Agentic AI Skills Curriculum for IT Professionals – DreamsPlus
Build Autonomous AI Systems That Perceive, Reason, Plan & Act
DreamsPlus offers an industry-aligned Agentic AI Training in Chennai designed to meet the rapidly growing demand for autonomous, goal-driven AI systems. This program focuses on building Agentic AI capabilities—systems that can independently reason, plan, collaborate, and take actions using tools and APIs.
This Agentic AI course in Chennai is tailored specifically for existing IT professionals across multiple roles, enabling them to design, deploy, and scale enterprise-grade agentic AI solutions.
Why Agentic AI Training Is Demand Today
Modern enterprises are rapidly adopting autonomous AI agent systems to automate workflows, decision-making, and operations. Unlike basic AI models, Agentic AI systems can think, reason, collaborate, and execute tasks across multiple tools and platforms.
This Agentic AI training for IT professionals prepares you to design, deploy, and manage intelligent agents used in:
AI automation platforms
Enterprise AI solutions
Conversational AI systems
Multi-agent orchestration frameworks
Autonomous business process automation
Why Choose DreamsPlus for an Agentic AI Course in Chennai?
- Trusted AI training institute in Chennai
- Industry-aligned curriculum
- Enterprise-level projects
- Expert trainers
- Career-focused learning paths
Agentic AI Course Curriculum
What You'll Learn in Workshop
Module 1: Agentic AI Fundamentals – 16 Hours
Learning Objectives
- Understand agent architectures: ReAct, AutoGPT, BabyAGI
- Differentiate traditional AI, Generative AI, and Agentic AI systems
- Grasp multi-agent systems and orchestration patterns
Topics Covered
- What makes AI agentic: autonomy, goal-orientation, tool usage
- Agent reasoning frameworks: Chain-of-Thought, Tree-of-Thought, ReAct
- Memory systems: short-term, long-term, episodic
- Tool integration and function calling
- Agent evaluation, alignment, and safety considerations
Hands-On Project
Build a task-planning autonomous agent using LangChain or AutoGen
Module 2: LLM Operations Essentials – 12 Hours
Topics Covered
- Prompt engineering for agentic behavior
- Context window management and retrieval strategies
- Model selection: GPT-4, Claude, Gemini, open-source models
- API usage, rate limiting, and cost optimization
- Error handling and fallback strategies
Lab
Implement prompt templates and context management pipelines for agent workflows
Module 3: RAG & Knowledge Systems – 12 Hours
Topics Covered
- Vector databases: Pinecone, Weaviate, Chroma
- Embedding models and semantic search
- Chunking strategies and metadata management
- Hybrid search approaches
- Knowledge graph integration
Lab
Build a RAG system that an agent can dynamically query
Track 1: Software Engineers / Developers – 80 Hours
Module 4: Agent Development Frameworks – 24 Hours
Skills Covered
- LangChain agents and chains
- AutoGen multi-agent conversations
- CrewAI for role-based agents
- LlamaIndex for data agents
- Semantic Kernel for enterprise integration
Projects
- Multi-step research agent with tool usage
- Code generation and debugging agent
- Customer service agent with escalation logic
Module 5: Tool Integration & APIs – 16 Hours
Skills Covered
- Function calling and tool schema design
- API wrapper development
- Browser automation (Playwright, Selenium)
- Database query generation
- Third-party integrations (Slack, GitHub, Jira)
Project
Build an agent that automates developer workflows across multiple tools
Module 6: Agent Testing & Reliability – 16 Hours
Skills Covered
- Unit testing for non-deterministic systems
- Evaluation frameworks: LangSmith, Phoenix
- Human-in-the-loop patterns
- Guardrails and output validation
- Observability and logging
Project
Implement a comprehensive testing suite for an agentic application
Module 7: Production Deployment – 24 Hours
Skills Covered
- Containerization for agent systems
- Streaming responses and async patterns
- State management and persistence
- Scaling agent workloads
- Monitoring and alerting
Capstone
Deploy a production-ready agentic application with monitoring
Track 2: Data Engineers – 70 Hours
Module 4: Data Pipeline Agents – 20 Hours
Skills Covered
- Automated data quality agents
- Schema inference and transformation
- Metadata extraction and cataloging
- Anomaly detection agents
- Self-healing data pipelines
Projects
Agent that monitors and fixes data pipeline issues autonomously
Module 5: Agentic ETL & Orchestration – 20 Hours
Skills Covered
- Dynamic pipeline generation
- Intelligent data routing
- Agent-based workflow optimization
- Integration with Airflow / Prefect
- Data lineage tracking
Project
Build an agent that designs ETL pipelines from requirements
Module 6: Vector Data Infrastructure – 16 Hours
Skills Covered
- Vector database architecture and scaling
- Embedding pipeline design
- Incremental indexing strategies
- Multi-modal embeddings
- Performance optimization
Project
Production-grade vector infrastructure for agent knowledge bases
Module 7: Agent Data Governance – 14 Hours
Skills Covered
- PII detection and redaction
- Access control for agent queries
- Audit logging
- Data versioning
- Compliance monitoring
Capstone
Secure enterprise data architecture for agent deployment
Track 3: DevOps / Platform Engineers – 70 Hours
Agent Infrastructure & MLOps
- Kubernetes & serverless agent workloads
- Message queues & auto-scaling
- CI/CD pipelines for agent deployment
- Observability, token usage & cost tracking
- Security, compliance & prompt injection defense
Capstone
Secure production deployment of a multi-agent system
Track 4: System Architects – 75 Hours
- Single-agent vs multi-agent architectures
- Orchestration patterns (hierarchical, flat, dynamic)
- Agent communication protocols
- State management strategies
- Enterprise AI governance
Capstone
Complete enterprise-scale Agentic AI architecture document
Track 5: QA / Test Engineers – 65 Hours
- Behavioral testing for non-deterministic systems
- LLM-as-judge evaluation frameworks
- Chaos engineering & reliability testing
- Quality metrics & performance benchmarking
Capstone
Enterprise QA framework forAgentic AI systems
Track 6: Business Analysts / Product Managers – 55 Hours
- AI use-case identification & ROI analysis
- Agent UX & conversational design
- KPI definition & dashboards
- Stakeholder communication & change management
Capstone
Complete Agentic AI product roadmap
Advanced Specializations – 40 Hours Each (Optional)
Multi-Agent Systems
Game theory, negotiation protocols, swarm intelligence, distributed decision-makingAutonomous Code Agents
Code generation, refactoring, automated testing, bug fixing, repository analysisEnterprise Integration
SAP, Salesforce, ServiceNow, legacy modernization, RPA + AIVertical AI Agents
Healthcare, Finance, Legal, Manufacturing, RetailLearning Methodology
Delivery Format
- 60% Hands-on Labs & Projects
- 25% Theory & Conceptual Learning
- 15% Case Studies & Discussions
Assessment Methods
- Weekly coding assignments
- Project-based evaluations
- Peer code reviews
- Capstone project presentation
- Optional certification exam
Tools & Platforms Covered
- GitHub
- Jupyter Notebooks
- AWS / Azure / GCP Sandboxes
- LangSmith / LangFuse
- Slack / Discord Learning Community
Prerequisites by Role
- Python programming
- REST APIs
- Cloud fundamentals
- Git version control
- Developers: OOP, async programming
- Data Engineers: SQL, ETL
- DevOps: CI/CD, containers
- Architects: distributed systems
- QA: automation tools
- Business Analysts: process mapping
Course Highlights – Agentic AI Course in Chennai
Industry-oriented Agentic AI training in Chennai
Hands-on Agentic AI certification program
Real-world autonomous AI agent projects
Role-specific learning paths
Enterprise tools: LangChain, AutoGen, CrewAI, LLMOps
Production deployment & monitoring
Designed for developers, data engineers, DevOps, architects, QA & BAs
Certification Path
Levels
- Level 1: Agentic AI Practitioner
- Level 2: Agentic AI Specialist
- Level 3: Agentic AI Architect
Recommended Learning Timeline
- Intensive Track: 12–16 weeks
- Part-Time Track: 6–9 months
- Cohort-based & milestone-driven learning
Industry Alignment & Career Outcomes
- AI Automation Specialists
- Agent Orchestration Engineers
- LLMOps Engineers
- Conversational AI Developers
- AI Integration Architects
- Autonomous System Designers
Disclaimer
All salary figures, job statistics, adoption rates, and quantitative data mentioned on this page are sourced from publicly available web resources, industry reports, and prevailing market trends. DreamsPlus does not guarantee the accuracy, completeness, or timeliness of this information.
Actual salaries, job opportunities, certification outcomes, and career growth may vary based on individual skills, experience, location, organization, and market conditions. This information is provided strictly for general guidance and reference purposes only. Learners are advised to independently verify all data before making career, financial, or educational decisions.
Frequently Asked Question
Agentic AI training in Chennai focuses on building autonomous AI agents that can reason, plan, use tools, and take actions independently. This course teaches professionals how to design, deploy, and manage agentic AI systems using technologies like LangChain, AutoGen, RAG, and multi-agent orchestration for real-world enterprise applications.
The Agentic AI course in Chennai is designed for IT professionals such as software developers, data engineers, DevOps engineers, system architects, QA testers, and business analysts. Anyone with basic Python knowledge and an interest in AI automation or autonomous systems can benefit from this training.
Through Agentic AI certification training, you will gain skills in autonomous AI agent development, multi-agent systems, LLMOps, RAG systems, vector databases, agent testing, security, and production deployment. You will also learn how to integrate AI agents with enterprise tools and cloud platforms.
Yes, this Agentic AI training in Chennai includes extensive hands-on learning with real-world projects. Participants will build task-planning agents, multi-agent systems, RAG-based AI agents, and production-ready agentic applications, with capstone projects aligned to enterprise use cases.
After completing the Agentic AI course in Chennai, learners can pursue roles such as Agentic AI Engineer, AI Automation Specialist, LLMOps Engineer, AI Integration Architect, Autonomous Systems Designer, and Conversational AI Developer across industries adopting AI-driven automation.