generic instructors with no hands-on implementation background.
2026 Ready Curriculum
AI-driven curriculum with advanced platform integrations and real-world configurations.
Basic, outdated syllabus that misses key technical integrations.
Daily & Weekly assignments
Daily assignments and weekly assessments focused on concept reinforcement and continuous feedback.
Self-paced learning with no accountability or progress tracking.
End-to-End Lifecycle
Hands-on project testing and deployment with portfolio-ready real-world exposure.
Basic lab exercises without any deployment or testing practice.
Interview Readiness
Structured interview preparation including mock interviews, PD sessions, and alumni guidance.
Minimal support limited to a generic certificate of completion.
Placement Support
Guaranteed interview support through tie-ups with top MNCs and 1-on-1 mock interview sessions.
Basic career tips with no direct industry connections.
Training Support
24/7 technical doubt resolution and personalized mentoring support.
Limited mentor availability and no support after class hours.
Affordable Fees
Competitive fixed pricing with flexible payment options and transparent fee structure.
Inflated fees with hidden costs and low return on investment.
FAQ's
INTERVIEW Question's
ABOUT CERTIFICATE
CERTIFICATION DUMPS

Course FAQs

What is the difference between AI Agents and traditional AI models?

What are AI Agents?

What is Agentic AI?

How do AI Agents differ from traditional AI tools?

Can AI Agents be used in business?

Do I need programming skills to work with AI Agents?

Industry-Recognized Certification

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