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.
Level
Advanced
Duration
8 weeks



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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.
Working professional who is carrying more then 10 years of industry experience.
Access to updated presentation decks shared during live training sessions.
E-book provided by TechPratham. All rights reserved.
Module-wise assignments and MCQs provided for practice.
Daily Session would be recorded and shared to the candidate.
Live projects will be provided for hands-on practice.
Expert-guided resume building with industry-focused content support.
Comprehensive interview preparation with real-time scenario practice.
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.
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.
Basics of LangChain and LangGraph
An introductory overview of using LangChain and LangGraph to build, connect, and orchestrate intelligent, multi-step AI workflows.
Exploring LangGraph Core Concepts
A concise introduction to building stateful, multi-step AI workflows using LangGraph for agent orchestration and decision-making.
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.
Multi-Agent Setup with LangGraph
A practical introduction to designing and orchestrating multiple AI agents that collaborate and share state using LangGraph.
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Scenario: Agentic AI built to autonomously resolve HR queries by understanding intent, triggering workflows, updating records, and learning from feedback to enhance experience
Scenario: Agentic AI solution enabling proactive IT support by predicting issues, automating fixes, orchestrating tools, and continuously optimizing service delivery.
Scenario: Agentic AI designed to manage sales operations by analyzing leads, executing actions, coordinating agents, and adapting strategies to maximize efficiency gains daily
Scenario: Agentic AI platform automating business processes by sensing events, making decisions, executing bots, and self optimizing workflows across systems seamlessly now.

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