What is this program and which institution offers it?

The program is the Advanced Engineering Program in AI Agent Workflows and Agentic Systems Development, offered by IITM Pravartak Technologies Foundation, the Technology Innovation Hub of IIT Madras established under the Department of Science and Technology, Government of India.

What is the duration and fee of the program?

The program runs for 7 months with 140+ hours of learning. The course fee is Rs. 1,25,000 + 18% GST.

Who are the Program Directors?

The program is led by three IIT Madras faculty: Prof. Balaji Srinivasan, Professor in Mechanical Engineering and founding core faculty at the School of Data Science and AI (PhD from Stanford University); Prof. Ganapathy Krishnamurthi, Professor in Engineering Design and founding core faculty at the School of Data Science and AI (PhD from Purdue University); and Prof. Kushal Shah, Professor of Applied Mathematics and Computer Science (PhD from IIT Madras, postdoc at Weizmann Institute, INAE Young Engineer Award recipient).

What tools and platforms are covered in this program?

Tools include Make, Zapier, Haystack, Relevance AI, LangChain for orchestration; Claude, ChatGPT, Cohere, LlamaIndex, OpenAI for GenAI and LLMs; GitHub Copilot, AutoGen for development; Evidently AI, Weights and Biases, PromptLayer for monitoring and evaluation; and Zoho, SAP, Salesforce for enterprise integration.

Does the program include campus immersion?

Yes. An optional 3-day campus immersion at IITM Pravartak Research Park is available as part of the program.

Can I self-fund this program?

Yes. You can self-fund either partially or fully. Futurense also provides financial assistance through partnered lending institutions.

Advanced Engineering Program in AI Agent Workflows and Agentic Systems Development

Orchestrate and scale strategies trusted by enterprise AI teams

Application Deadline

10th April, 2026

Apply Now Download Brochure

Application Closes In:

Days

Hours

Minutes

Sec

Start Date

18th April, 2026

Duration

7 Months | 140+ Hrs

Course Fee

₹1,25,000 + 18% GST

No. of Seats Left

6

Credits

18

Application Deadline

10th April, 2026

Application Closes In:

Days

Hours

Minutes

Sec

Program Highlights

Build AI-driven business processes using multi-agent orchestration & context engineering.

Integrate AI agents with APIs and business systems, supported by human-in-the-loop governance.

Get hands-on experience with 30+ tools while building a deployable capstone.

Learn through weekend sessions with IIT faculty & industry leaders, with an optional 3-day campus immersion.

Download Brochure For Full Details

About IITM Pravartak

IITM Pravartak Technologies Foundation is the Technology Innovation Hub of IIT Madras, established under the Department of Science and Technology, Government of India. Embedded within the IITMRP ecosystem, it combines renowned faculty, cutting-edge labs, and specialised research facilities to drive skilling, innovation, and incubation.

Working at the intersection of academia, research, and industry, IITM Pravartak fosters the adoption of deep technology, nurtures next-generation talent, and enables real-world impact.

Our Program Director

Prof. Balaji Srinivasan

B.Tech from IIT Madras, MS from Purdue University, and PhD from Stanford University

Prof. Balaji Srinivasan is a Professor in the Department of Mechanical Engineering and founding core faculty at the School of Data Science and Artificial Intelligence at IIT Madras, pursuing research in the areas of fundamental Machine Learning and Deep Learning with focus on applications to science and engineering disciplines. He earned his B.Tech from IIT Madras, MS from Purdue University, and PhD from Stanford University, where he was the William K. Bowes, Stanford Graduate Fellow. Prior to his current role at IIT Madras, he was a faculty member at IIT-Delhi and a post doctoral fellow at University of Michigan, Ann Arbor. His current research involves developing computational algorithms and models for a range of practical engineering problems that use a combination of probabilistic models, PDE based approaches as well as data-driven approaches. He has published research papers across multiple domains including Machine Learning, Partial Differential Equations, Computational algorithms, and High performance computing.

Prof. Ganapathy Krishnamurthi

PhD from Purdue University, and MSc in Physics from IIT Madras

Prof. Ganapathy Krishnamurthi is a Professor in the Department of Engineering Design and founding core faculty at the School of Data Science and Artificial Intelligence at IIT Madras. He earned his PhD from Purdue University, and MSc in Physics from IIT Madras. He worked as a post-doctoral research fellow at Case Western Reserve University, USA and at Mayo Clinic, USA. His research and work experience focuses on applying Machine Learning and Artificial Intelligence techniques to problems in medical image analysis, computer vision, interpretability/explainability ability of Deep Learning models across various applications and using deep learning to solve inverse problems in medical imaging and computer vision. His current research involves developing deep learning solutions for time series data in business, engineering and imaging applications. He has published numerous research papers pertaining to Deep Learning and Machine Learning applied to many areas in science, engineering and technology.

Prof. Kushal Shah

B.Tech and Ph.D. in Electrical Engineering from IIT Madras

Prof. Kushal Shah is a Professor of Applied Mathematics and Computer Science. He previously served as Associate Professor in the Department of Electrical Engineering and Computer Science at IISER Bhopal and as Assistant Professor in the Department of Electrical Engineering at IIT Delhi. He earned his B.Tech and Ph.D. in Electrical Engineering from IIT Madras, and later pursued postdoctoral research as a Feinberg Graduate Fellow in Applied Mathematics at the Weizmann Institute of Science, Israel. His research spans Artificial Intelligence, Machine Learning, Large Language Models, and Dynamical Systems, focusing on developing ethical and practical frameworks for intelligence testing, data-centric AI systems, and algorithms for anomaly detection, biomedical text mining, and time-series analysis. He has published extensively in reputed journals including PNAS, Physical Review Letters, IEEE Transactions, and AI & Society, and is the author of the book Plasma and Plasmonics (Ane Books / De Gruyter). Recipient of the INAE Young Engineer Award, he has delivered invited talks at leading global institutions such as Imperial College London, University of Warwick, and the Weizmann Institute of Science.

The IIT Advantage

Experience Campus Immersion At IITM Pravartak Research Park

Certification From IITM Pravartak

Receive a Certificate of completion from IITM Pravartak,
recognizing your achievement.

in Just 7 Months

How You Go From Learning To Orchestrating Enterprise Multi-Agent Systems

Module 1: Building Foundations for AI Agents with Deep Learning & NLP

Overview of Deep Learning and Neural Networks
Structure of neural networks and backpropagation
Key activation functions (ReLU, Sigmoid, Tanh)
Training neural networks and hyperparameter tuning
Introduction to NLP and its connection with AI agents

Module 2: Exploring NLP & Generative AI for Complex Problem Solving

NLP techniques: tokenization, stemming, lemmatization, TF-IDF
Word embeddings: Word2Vec, GloVe
Generative AI: GANs, VAEs
Applications of generative models in content creation (text, art, music)
Introduction to transformers and GPT

Module 3: Leveraging Large Language Models (LLMs) for AI Agents

Introduction to Large Language Models (LLMs)
Transformer architecture and attention mechanisms
Pre-training and fine-tuning LLMs
Use cases: GPT, BERT, T5, and more
LLMs vs. traditional rule-based systems

Module 4: Transitioning from AI Models to AI Agents with Deep Learning and LLMs

Understanding AI agents and their evolution
Key differences between AI models and agents
Using neural networks and LLMs in agent design
Contextual decision-making for agents
AI agent frameworks and tools

Module 5: Systems Thinking Foundation for Product Design

Holistic analysis of interconnected workflows
Identifying feedback loops
Mapping dependencies; Emergent behavior in MAS
Balancing optimization across subsystems

Module 6: Designing Workflows and Systems for Agents

Problem immersion; Journey mapping (As‑Is → To‑Be)
Leverage point discovery
KPI & guardrail definition
Service blueprint creation

Module 7: MAS Design

Hierarchical
Manager‑worker
Peer‑to‑peer
Blackboard
Contract‑net
Debate/hybrid human‑agent

Module 8: Exploring Context Management in Multi-Agent Systems

Understanding context in AI workflows
Passing context between agents
Context engineering for task completion
Designing inputs/outputs for multi-agent workflows.

Module 9: Designing and Coordinating Multi-Agent Systems

Multi-agent system architecture
Agent coordination and task delegation
Message passing between agents
Defining agent roles within workflows.

Module 10: Optimizing Agent Workflows for Scalability and Efficiency

Workflow design templates
Task decomposition and agent interaction
Process mapping and optimization
Designing scalable workflows for complex systems.

Module 11: Prototyping Multi-Agent Systems for Real-World Applications

Design-first approach to multi-agent systems
Integrating agent workflow design into prototyping
Connecting agents within workflows to simulate real-world applications.

Module 12: Integrating Real-World Tools for Agentic Workflows

Integrating real-world tools with agentic workflows
Leveraging memory systems
Using external APIs and data sources in multi-agent workflows
Scaling workflows with advanced tools.

Module 13: Injecting Context into Agent Workflows for Dynamic Handling

Integrating real-world tools with agentic workflows
Dynamic input handling
Context injection techniques for adaptive agent workflows
Role-based prompts and task-specific agent communication.

Module 14: Integrating Real-World Tools for Agentic Workflows

Business-driven multi-agent system automation
Automating complex business workflows with multiple agents
Ensuring smooth coordination and context passing.

Module 15: Monitoring and Managing Multi-Agent Systems in Real-Time

Understanding real-time monitoring of multi-agent workflows
Using logging and monitoring tools to track agent performance
Debugging agent communication and task delegation errors.

Module 16: Integrating Multi-Agent Systems into Enterprise Workflows

Integrating agent systems into business enterprise workflows
Bridging agents with enterprise resource planning (ERP) and customer relationship management (CRM) systems.

Module 17: Advanced Context Engineering for Complex Systems

Deep dive into context engineering for multi-agent systems
Handling complex context switches in large-scale workflows
Adaptive task handling.

Participants will work on 10+ diverse hands-on activities with AI Tools

Build a multi-agent customer support automation using CrewAI and LangChain

Design a Manager–Worker orchestration pipeline integrated with an enterprise CRM

Deploy a context-aware document retrieval agent using Flowise and OpenAI APIs.

AI Clinic

Through the Futurense AI Clinic, you’ll gain hands-on exposure to real enterprise-grade AI projects, from ideation to deployment.

Work on Live Projects

Solve real business challenges using GenAI, Agentic AI, and automation workflows.

Use Industry-Standard Tools

Hands-on with LangChain, CrewAI, Flowise, OpenAI APIs, Zapier, HubSpot, and more.

Collaborate with Experts

Guided by IIT faculty and industry mentors through each phase of your project.

End-to-End AI Execution

Build, test, and deploy intelligent workflows that simulate real-world problem solving.

While mastering 20+ Tools

Agent Orchestration & Workflow

Generative AI & Prompting

AI-Enhanced Development & Testing

Monitoring & Feedback Loops

Enterprise System Integration

Testing & Evaluation Frameworks

By The End, You’ll Be Able To Do All This

Workflow-First Design

Re-engineer business processes so agents operate as reliable executors instead of retrofitted add-ons.

Context Engineering

Master prompt strategies, memory management, and reasoning approaches to drive precision in outputs.

Multi-Agent Orchestration

Architect collaboration models like Manager–Worker, Peer-to-Peer, and Hybrid systems for enterprise use.

Enterprise Integration

Connect agents with APIs, databases, CRMs, ERPs, and external tools to ensure production-grade workflows.

Human-in-the-Loop Governance

Design trust, oversight, and continuous feedback loops that enable scalable adoption across enterprises.

Modular & Scalable Architectures

Build reusable agent components that can be rapidly deployed across multiple use cases and teams.

This Program is for

Educational Qualification

Bachelor’s degree (minimum 3 years) in Computer Science, IT, Engineering, Mathematics, or a related field. MCA / M.Sc / M.Tech candidates with exposure to technology, analytics, or systems are also eligible

Work Experience

Minimum 1 year of experience in product management, software development, enterprise/solution architecture, data science, ML engineering, automation & process excellence, or consulting.

Freshers

Exceptional fresh graduates with strong programming skills and aptitude for AI workflows may be considered via screening.

Prior Knowledge

Familiarity with programming (Python preferred), AI concepts, APIs, and data-driven systems.

Selection Process

Clear a pre-screen exam testing programming fundamentals, logic, and workflow/AI readiness.

Qualifying Test

What You’ll Be Tested On

Logical Reasoning

Python Programming

AI & ML Concepts

Data Literacy & Interpretation

Duration: 60 minutes

Important Guidelines

Each section has its own pass criteria: you must score at least 40% in each area.

There is no sectional time limit; you may answer sections in any order.

Show all workings for coding or analytical questions where applicable.

No prior experience needed.

Software Engineers & Developers

looking to transition into agentic development.

Solution Architects & Enterprise Architects

designing AI-enabled business systems.

Data Scientists, ML Engineers & AI Developers

moving from prototypes to production-ready workflows.

Automation & Process Excellence Professionals

and Service Designers re-engineering processes with multi-agent systems.

Roles Thatʼll Be Looking for You

AI Agent Workflow

Context Engineering & Precision Automation

Enterprise AI Systems

Earning Potential

₹15-25 LPA

Career Assistance By Futurense

Young man studying math, writing notes with a pen while looking at a laptop screen displaying a right triangle and equations.

Profile, Narrative & Resume Building

Craft a recruiter-ready identity with optimized resumes, LinkedIn profiles, and a strong career narrative.

Students seated at desks with laptops attending an online video conference featuring a man speaking.

Career-Specific Training

Develop job-ready skills with role-focused training, capability tests, AI tools workshops, and continuous upskilling to match real hiring expectations.

Two men sitting at a table in an office, reviewing documents and discussing work with a laptop and coffee cups nearby.

Futurense Job Board - Exclusive Opportunities

Access curated, pre-vetted roles before they hit public portals, with priority visibility for Futurense learners.

Two men reviewing a resume document together at a table in a modern office setting.

Interview Playbooks & Cheat Sheets

Get insider interview guidance with structured playbooks: FAQs, sample answers, frameworks, recruiter insights, and round-wise preparation.

Mock Interviews with Experts

Experience real interview simulations with personalized feedback from mentors, industry leaders, and FLC members.

Three young professionals enjoying coffee and snacks while collaborating around a laptop in a modern office.

Mentor Referrals & Networking

Unlock referral advantages, insider recommendations, alumni-driven opportunities, and FLC mentorship that accelerates your career entry.

Two men sitting across a wooden table in an office, one taking notes and the other using a laptop.

Salary Negotiation Support

Get guidance on positioning, benchmarking, negotiation strategy, and communication to secure the compensation you deserve.

Our students are acing it!

They are working at companies which are a dream for most

Fee Structure

Total Admission Fee

₹1,25,000

+ 18% GST

Apply Now

Program fee is subject to change from the next cohort.

A non-refundable application deposit of ₹5,000 will be adjusted in the total fee. Program fees are refundable only if the student withdraws before the start date. No refunds will be made after the program begins.

An additional ₹10,000 will be applicable if you opt for the Campus Immersion (optional).

Deserving candidates opting for the upfront payment plan may be eligible for a scholarship of up to ₹9,000.

Application Deadline

10th April, 2026

Admissions close once the required number of students is enrolled for the upcoming cohort. Apply early to secure your seat.

How it Works

Application Process

Submit Your Application

Fill in your details and share your interest in joining the program.

Clear the Qualifying Test

A short test designed to assess your programming fundamentals and AI/workflow readiness

Pay and Confirm Your Seat

Secure your spot in the upcoming cohort with flexible payment options

Apply Now

Traditional AI Agent vs. IITM Pravartak: AI Agent Workflows and Agentic Systems Development

Dimension

This Programme

Other Programme

Core Philosophy

Workflow-first, designing systems where agents collaborate and deliver outcomes

Tool-first, focused on building individual agents

Curriculum Style

End-to-end orchestration of workflows, with modules on context, governance, and enterprise integration

Teaches how an agent works, often limited to frameworks and demos

Tool Exposure

Hands-on with 30+ enterprise tools with LangChain, Zapier, Relevance AI, GPT-4o tools, Claude, and many others, all applied within workflows

Covers isolated tools or frameworks (LangChain, AutoGPT, etc.)

Multi-Agent Coverage

Covers manager–worker, peer-to-peer, and hybrid orchestration patterns for real-world enterprise use

Often ignores collaboration models; focuses on single-agent demos

Product Architecture

Human-in-the-loop protocols, trust, safety, and continuous feedback loops embedded from the start

Rarely emphasized

Deployment Focus

Enterprise-grade workflows, APIs, databases, CRMs, and ERPs integrated for production readiness

Focus on PoCs and sandbox demos

Mentor Access

Direct mentorship from IIT faculty and Futurense Leadership Council with enterprise project reviews

Limited peer or tool-community guidance

Capstone Format

Real enterprise-ready agentic workflow project, reviewed by industry mentors and IITM faculty

Mock case studies or single-agent prototypes

Learning Outcome

Architect, orchestrate, and deploy scalable multi-agent systems with measurable business impact

Understand how to build a basic agent

Mindset Trained

Workflow-first AI leader who designs for scale, trust, and enterprise adoption

Tool-user or experimenter

Feeling Underconfident About Your Tech Skills?

Kick things off with a 2-Week Bridge Course that gets you course-ready

Young man in a blue shirt resting his chin on his hand, looking thoughtfully upward.

What you'll learn:

Maths Refresher

Programming Foundations

Data Manipulation & Representation

Cloud Foundations

Machine Learning Essentials

Worth ₹29,000

Included free with your enrollment.

Led by the Futurense Leadership Council (FLC)

A collective of CXOs, AI leaders, and digital transformation heads from global and Fortune 500 companies shaping the AI-native workforce.

Aditya Khandekar

President, Corridor Platforms

Akshay Kumar

Research & Analytics Leader

Alok Tiwari

Director of Analytics, Junglee Games

Anand Das

Chief Digital & AI Officer, TVS Motors

Aneel kumar

Global Chapter Leader - ICSS, DD&T

Anirban Nandi

Head of AI Products & Analytics (Vice President), Rakuten India

Ankit Mogra

Director – Insights & Analytics, Ather Energy

Anupam Gupta

Independent Consultant – AI/ML Product Development, Amplify Health

Arpit Agarwal

Data Science Manager, Google

Arvind Balasundram

Executive Director, Commercial Insights & Analytics

Ashish Dabas

Vice President, Capital One

A V Rahul

Director, Analytics, - Barracuda

Bhairav M

Senior Manager Data Science and Product Management

Bhargab Dutta

Chief Digital Officer, Centuryply

Deepa Mahesh

Head of Strategy & Operations, Board Member

Divesh Singla

SVP, Global Operations Services and Managing Director, India & Philippines, SignantHealth

Indrani Goswami

Director of Analytics, NYKAA

Ishu Jain

Head of Analytics

Kaushik Das

Managing Director, JCPenney

Krithika Muthukrishnan

Chief Data Science Officer, Scripbox

Madhu Hosadurga

Global Vice President, Enterprise AI, Schneider Electric

Madhurima Agarwal

Managing Director - Microsoft for Startups

Monica S Pirgal

Chief Executive Officer, Bhartiya Converge

Muthumari S

Global Head of Data & AI Studio

Nithya Subramanian

Senior Director Data & AI COE - Best Buy

Nitin Srivastava

Global Head of Data and Analytics, Dr. Martens plc

Pankaj Rai

Group Chief Data and Analytics Officer, Aditya Birla Group

Pankaj Srivastava

Partner, PwC

Praveen Sathyadev

Head - EU/UK Business Growth (VP) - Analytics, Insights and AI, Course5i

Ruchika Singh

Director, Data Science & Insights, Spotify

Satyakam Mohanty

Founder & Managing Partner, Wyser

Saurabh Agarwal

Chief Executive Officer

Saurabh Kumar

Director - Data Engineering

Sharmistha Chaterjee

Executive Engineering Manager - Head of Software and Systems Engineering, Commonwealth Bank

Shirsha Ray Chaudhuri

Director of Engineering

Srini Oduru

Head of IT Delivery and Operations, Cervello India

Sulabh Jain

Chief Analytics Officer

Sumon Mal

Head of Backend Engineering, Sony LIV

Supria Dhanda

Co-Founder & Managing Partner, Wyser

Swati Jain

Partner - Digital, AI & Analytics, Deloitte

Tushar Chahal

Chief Technology Officer, Numisma Bank

Tushar Sahu

Director Engineering, Google

Vidhi Chugh

AI Executive | Microsoft MVP

Vishal Nagpal

Director of Data and AI at Best Buy

Vishal Nagpal

Director of Data and AI at Best Buy

Vidhi Chugh

AI Executive | Microsoft MVP

Tushar Sahu

Director Engineering, Google

Tushar Chahal

Chief Technology Officer, Numisma Bank

Swati Jain

Partner - Digital, AI & Analytics, Deloitte

Supria Dhanda

Co-Founder & Managing Partner, Wyser

Sumon Mal

Head of Backend Engineering, Sony LIV

Sulabh Jain

Chief Analytics Officer

Srini Oduru

Head of IT Delivery and Operations, Cervello India

Shirsha Ray Chaudhuri

Director of Engineering

Sharmistha Chaterjee

Executive Engineering Manager - Head of Software and Systems Engineering, Commonwealth Bank

Saurabh Kumar

Director - Data Engineering

Saurabh Agarwal

Chief Executive Officer

Satyakam Mohanty

Founder & Managing Partner, Wyser

Ruchika Singh

Director, Data Science & Insights, Spotify

Praveen Sathyadev

Head - EU/UK Business Growth (VP) - Analytics, Insights and AI, Course5i

Pankaj Srivastava

Partner, PwC

Pankaj Rai

Group Chief Data and Analytics Officer, Aditya Birla Group

Nitin Srivastava

Global Head of Data and Analytics, Dr. Martens plc

Nithya Subramanian

Senior Director Data & AI COE - Best Buy

Muthumari S

Global Head of Data & AI Studio

Monica S Pirgal

Chief Executive Officer, Bhartiya Converge

Madhurima Agarwal

Managing Director - Microsoft for Startups

Madhu Hosadurga

Global Vice President, Enterprise AI, Schneider Electric

Krithika Muthukrishnan

Chief Data Science Officer, Scripbox

Kaushik Das

Managing Director, JCPenney

Ishu Jain

Head of Analytics

Indrani Goswami

Director of Analytics, NYKAA

Divesh Singla

SVP, Global Operations Services and Managing Director, India & Philippines, SignantHealth

Deepa Mahesh

Head of Strategy & Operations, Board Member

Bhargab Dutta

Chief Digital Officer, Centuryply

Bhairav M

Senior Manager Data Science and Product Management

A V Rahul

Director, Analytics, - Barracuda

Ashish Dabas

Vice President, Capital One

Arvind Balasundram

Executive Director, Commercial Insights & Analytics

Arpit Agarwal

Data Science Manager, Google

Anupam Gupta

Independent Consultant – AI/ML Product Development, Amplify Health

Ankit Mogra

Director – Insights & Analytics, Ather Energy

Anirban Nandi

Head of AI Products & Analytics (Vice President), Rakuten India

Aneel kumar

Global Chapter Leader - ICSS, DD&T

Anand Das

Chief Digital & AI Officer, TVS Motors

Alok Tiwari

Director of Analytics, Junglee Games

Akshay Kumar

Research & Analytics Leader

Aditya Khandekar

President, Corridor Platforms

Ready to Redefine Agentic Innovation in the AI Era?

Advance your career with IITM Pravartak's Advanced Certificate in AI Agent Workflows. Learn to design intelligent systems and multi-agent workflows with industry experts.

Apply Now

Frequently Asked Questions

We know you might have some questions before getting started in our platform

Program Overview & Eligibility

Learning Format, Faculty & Pedagogy

Curriculum & Tools

Career Pathways & Outcomes

Financials & Support

What is the name of the certificate program?

The program is called Advanced Engineering Program in AI Agent Workflows and Agentic Systems Development, offered by IITM Pravartak Centre of Excellence in collaboration with Futurense Technologies.

What is the duration of the program, and when does the first cohort begin?

The program duration is approximately 7 months (140+ hours), with the first cohort scheduled to begin as per the announced program start date.

What are the eligibility criteria for this program, and who should ideally enroll?

• Engineers interested in AI systems and automation
• Software professionals looking to build expertise in AI agents
• Data professionals working with AI and machine learning
• Product managers exploring AI-driven product development
• AI enthusiasts interested in agentic workflows and intelligent systems

How can I apply to the IITM Pravartak AI Agents and Agentic Workflows program?

Applicants can apply through the official Futurense admissions portal by submitting the application form along with the required documents.

When will the application process start?

The application process is currently open, and interested candidates can apply online as seats are limited.

Why is this program considered unique compared to other AI certificate programs?

The program focuses on AI agents, autonomous systems, and real-world agentic workflows, combining technical AI concepts with practical product and workflow implementation.

Is there a selection process for admission?

Yes. Admission typically requires meeting eligibility criteria and clearing a pre-screening or evaluation process.

What documents are required for application?

Applicants must submit identity proof, educational certificates, resume, and relevant professional documents as part of the application process.

Will there be any pre-screening exam for enrollment?

Yes, applicants may be required to complete a pre-screening assessment as part of the admission process.

Is coding experience required to qualify for the pre-screening exam?

Coding experience is helpful but not mandatory, as the program focuses on understanding AI systems and workflows along with practical implementation.

What documents should I keep ready during the application process?

Applicants should keep PAN, Aadhaar, educational documents, resume, and financial documents if applying for loan support.

What makes this certificate program particularly suitable for engineers and tech professionals?

The program combines AI engineering concepts with real-world agentic workflow implementation, helping professionals build skills required for next-generation AI-powered systems.

How is the teaching format structured for this hybrid program?

The program follows a hybrid format with live online sessions, hands-on learning, and a campus immersion experience.

What if I cannot take leave for campus immersion?

The campus immersion is scheduled toward the end of the program, allowing participants to plan in advance.

Will hostel accommodation be provided for outstation participants during immersion?

Yes, accommodation may be arranged for outstation participants, subject to availability.

Who is the program director, and why is their expertise important?

The program director provides academic leadership and ensures the curriculum remains aligned with the latest advancements in AI and agentic systems.

What makes IITM Pravartak a leader in technological education, particularly in AI and data science?

IITM Pravartak is associated with IIT Madras and focuses on cutting-edge research, AI innovation, and industry collaboration.

How do industry leaders and the Futurense Leadership Council (FLC) contribute to the program?

Industry experts conduct live sessions, masterclasses, mentorship programs, and real-world case discussions, ensuring strong industry relevance.

What areas of AI and agentic workflows does the program cover?

The program covers AI agents, generative AI, autonomous systems, agent orchestration, and real-world AI workflow implementation.

What tools and platforms are included in the program?

Participants learn tools such as ChatGPT, Claude, Gemini, LangChain, AI development frameworks, and product development tools.

Why are AI agents considered the next big evolution in AI technology?

AI agents enable autonomous decision-making, task execution, and intelligent workflow automation, making them essential for scalable AI systems.

What are the key modules in the program related to AI agents and workflows?

Modules include AI foundations, generative AI applications, agentic systems design, multi-agent collaboration, workflow automation, and AI-powered product development.

How does the program allow participants to specialize in specific domains?

Participants can apply AI agent concepts to domains such as fintech, SaaS, healthcare, e-commerce, and enterprise automation.

What practical projects or hands-on outcomes are included in the program?

Hands-on work includes building AI agents, designing automated workflows, creating AI-driven prototypes, and developing AI-powered MVPs.

What is the significance of learning multi-agent systems and agent collaboration?

Multi-agent systems allow multiple AI agents to collaborate, automate complex workflows, and improve decision-making efficiency.

What is the difference between traditional AI, generative AI, and agentic AI?

Traditional AI focuses on predictive models, generative AI creates new content, and agentic AI enables autonomous systems capable of planning and executing tasks.

What job roles can participants pursue after completing this program?

Participants can pursue roles such as AI Engineer, AI Agent Developer, GenAI Specialist, AI Product Manager, Automation Architect, and AI Solutions Consultant.

How do skills in generative AI and agentic AI impact salary and job opportunities?

Professionals with these skills often experience higher salary growth and increased demand across AI-driven companies.

How does this program align with the growing adoption of AI agents in companies?

The program prepares professionals to design and deploy AI agents for real-world enterprise workflows and product systems.

How will this program help future-proof careers in a rapidly evolving AI market?

It equips professionals with skills in AI systems design, automation, and agentic architectures, which are rapidly becoming industry standards.

How are agentic AI systems used across industries such as healthcare, manufacturing, and telecom?

Examples include AI healthcare assistants, intelligent manufacturing automation, and AI-powered customer support systems in telecom.

What is the projected market value of generative AI and enterprise adoption trends?

The generative AI market is projected to reach over $1 trillion in value by 2032 , with a large percentage of enterprises prioritizing adoption.

How does India rank globally in AI startups and innovation?

India is among the top global hubs for AI startups, with rapid growth in generative AI and AI agent development.

What is the program fee, and what financing options are available?

The program fee is announced during admissions and includes flexible EMI and loan options through financial partners.

Is there an additional cost for attending the campus immersion?

Yes, there may be an additional immersion fee of ₹10,000, which covers participation and campus-related expenses.

What is the payment schedule and process?

Participants must pay an application deposit first, followed by the remaining program fee within the specified timeline after receiving the offer letter.

Can I self-fund the program?

Yes, candidates can self-fund the program either fully or partially.

Does Futurense offer loan support?

Yes, Futurense partners with financial institutions to provide loan and EMI options.

What are the interest rates on education loans?

Interest rates depend on the financial partner and repayment plan, and are generally competitive.

What is the program's fee, and what financing options are available?

The program fee is ₹1,10,500 + 18% GSTand possible scholarships for deserving candidates.