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Agentic AI GenAI · LLMs · Automation ✔ 30 Hour Programme

Agentic AI Professional
Programme

This program is designed for professionals who want to advance their careers in AI and Generative AI by learning how to design, build, and deploy Agentic AI systems — intelligent, goal-driven AI agents capable of reasoning, planning, and autonomous action. Format: Theory + Lab/Assignments per syllabus.

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Format
Theory + Lab/Assignments
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Certificate
Arich Certified
Enrol Now →
Course Code
AGAI
Internship syllabus overview
INT
AGAI-INT · Internship Syllabus
14 Modules
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📄 AGAI-INT — 30-Hour Internship Syllabus
L1
AGAI-INT
Agentic AI & Generative AI — Module Plan
01
AI & Generative AI Foundations (3 Hours)
▼
Introduction to Artificial Intelligence
Generative AI landscape
AI vs ML vs Deep Learning
LLM fundamentals
Real-world AI applications
02
Introduction to Agentic AI (3 Hours)
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What is Agentic AI
Autonomous agents & goal-driven systems
Agents, Tasks & Workflows
Agent ecosystem overview
03
Agent Architecture & Design (4 Hours)
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Agent architecture fundamentals
Symbolic reasoning systems
BDI (Belief–Desire–Intention) models
LLM-based agents
Memory and context management
04
Core Agent Capabilities (3 Hours)
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Perception → Planning → Action cycle
Tool usage & API interaction
Reasoning workflows
Autonomous execution strategies
05
Prompt Engineering for Agents (3 Hours)
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Prompt engineering fundamentals
Structured prompting techniques
Chain-of-Thought reasoning
ReAct framework concepts
06
Multi-Agent Systems (MAS) (3 Hours)
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Multi-agent collaboration
Role-based agent design
Supervisor & helper agents
Human–Agent collaboration
07
Intelligent Automation & Productivity (2 Hours)
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Workflow automation using AI agents
Research automation systems
Document & reporting automation
Productivity optimization using AI
08
Deployment Concepts for Agentic AI (2 Hours)
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Introduction to AI deployment
Cloud AI fundamentals
Containerization overview
Production considerations
09
Ethics, Safety & Responsible AI (2 Hours)
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AI ethics fundamentals
Alignment challenges
Responsible AI design
Human oversight principles
10
Final Project (3 Hours)
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Participants build a real-world Agentic AI solution such as:
AI Research Assistant
Workflow Automation Agent
Personal AI Assistant
Business Intelligence Agent
11
Revisiting Key Concepts (1 Hour)
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Concept recap
Architecture review
Best practices summary
12
Comprehensive Quiz & Assessment (1 Hour)
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Scenario-based evaluation
Knowledge validation
13
Project Presentations (1 Hour)
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Participant demos
Peer review
Instructor evaluation
14
Guidance on Next Steps (1 Hour)
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Career roadmap in AI & Agentic AI
Portfolio building
Certification guidance
Next learning paths (RAG, LLMOps, Multi-Agent AI)