Advanced Agentic AI Course in Kolkata
Applied Agentic AI Systems, Design & Impact
Advanced Agentic AI Training in Kolkata | Classroom & Live Online | Practical AI Agent Development
Learn how to design, build, integrate and deploy practical
Agentic AI systems with the Applied Agentic AI Systems, Design & Impact program from Palium Skills.
This advanced practitioner-focused program goes beyond basic Generative AI and prompt engineering. It covers the technologies and architectures used to build modern AI-agent solutions, including
Large Language Models (LLMs), prompt engineering, Python, Retrieval-Augmented Generation (RAG), vector databases, AI agents, tool calling, multi-agent systems, LangChain, LangGraph, CrewAI, AutoGen, Model Context Protocol (MCP), AI automation, deployment, observability and AI product strategy.
The program is designed for developers, software professionals, AI/ML practitioners, technical professionals, product professionals, entrepreneurs and experienced business users who want to move from using AI tools to
designing and implementing AI-powered systems.
Training is available through
classroom and live online modes, including training options in Kolkata.
Applied Agentic AI Training in Kolkata
Agentic AI is moving beyond simple question-and-answer interactions toward systems capable of working through multi-step objectives, using tools, retrieving information, coordinating tasks and operating within defined workflows.
Palium Skills'
Advanced Agentic AI course in Kolkata provides a structured pathway from modern LLM concepts to practical AI-agent architecture and implementation.
The program combines:
- Instructor-led learning
- Practical demonstrations
- Coding and development exercises
- AI-agent architecture
- RAG implementation
- Multi-agent workflows
- AI automation
- Tool integration
- MCP concepts
- Deployment and observability
- Business use cases
- Capstone project work
Training Modes
- Classroom training in Kolkata
- Live online instructor-led training
- Mentor-supported learning
- Weekday batches
- Weekend options, subject to batch schedule
What Is Agentic AI?
Agentic AI refers to AI systems designed to work toward defined goals by combining capabilities such as reasoning, planning, context management, tool usage, memory, information retrieval and workflow execution.
A traditional Generative AI interaction may produce an answer to a prompt.
An agentic system can be designed to take a broader objective and perform a sequence of controlled steps.
For example, an AI agent may:
- Receive a business objective.
- Understand the task.
- Break the task into smaller steps.
- Retrieve relevant information.
- Select appropriate tools.
- Execute actions.
- Evaluate results.
- Continue the workflow where appropriate.
- Escalate to a human when required.
The Applied Agentic AI program teaches the technologies and architectures required to understand and implement these systems.
Generative AI vs Agentic AI
Generative AI and Agentic AI are closely connected but serve different purposes.
Generative AI focuses on producing outputs such as text, code, images, summaries and other content.
Agentic AI extends these capabilities into goal-oriented workflows where AI systems can be designed to use tools, retrieve information, perform multiple steps and interact with external systems under defined controls.
This course focuses on the engineering and architecture required to move from basic Generative AI usage toward
practical AI-agent systems.
What You Will Learn
By completing this advanced Agentic AI training program, learners will understand how to:
- Work with modern Large Language Models
- Design effective prompts and system instructions
- Build AI-powered applications using Python
- Understand embeddings and vector representations
- Design Retrieval-Augmented Generation systems
- Work with vector databases
- Build knowledge-based AI assistants
- Design single-agent architectures
- Implement tool and function calling
- Design multi-agent systems
- Use agent orchestration frameworks
- Work with LangChain and LangGraph
- Explore CrewAI and AutoGen
- Understand Model Context Protocol (MCP)
- Connect AI agents with tools and external systems
- Build AI automation workflows
- Deploy AI applications
- Monitor and evaluate AI-agent systems
- Apply observability concepts
- Evaluate AI-agent performance
- Design enterprise AI use cases
- Assess business impact and ROI
Advanced Agentic AI Course Curriculum
Module 1: Generative AI, LLMs and Agentic AI Foundations
- Artificial Intelligence overview
- Machine learning and deep learning context
- Generative AI
- Large Language Models
- Foundation models
- Transformer-based AI
- LLM capabilities and limitations
- Context windows
- Tokens and tokenization
- Introduction to Agentic AI
- Generative AI vs Agentic AI
- AI assistants vs AI agents
- Agentic AI architectures
Module 2: Python for AI Application Development
- Python fundamentals for AI applications
- Variables and data structures
- Functions
- Classes and objects
- Exception handling
- Modules and packages
- JSON
- Working with APIs
- HTTP requests
- Environment variables
- Virtual environments
- Python libraries for AI applications
- Building Python-based AI utilities
Learners who already have Python development experience can use this module to connect existing programming knowledge with AI application development.
Module 3: Prompt Engineering and LLM Application Design
- Prompt engineering fundamentals
- System instructions
- User instructions
- Context engineering
- Structured prompts
- Few-shot prompting
- Chain-of-thought concepts
- Output formatting
- JSON outputs
- Prompt templates
- Prompt testing
- Prompt evaluation
- Improving reliability
- Guardrails and constraints
Module 4: Embeddings, Vector Databases and RAG
Retrieval-Augmented Generation
Learn how AI applications can retrieve relevant information before generating responses.
Topics include:
- Embeddings
- Semantic search
- Vector representations
- Document ingestion
- Document preprocessing
- Chunking strategies
- Metadata
- Vector search
- Retrieval
- Context injection
- RAG pipelines
- Retrieval quality
- RAG evaluation
- Knowledge assistants
Technologies and platforms
Depending on the practical implementation, learners may work with technologies such as:
- LangChain
- Pinecone
- PostgreSQL
- MongoDB
- Other vector-search technologies
Practical Project
Build a RAG-powered knowledge assistant
The project demonstrates how documents can be processed, indexed and retrieved to provide context-aware AI responses.
Module 5: AI Agents and Agent Architecture
- What is an AI agent?
- Agent components
- Goals
- Instructions
- Memory
- Context
- Planning
- Reasoning concepts
- Tool usage
- Agent state
- Agent loops
- Task decomposition
- Agent workflows
- Human-in-the-loop systems
- Agent evaluation
- Failure handling
Module 6: Tool Calling and AI System Integration
Learn how AI applications can interact with external functions and systems.
Topics include:
- Function calling
- Tool definitions
- Structured inputs
- Structured outputs
- API integration
- External services
- Database interaction
- Tool selection
- Tool validation
- Error handling
- Permission controls
- Human approval workflows
Practical Project
Build a tool-enabled AI assistant
The assistant is designed to interpret a request and use defined tools to complete selected tasks.
Module 7: LangChain and LangGraph
LangChain
- LLM integration
- Prompt templates
- Chains
- Tools
- Retrievers
- Agents
- Memory concepts
- RAG applications
LangGraph
- Graph-based agent workflows
- Nodes
- State
- Edges
- Conditional workflows
- Agent loops
- Human intervention
- Multi-step orchestration
- Stateful AI applications
Practical Application
Design a structured agent workflow using modern AI orchestration techniques.
Module 8: Multi-Agent AI Systems
Learn how multiple specialized agents can work together to solve complex tasks.
Topics include:
- Single-agent vs multi-agent systems
- Agent roles
- Agent specialization
- Communication
- Task delegation
- Coordination
- Sequential workflows
- Parallel workflows
- Supervisor architectures
- Agent collaboration
- Multi-agent evaluation
- Failure handling
Frameworks and concepts may include:
- CrewAI
- AutoGen
- LangGraph
- Other relevant agent orchestration approaches
Practical Project
Build a multi-agent business workflow
Design multiple specialized agents that collaborate on a defined business problem.
Module 9: Model Context Protocol (MCP)
MCP Training and AI System Connectivity
Understand the principles behind
Model Context Protocol (MCP) and how AI applications can interact with external tools, resources and systems through standardized interfaces.
Topics include:
- MCP concepts
- MCP architecture
- MCP clients
- MCP servers
- Tools
- Resources
- External system integration
- AI-agent tool connectivity
- Secure tool access
- MCP-based workflows
- Practical MCP use cases
The module helps learners understand how modern AI applications can be connected to external capabilities.
Module 10: AI Automation and Agentic Workflows
- AI workflow automation
- Trigger-based workflows
- Multi-step automation
- AI decision points
- Tool integration
- Business process automation
- Human approval
- Error handling
- Workflow monitoring
- Automation governance
Automation Platform
Learners may explore platforms such as
n8n and other suitable AI automation technologies.
Practical Project
Build an AI-powered automated workflow
Design a workflow that combines AI reasoning with business process automation.
Module 11: Deployment, Evaluation and Observability
Building an AI agent is only part of the process. Production-oriented AI systems also require testing, monitoring and evaluation.
Topics include:
- Application deployment
- APIs
- Docker fundamentals
- Cloud deployment concepts
- Environment configuration
- Logging
- Monitoring
- Agent evaluation
- Tracing
- Latency
- Cost monitoring
- Quality evaluation
- Failure analysis
- Observability
Tools and platforms may include:
- LangSmith
- Phoenix
- Docker
- Cloud platforms such as Azure
- Other relevant AI application infrastructure
Module 12: AI Product Strategy, Business Impact and Capstone
The final module connects technical implementation with practical business outcomes.
Topics include:
- Identifying suitable AI-agent use cases
- AI product design
- Business requirements
- Cost considerations
- AI implementation strategy
- ROI evaluation
- Risk assessment
- Responsible AI
- Human oversight
- Security and privacy
- AI product readiness
- Deployment considerations
- Measuring business impact
Capstone Project
Learners design and develop an
end-to-end Agentic AI solution that brings together concepts from the program.
A capstone may include:
- LLM integration
- Prompt engineering
- RAG
- Tools
- AI agents
- Multi-agent workflows
- Automation
- External-system integration
- Evaluation
- Deployment considerations
Practical Agentic AI Projects
The program emphasizes practical application rather than only theoretical learning.
Potential projects include:
1. RAG Knowledge Assistant
Build an AI assistant that retrieves information from a document or knowledge base before generating a response.
2. Tool-Enabled AI Assistant
Create an assistant capable of interacting with defined tools or APIs.
3. Multi-Agent Business System
Design multiple specialized agents that collaborate on a business workflow.
4. AI Automation Workflow
Build an automated workflow combining AI capabilities with business-process automation.
5. End-to-End Agentic AI Capstone
Develop an integrated AI-agent application combining multiple technologies covered during the program.
Technologies Covered
Depending on the practical implementation and current technology versions, the program may include:
- Python
- Large Language Models
- ChatGPT
- Generative AI
- Prompt Engineering
- RAG
- Embeddings
- Vector Databases
- LangChain
- LangGraph
- CrewAI
- AutoGen
- Model Context Protocol (MCP)
- n8n
- APIs
- Docker
- Azure
- LangSmith
- Phoenix
- AI automation tools
Technology coverage may evolve as the Agentic AI ecosystem changes.
Who Should Take This Advanced Agentic AI Course?
This program is intended for learners who want to move beyond basic AI-tool usage and understand AI-agent development and system design.
It is suitable for:
- Software developers
- Python developers
- AI/ML professionals
- Data professionals
- Application developers
- Solution architects
- Technical consultants
- Business analysts with technical exposure
- Product managers
- Technology managers
- Automation professionals
- Startup founders
- Entrepreneurs
- Experienced working professionals
Prerequisites
Recommended prerequisites include:
- Basic Python programming
- Familiarity with programming concepts
- Basic understanding of APIs
- Familiarity with JSON
- Basic understanding of Generative AI and LLMs
- Basic computer and internet skills
Prior experience with machine learning is helpful but not mandatory.
Learners without programming experience should consider beginning with the
Agentic AI Foundations: Building Intelligent AI Assistants program before progressing to this advanced course.
Agentic AI Foundations vs Applied Agentic AI Systems
Palium Skills offers a structured pathway for different learner levels.
Agentic AI Foundations
Designed for:
- Beginners
- Students
- Non-programmers
- Business professionals
- Professionals new to AI
Focus:
- Generative AI
- AI assistants
- Prompt engineering
- AI tools
- AI automation
- No-code/low-code workflows
Applied Agentic AI Systems
Designed for:
- Developers
- Technical professionals
- AI practitioners
- Advanced learners
- Professionals with programming experience
Focus:
- Python
- LLM applications
- RAG
- Vector databases
- AI agents
- Tool calling
- Multi-agent systems
- LangChain
- LangGraph
- MCP
- AI automation
- Deployment
- Observability
- AI product strategy
Recommended pathway:
Agentic AI Foundations → Applied Agentic AI Systems
Agentic AI Training in Kolkata
Palium Skills provides advanced
Agentic AI training in Kolkata through instructor-led classroom programs and live online learning.
South Kolkata Center
1st Floor, Sheeba Bhavan
1/22 Poddar Nagar
Near South City Mall
Kolkata – 700068
Salt Lake Center
5th Floor, RDB Boulevard
Block GP, Salt Lake Electronic Complex
Kolkata – 700091
The program is also available through live online training for learners outside Kolkata.
Classroom and Live Online Agentic AI Training
Classroom Training
Attend instructor-led sessions at the Palium Skills Kolkata training centers with practical exercises and mentor interaction.
Live Online Training
Participate in live instructor-led sessions remotely from anywhere in India or internationally.
Training Options
- Weekday batches
- Weekend options
- Classroom learning
- Live online learning
- Mentor-supported practical work
Batch schedules are subject to availability.
Career Applications of Agentic AI
Agentic AI skills can be applied across technology and business functions.
Potential application areas include:
- Software development
- IT automation
- Customer support
- Business operations
- Research
- Knowledge management
- Human Resources
- Marketing
- Sales
- Finance
- Project management
- Data analysis
- Document processing
- Enterprise workflow automation
The course is intended to help professionals understand how to identify suitable AI-agent use cases and translate them into practical technical solutions.
Why Learn Applied Agentic AI?
The AI ecosystem is moving from simple content generation toward increasingly integrated AI applications.
Professionals who understand the underlying technologies can explore how AI can be used to:
- Automate repetitive workflows
- Build intelligent assistants
- Retrieve information from enterprise knowledge
- Connect AI to tools and APIs
- Coordinate multiple AI tasks
- Develop AI-enabled applications
- Evaluate AI system performance
- Integrate AI into business processes
The program therefore combines
AI application development, agent architecture and business impact rather than focusing only on prompt usage.
Industry Faculty — Suman A
Suman A — Industry Faculty | Software Development & AI Application Experience
Suman A is an experienced industry faculty member associated with Palium Skills, bringing
extensive software development and IT industry experience to the training environment.
His industry-oriented experience provides a practical perspective on how software applications are designed, developed, integrated and maintained in professional environments.
For an advanced Agentic AI program, this software-development background is particularly relevant because modern AI-agent applications increasingly combine:
- Software development
- APIs
- Python
- Application architecture
- Data processing
- AI models
- External tools
- Workflow automation
- System integration
- Application testing
- Deployment considerations
Suman A's training approach focuses on helping learners connect emerging AI technologies with established software-development principles.
Faculty Focus
His practical teaching approach can cover areas such as:
- Software application development
- Programming concepts
- AI application integration
- Python-based development
- API integration
- AI workflow design
- Application architecture
- AI assistants
- Agentic AI concepts
- Automation
- Practical project development
Industry-Oriented Learning
The objective of the faculty-led sessions is to help learners understand not only how an AI technology works, but also how it can fit into a real application or business workflow.
Learners are encouraged to consider:
- What problem is being solved?
- What data is required?
- Which AI capability is appropriate?
- Which tools or APIs are required?
- Where should automation be used?
- Where is human approval required?
- How should the application be tested?
- How should performance and cost be evaluated?
- How can the solution be maintained?
This industry-oriented perspective is an important part of the Applied Agentic AI Systems program.
Course Duration and Delivery
Course: Applied Agentic AI Systems, Design & Impact
Level: Practitioner / Advanced
Duration: 4 Months
Training Mode: Classroom / Live Online
Location: Kolkata
Online: Available
Projects: Practical projects + capstone
Faculty: Industry-oriented instructor-led training
Certificate: Palium Skills Course Completion Certificate
Certification
Participants who successfully complete the program receive a:
Palium Skills Course Completion Certificate in Applied Agentic AI Systems, Design & Impact
The certificate confirms completion of the Palium Skills training program.
Enquire About Advanced Agentic AI Training
Interested in learning how to design and build practical AI-agent systems?
Contact Palium Skills for:
- Upcoming batch dates
- Classroom training in Kolkata
- Salt Lake training
- South Kolkata training
- Live online training
- Course fee
- Admission information
- Corporate training
- Customized AI training
Call: 8420594969 / 7044871915
WhatsApp: 9903130500
Email: info@paliumskills.com
Website: www.paliumskills.com
Palium Skills
Professional training in
Artificial Intelligence, Agentic AI, Generative AI, Data Analytics, Microsoft technologies, Programming, Oracle, Automation and professional technology skills, delivered through classroom and live online learning.
New to Agentic AI? Start with our
Agentic AI Foundations: Building Intelligent AI Assistants program before progressing to this advanced practitioner course.
