What is the Executive Post Graduate Certificate in Quantum Computing & AI?
Key Highlights: Executive Post Graduate Certificate in Quantum Computing & AI
Why Choose the IIT Kharagpur Quantum Computing & AI Course?
This Executive Post Graduate Certificate in Quantum Computing & AI program helps you to apply quantum computing principles to AI and ML by making a good understanding of algorithms, hardware limitations, and the problems these methods can solve.
Some key features of this program among other IIT Kharagpur online courses are:
Credibility of IIT Kharagpur: Being the first Indian Institute of Technology in India, IIT Kharagpur ranks fifth in Engineering according to NIRF 2025 owing to a legacy of 75 years of academic excellence.
Faculty from IIT Kharagpur: The course includes expertise of faculty members in quantum physics and computational quantum chemistry.
Practice in Quantum Hardware: The course covers practical knowledge about quantum circuits hardware as well as simulators.
Quantum Computing & AI: The course covers quantum algorithms, hybrid quantum computing, and quantum machine learning.
Individual Capstone: You will come up with an idea, try it out, check the results, and give your feedback.
Executive Alumni Status: Once you complete the program, you will become a part of the IIT Kharagpur Executive Education Alumni Network.
What Will You Learn In This Quantum Computing and AI Course?
This Executive Post Graduate Certificate in Quantum Computing & AI is of total 24 weeks and begins with a 3 week foundational bridge component, which helps you to build your basics, if you are new to this field.
This IIT Kharagpur AI course have these modules:
Bridge: Foundations
Weeks -3 to 0 | Asynchronous learning with optional live support
Topics Covered:
Linear algebra, complex numbers, and probability
Python, NumPy, SciPy, Matplotlib, Jupyter, and Git
Machine learning and optimization basics
Cryptography, digital signatures, key exchange, and TLS
Skills Acquired:
Using Python for scientific computing
Applying mathematical foundations used in quantum computing
Understanding machine learning, optimization, and cryptography basics
Course 1: Quantum Foundations and Circuit Engineering
Weeks 1–4
Topics Covered:
Quantum states, measurement, gates, circuits, and entanglement
Qiskit, circuit simulation, and real quantum hardware
Quantum algorithms, including Deutsch–Jozsa and Grover's search
Qubit technologies, circuit transpilation, and noise
Skills Acquired:
Building and analysing quantum circuits
Using Qiskit to simulate and run circuits
Implementing basic quantum algorithms
Course 2: Hybrid Quantum Computation
Weeks 5–8
Topics Covered:
QUBO and Ising models for optimization problems
QAOA, VQE, and quantum simulation
Quantum and classical optimization methods
Hybrid CPU, GPU, and quantum workflows with cloud platforms
Skills Acquired:
Formulating optimization problems for quantum methods
Building and evaluating QAOA and VQE workflows
Comparing quantum results with classical approaches
Course 3: Quantum Hardware and NISQ Computing
Weeks 9–11
Topics Covered:
Qubit technologies, hardware connectivity, and circuit mapping
Decoherence, noise, fidelity, and quantum channels
Error mitigation methods
Quantum error-correction codes and fault-tolerant computing
Skills Acquired:
Understanding qubit technologies and hardware constraints
Assessing noise and error-mitigation methods
Understanding physical and logical qubits
Course 4: Applied Quantum Machine Learning
Weeks 12–15
Topics Covered:
Data encoding and quantum feature maps
Quantum kernels, variational classifiers, and quantum neural networks
PennyLane, PyTorch, trainability, and quantum generative models
Model evaluation against classical baselines
Skills Acquired:
Encoding data for quantum machine learning
Building quantum machine learning models
Evaluating results against classical methods
Course 5: Post-Quantum Cryptography and AI Security
Weeks 16–18
Topics Covered:
Quantum threats to public-key cryptography and AI data
NIST standards: ML-KEM, ML-DSA, and SLH-DSA
Hybrid cryptography and security of AI systems
Cryptographic migration and Quantum Key Distribution
Skills Acquired:
Understanding quantum-related security risks
Identifying systems that may need quantum-resistant protection
Understanding post-quantum methods and migration planning
Course 6: Quantum Strategy and Individual Capstone
Weeks 19–24
Topics Covered:
Quantum applications and use-case evaluation
Comparison with classical methods, including cost and resource needs
Platform and vendor assessment
Capstone development and final presentation
Skills Acquired:
Identifying suitable quantum-computing problems
Comparing quantum approaches with classical baselines
Presenting technical findings and limitations
Capstone: Design and Implement a Quantum Computing Solution
The individual capstone project encourages participants to identify a problem, come up with a solution that uses quantum mechanics principles, and perform a benchmark with a classical solution. Participants report their experiments together with the identified challenges. They present the paper and do a viva individually.
Capstone Focus:
Select and formulate a problem
Build and test a quantum prototype
Compare results, resources, and costs
Document findings and limitations
Present the project and complete a viva
Tools and Frameworks Covered in Executive Post Graduate Certificate in Quantum Computing & AI
1. Quantum Circuit Design and Execution
Quantum circuits are built, the quantum computers are simulated and finally quantum circuits are executed as quantum circuits.
Qiskit and OpenQASM 3
IBM Quantum
qBraid and Qniverse
2. Quantum Machine Learning and Scientific Computing
Data is being prepared, experiments are conducted and models in machine learning and scientific computing fields are developed by quantum technologies.
Python, NumPy, and SciPy
Matplotlib, Jupyter, and Git
PennyLane and PyTorch
3. Hybrid Computing and Cloud Platforms
Focus on researching and developing computing workflows that utilize both classical (traditional) processors and quantum resources.
NVIDIA CUDA-Q
IBM Quantum Runtime
AWS Braket and Azure Quantum
Quantum annealing platforms; CPUs and GPUs
4. Optimization and Quantum Algorithms
Working with methods for optimization and simulation.
QUBO and Ising models
QAOA and VQE
Quantum kernels and variational classifiers
MILP, CP-SAT, and metaheuristics
5. Post-Quantum Cryptography
Understanding standards used in quantum-resistant security planning.
ML-KEM (FIPS 203)
ML-DSA (FIPS 204)
SLH-DSA (FIPS 205)
Cryptographic libraries, hybrid cryptography, and migration planning
Who Should Enrol in the Executive Post Graduate Certificate in Quantum Computing & AI from IIT Kharagpur?
This program falls among the best IIT kharagpur courses for working professionals. It is suitable for you if you are a:
AI and Machine Learning Professionals
If you are currently working with machine learning models and want to learn about quantum kernels, variational classifiers, hybrid workflows, and comparison with classical baselines.
Software and Data Engineers
If you are working in software or data engineering, this IIT Kharagpur AI course will help you learn the basics of programming a quantum computer, circuit design, algorithms, and various quantum platforms.
Science and Engineering Professionals
If your current work involves modelling, simulation or computational problems, this course will help you to explore the quantum algorithms, optimization, and hardware limitations.
Researchers and R&D Professionals
If you work in research or technology development, this course will help you to evaluate quantum simulation, machine learning, hardware, and its potential applications.
Cybersecurity Professionals
If you are currently working in cybersecurity or cryptography, this course will help you to study quantum threats, post-quantum standards, and migration planning.
Eligibility Criteria for the IIT Kharagpur Executive Post Graduate Certificate in Quantum Computing & AI
Applicants should meet the following academic and technical requirements for the IIT Kharagpur Quantum Computing and AI course:
Graduation with a minimum of 50% marks
B.Tech/M.Tech or B.E/M.E in CS, IT, AI, or ECE are preferred
B.Sc/M.Sc in Computer Science, Mathematics, or Statistics
MCA/BCA
Candidates from other disciplines must have a minimum of 2 years of experience in the technology field
Prerequisite:
Before enrolling, candidates should be comfortable with:
Writing Python functions and using basic data structures
Undergraduate mathematics, including linear algebra and probability
Basic statistics used in machine learning
Prior quantum-computing knowledge is not required.
IIT Kharagpur Executive Post Graduate Certificate in Quantum Computing & AI Fees Structure
The Executive Post Graduate Certificate in Quantum Computing & AI fees structure is below:
If you are looking for a best course which cover quantum computing along with AI among the IIT kharagpur courses online, this course combines both in a single fee structure.
How To Apply For This IIT Kharagpur Quantum Computing And AI Course?
The process for applying in this Executive Post Graduate Certificate in Quantum Computing & AI is simple and can be completed only in three steps:
Fill in your details and complete the application: Submit the required information to apply for the program.
Get shortlisted and receive the offer letter: Shortlisted applicants receive an offer letter with the next steps.
Block your seat: To finalize your enrollment and get a confirmed seat, pay the seat-blocking amount and that's it you are in.