PG Diploma Programs in 3 Emerging Fields:

This is a fully residential, intensive 6-month PG Diploma jointly offered by IIT Gandhinagar and Futurense Technologies. It blends advanced engineering with modern AI/ML/GenAI to produce job-ready professionals in critical technology domains, built by IIT Gandhinagar x Fortune-500 Industry Leaders.

The program lasts six months and is fully residential at the IIT Gandhinagar campus. It comprises 600+ hours of experience, designed to provide capabilities equivalent to 2 years of professional experience. The program is highly exclusive, accepting only 60 students by invitation after the selection process.

Yes, graduates receive IIT Gandhinagar Executive Alumni Status.

Yes, 100% Placement Support is provided, subject to conditions which include maintaining a 7.0+ CGPA.

Candidates must hold a Bachelor’s degree in CS/IT/ECE/Maths or related technical disciplines. Final-year UG students or 3-year technical diploma holders with relevant experience may be considered at the institute’s discretion. A foundational comfort level with Python basics and 10+2 math (linear algebra & probability) is expected.

Yes, a pre-screening/qualifier test is mandatory to assess technical readiness. Topics covered are: Mathematical Foundations, Tech & Computing Fundamentals, Logical Reasoning, Data Interpretation, Verbal Reasoning, and a Coding Section (Python, SQL).

Evaluation uses a continuous assessment methodology with a minimum passing score of 50%. Grades typically weigh: End-term (35%), Quizzes (30%), Mid-term (25%), and Attendance (10%).

A PG Diploma certificate co-branded by IIT Gandhinagar and Futurense Technologies, upon meeting all academic and conduct requirements.

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Yes. Upon formally signing the program undertaking, participants will be issued an official IIT Gandhinagar ID card and a corresponding official email ID for the duration of the six-month program. These credentials are provided to facilitate all academic and program-related activities.

The following documents are necessary to complete your application for the PG Diploma in AI / Agentic AI Engineering:

1. Identity Proof: Aadhaar Card and 1.PAN Card.
2. Personal Record: Proof of Date of Birth (DOB).
3. Academic Records:
- 10th Standard Marksheet.
- 12th Standard Marksheet.
- Graduation Marksheets/Degree Certificate (or the latest semester transcripts for final-year students).
4. Professional Summary: A comprehensive resume (CV).
5. Employment Verification: Employment proofs (required only if applicable to your profile).

The admissions process is highly selective, designed for The Chosen 60. The process is as follows:

1. Apply Online: Submit your application and documents.
2. Round 1: AINPT - IIT GN: A mandatory 90-minute exam testing technical, aptitude, and problem-solving skills.
3. Round 2: Panel Interview: Evaluation by an IIT faculty + industry mentor panel to assess your capability and commitment.
4. Offer & Enrollment: You receive an invite once selected.

Yes, the program is fully residential. On-campus hostel accommodation is provided for the entire duration. Access to mess facilities and various campus amenities is available as per standard institute norms.

While the full schedule is dynamic, the immersive weekdays generally follow a structured pattern, balancing scheduled lectures, dedicated laboratory or practical sessions, and protected blocks of time for guided capstone project work. The detailed weekly timetable will be provided during your final onboarding phase.

Short breaks are aligned to the IIT Gandhinagar’s academic calendar. Leave follows institute rules and the academic schedule; excessive absence may impact eligibility and grades.

Yes, education finance partners are typically available for eligible candidates, allowing the fee to be paid via EMI plans through these partners.

Financial Aid and Documentation

1. Loan/EMI Availability: Yes, loan and EMI (Equated Monthly Installment) options are available for eligible candidates through
Futurense's partnerships with established education financiers (e.g., Propelld, Avanse, IDFC, ICICI).

2. Required Documentation for Financing: The typical documentation required for loan processing includes:
Aadhaar Card and PAN Card.
Bank statements.
Payslips (if currently employed).
Academic records.
A recent photograph.

Policies for withdrawal, deferral, and refunds follow the institute's guidelines shared in the official admission offer. Qualifier fees are non-refundable.

Withdrawal Policy

1. Governing Rules: Program withdrawal is strictly governed by the institute’s official academic and fee policies, which are clearly communicated in the admission offer.
2. Refunds and Deferrals: Any requests for potential refunds or deferrals of the program will strictly follow those established institutional rules.
3. Qualifier Fee Note: Please note that the initial qualifier test fee is non-refundable under all circumstances.

Full-Stack Developer, Java Developer, Backend Engineer (Spring Boot), Frontend Engineer (React/Next.js), DevOps/MLOps Engineer, AI-Augmented Software Engineer, and Intelligent Systems Architect.

Every stage of the SDLC is taught with AI assistance—using tools like Copilot/CodiumAI for coding & tests, and ChatGPT/LangChain for APIs and orchestration. It includes cloud-native deployment, AIOps/MLOps, and an AI-integrated capstone.

Core modules cover: Foundations (Java/JavaScript), Clean Code (SOLID/AI code reviews), Backend (Spring Boot/LangChain), Frontends (React/Next.js/AI UX), DevOps & MLOps (CI/CD, Docker/K8s, AIOps), and AI-Driven System Design & Security.

The curriculum includes guidance for achieving certifications like AZ-204 (Developing Solutions for Microsoft Azure).

Data Engineer, Cloud Data Engineer, Analytics Engineer, Data Platform Engineer, MLOps Engineer, and Applied/Engineering-focused Data Scientist.

Strong engineering depth covering ETL/ELT, batch + streaming, big data (Hadoop/Spark), cloud DWH (Redshift/BigQuery/Synapse), and MLOps. The focus is on scalability, reliability, and governance in a production-grade capstone.

Key tools include: Python, SQL, orchestration (Airflow), data streaming (Kafka), big data (Hadoop/Spark), cloud DWH (Redshift/BigQuery/Synapse), data lake formats (Delta/Hudi/Iceberg), MLOps (MLflow/W&B), and visualization (Power BI/Tableau).

Role-aligned interview prep focusing on SQL/DSA for data and pipeline/system design, plus certification guidance (e.g., GCP Professional Data Engineer, Azure DP-203, Databricks Data Engineer Associate).

It’s product- and deployment-oriented: end-to-end ML/DL + LLMs + multi-agent systems (LangChain, LangGraph, AutoGen, CrewAI), with strong hands-on labs and a production-grade capstone—so you graduate with job-ready skills and a portfolio.

Deep Learning, NLP for GenAI, LLM Mastery & Prompt Engineering, Production AI (cloud/MLOps/CI-CD), Agentic AI with LangChain, and Advanced multi-agent systems with LangGraph/AutoGen/CrewAI.

Yes, a bridge course is provided to solidify foundational knowledge. Modules include: Mathematical Foundations for AI, Python Programming Basics, Vibe Coding Fundamentals, and Prompt Engineering & Generative AI Essentials.

The curriculum integrates specialized job-preparation modules, including dedicated sessions on competitive coding and techniques for technical interview preparation.

A production-grade capstone showcasing ML/DL + LLM + Agentic pipelines, CI/CD, cloud deployment, observability, and governance—demonstrable on GitHub.