Executive Program in AI Engineering & Intelligent Agents
Build and deploy production-ready AI systems and intelligent agents for enterprise environments.
Certificate: CCE IIT Roorkee Certificate on successful completion
Duration: 80 Hours, weekend friendly
Next Cohort: April 4th 2026
Format: Live online sessions, hands on labs, recorded material after every class
Audience: IT, engineering, and technology professionals working on enterprise systems, with 2 to 15 years of experience.
Program Fee: ₹120,000 + GST
Scholarships: Merit and need based options available*
Sessions by: IIT Roorkee faculty and industry experts.
IIT Roorkee Pedigree
NIRF #6 institution
Academic rigor with industry-relevant AI engineering
Live Online, Weekend Sessions
Executive-friendly live classes
Designed for working professionals
AI Engineering Focus
Python, ML, LLMs, RAG, and agents
Engineering-first learning approach
Practical, Hands-On Labs
Build real AI workflows
Code-first, implementation-driven labs
Enterprise AI Systems
Design production-ready AI systems
Reliability, evaluation, and integration
IIT Roorkee Certificate
Certificate from CCE IIT Roorkee
On successful program completion
This program is designed for professionals with 2 to 15 years of experience working in IT services, product companies, and technology-driven enterprise organizations, including:
Software development and backend engineering
- IT development and IT infrastructure
- Cloud engineering and DevOps
- Data engineering and data platforms
- QA and automation
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AI, ML, and analytics engineering teams (including enterprise and manufacturing environments)
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Product engineering and solution delivery
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Consulting roles working on enterprise systems
Advanced ML background is not required. Basic familiarity with Python is helpful but not mandatory.
Delivered with the Continuing Education Centre of IIT Roorkee, this program combines academic rigor with a strong engineering focus.
AI engineering is now a core capability across industries, with manufacturing, automobile, energy, pharma, logistics, and BFSI organizations building internal AI systems for automation, decision support, and intelligent operations.
Participants learn from IIT Roorkee faculty and industry practitioners through hands-on, implementation-led instruction designed for engineers working on real enterprise systems.
Many AI programs today fall into one of two categories:
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Strategy-focused programs for business leaders that explain why AI matters, but do not teach technical implementation
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Academic data science programs that focus on math and model training, but not modern LLM or agent-based systems
This creates a clear gap for working engineers.
Most IT and ITeS professionals do not need to train large models from scratch. Instead, they need to learn how to:
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Use existing models and LLMs effectively
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Build reliable retrieval augmented generation (RAG) pipelines
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Design tool-based agents and workflows
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Integrate AI capabilities into real applications and services
This executive program is designed to build exactly these practical, engineering-focused capabilities.
Applied engineering roles this skill set supports:
- AI Engineer
- Applied AI Engineer
- ML Engineer
- LLM Engineer
- Intelligent Automation Engineer
- Agent Workflow Developer
- RAG Developer
- AI Product Developer
Engineering-Focused Skills
Participants gain engineering focused skills, including:
Core Implementation Skills
- Building ML models in Python using standard libraries
- Working with LLM APIs for reasoning, summarisation, and workflow automation
- Designing prompts and structured outputs that are safe for integration
- Building simple RAG systems using vector databases and document retrieval
Advanced Integration Skills
- Using tool calling to create functional agents for enterprise tasks
- Implementing workflows that combine models, retrieval, and tools
- Deploying small AI features through APIs or lightweight user interfaces
- Evaluating AI outputs and improving them through iteration
The learning experience emphasises writing code, debugging errors, examining logs, understanding model behaviour, and building practical components step by step.
Where our learners work
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No Black Box Approach
The program follows a code first, no black box approach.
Deep Understanding
- How Python code, LLM APIs, and retrieval layers work together
- How agents decide when to call tools and how to handle tool outputs
- How to analyse failure modes and adjust prompts, retrieval, or logic
Robust Implementation
- How to structure workflows so that they are predictable and safe
- How to design small but robust AI micro features inside existing applications
- Building engineering confidence, not just conceptual understanding
Our Goal
The goal is to build engineering confidence, not just conceptual understanding.
The program includes 80 hours of live instruction through weekend virtual classes. Recorded videos are provided after each session for revision.
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Module 1
Motivation for AI and Modern AI Landscape
- Why AI matters for engineers
- Evolution of AI systems
- Handling unstructured text input
- How LLMs and agents became the new engineering stack
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Module 2
Foundations of Data, Machine Learning, and AI Systems
- Data fundamentals for AI workflows
- ML concepts engineers must know
- What makes an AI system work end to end
- How ML, LLMs, retrieval, and agents connect in real systems
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Module 3
Foundations of AI Engineering with Python
- Python structures used in AI applications
- Working with APIs, JSON, and data parsing
- Handling unstructured text input
- Code organisation and reusable utilities
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Module 4
Machine Learning Fundamentals for Implementation
- Supervised and unsupervised learning basics
- Training small models using standard libraries
- Evaluating model behaviour with metrics
- Exporting and reusing trained models
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Module 5
Working with LLM Systems
- Calling LLM APIs safely and efficiently
- Prompt patterns for reasoning and structured outputs
- Understanding context windows and token limits
- Using LLMs to generate functions, summaries, and transformations
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Module 6
Retrieval Augmented Generation (RAG)
- Document loading, chunking, and preprocessing
- Embeddings and vector search
- Connecting retrieval to LLM prompts
- Building a simple RAG pipeline end to end
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Module 7
Basic Agents and Tool Powered Workflows
- Defining Python functions as tools
- Allowing models to call tools with controlled inputs and outputs
- Designing simple multi step agent workflows
- Agent result refinement and validation patterns
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Module 8
Building and Deploying AI Applications
- Wrapping models and workflows into APIs using FastAPI
- Simple UI creation using Streamlit or similar tools
- Environment setup and dependency management
- Introduction to monitoring, logging, and basic observability
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Module 9
Engineering Patterns for Enterprise AI Systems
- Evaluating AI outputs for accuracy and reliability
- Improving retrieval and prompting strategies
- Error handling and fallback mechanisms
- Basic safety, guardrails, and controlled execution principles
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Module 10
Capstone Implementation
Participants build an end to end AI system that includes:
- Model or LLM usage
- Retrieval logic
- Tool based workflow or agent logic
- A functional interface or API
- Clear documentation and demonstration
Real Engineering Tasks
Every module includes guided labs aligned with real engineering tasks. You will practise:
Python ML Pipelines
Writing Python ML pipelines and evaluating models with interpreting metrics
LLM Workflows
Building LLM workflows using APIs and creating vector stores with retrieval pipelines
Agent Systems
Designing and wiring tools for agent systems and deploying AI features with APIs
Templates and starter projects are provided to help you continue after the program.
Industry-Aligned Tools
The program uses practical, industry aligned tools such as:
Core Technologies
- Python - Primary programming language
- OpenAI and similar LLM APIs - For language model integration
- LangChain style frameworks - For workflow structuring
- Basic agent utilities - For intelligent automation
Infrastructure & Deployment
- Vector databases - Chroma, Pinecone for retrieval
- FastAPI - For serving models and workflows
- Streamlit - For rapid interface development
- Standard Python ML libraries - For model implementation
Only stable and commonly used tools are included so that you can apply them directly in your workplace.
Academic Rigor, Industry Relevance, Trusted Credential
Delivered in collaboration with IIT Roorkee, the program combines academic rigor with a strong engineering focus aligned to real-world AI systems.
Participants learn through live sessions led by IIT Roorkee faculty, who bring research depth and analytical rigor, along with experienced industry practitioners who guide the implementation of AI, LLM, and agent-based systems used in enterprise environments.
This blend of academic depth and practical engineering experience ensures participants gain both conceptual clarity and hands-on capability required to design, build, and deploy reliable AI systems.
On successful completion, participants earn a Certificate of Completion from the Continuing Education Centre (CEC), IIT Roorkee, a credential recognized across industry and academia for structured, engineering-focused learning.
Prof. Pradeep Jha
Specialist in Smart Manufacturing and AI
Structured Learning Experience
Duration & Structure
- Total duration: 80 hours
- Live sessions: 18 sessions of 2.5 hours each
- Faculty-led learning: 45 hours
- Hands-on practice: 35 hours of tutorials and capstone work
Schedule & Delivery
- 10 modules delivered in structured engineering sequence
- Weekend live online sessions for working professionals
- Recordings shared after every class
- Guided support for capstone development
₹120,000 + GST
Complete Program Fee
Scholarships*
Available based on eligibility - Merit and need-based options
Payment Options
Full payment required at the time of enrollment
Optional Campus Immersion*
2-day optional campus visit, Includes food and shared accommodation, Available at additional cost
Group Discounts
Special rates for multiple participants from same organization
Submit Interest
Share your details to explore fit for the executive program.
Advisory discussion
Our team guides you on business relevance, priorities, and program alignment.
Enrollment & Onboarding
Confirm participation and get access to strategy sessions and resources.
The program welcomes engineers and technology professionals from IT, enterprise, and industrial environments who are committed to hands-on learning and real-world implementation.
Career Outcomes
The program builds skills relevant for engineering and solution roles such as:
(AI Driven)
Participants gain the ability to design and implement real-world AI systems that seamlessly integrate into enterprise environments.
Ready to Upskill
Build enterprise ready AI engineering skills with IIT Roorkee faculty and industry mentors. Move beyond experimentation and learn how to ship working AI features in real systems.
FAQs
* Optional Campus Immersion: Campus immersion is optional and available at an additional cost. Approximate charges are ₹10,000 for 2 days, which includes food and shared accommodation (on a sharing basis). Subject to confirmation.
* Scholarships: Scholarships are subject to meeting predefined eligibility criteria such as educational background, academic performance, and professional experience. Final approval is at the sole discretion of Institute.