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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery | Frequency Of Classes |
|---|---|---|---|
| English | Self Study, Virtual Classroom, Campus Based/Physical Classroom | Video and Text Based | Weekends |
Course Overview
The Certification In Quantum Computing and Machine Learning course is a six months executive course designed to equip professionals with the knowledge and skills to navigate the emerging landscape of quantum technologies and their integration with machine learning. This Certification In Quantum Computing and Machine Learning course is being offered by IIT Delhi in collaboration with TimesPro. This Certification In Quantum Computing and Machine Learning course provides a comprehensive understanding of quantum computing principles, quantum algorithms, and their applications in machine learning.
The participants will delve into the nuances of quantum mechanics, explore the differences between classical and quantum computing and gain hands-on experience with quantum algorithms. This Certification In Quantum Computing and Machine Learning course is ideal for participants with a background in mathematics and programming and a keen interest in emerging technologies.
The Highlights
- Six-month intensive programme
- Offered by IIT Delhi
- E-certificate from CEP, IIT Delhi
- Campus immersion
- 70 hours of live sessions
- Expert faculty
Important dates
Course Commencement Date
Start Date : 29 Jun, 2025
Programme Offerings
- Offered by IIT Delhi
- Campus immersion
- E-certificate from CEP
- IIT Delhi
- direct-to-device learning
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIT Delhi |
The fees for the Certification In Quantum Computing and Machine Learning course is :
Fees components | Amount |
Programme Fee | Rs. 1,79,000 |
GST@18% | Rs. 32,200 |
Total | Rs. 2,11,220 |
Instalments Schedule:
Instalment | Date | Amount |
Application Fee** | To be paid at the time of registration | Rs. 1,000 |
1st Instalment | Within 5 days of offer rollout | Rs. 44,000 |
2nd Instalment | 29th July, 2025 | Rs. 45,000 |
3rd Instalment | 29th August, 2025 | Rs. 45,000 |
4th Instalment | 28th September, 2025 | Rs. 45,000 |
Eligibility Criteria
To enrol in the Certification In Quantum Computing and Machine Learning course, the participants must have completed their graduation in B.Tech/BE, BCA/MCA, B.Sc in all streams, BA/MA in mathematics.
What you will learn
The participants will understand the foundation principles of quantum computing, including quantum bits, superposition, entanglement and quantum gates. The Certification In Quantum Computing and Machine Learning course will delve into various quantum algorithms, such as Grover's and Shor's algorithms, and their applications in solving complex computational problems.
The participants will explore the integration of quantum computing machine learning, examining how quantum algorithms can enhance machine learning models. Topics will include quantum linear regression, quantum neural networks, and variational quantum algorithms. By the end of the Certification In Quantum Computing and Machine Learning course, participants will have a robust understanding of how to leverage quantum computing in the realm of machine learning.
Who it is for
The target audience for the Certification In Quantum Computing and Machine Learning course includes:
Admission Details
Follow the steps given below to take admission in Certification In Quantum Computing and Machine Learning:
Step 1: Visit the course page : https://timespro.com/executive-education/iit-delhi-certification-in-quantum-computing-and-machine-learning
Step 2: After ensuring that you fulfil the eligibility criteria, scroll down the page to fill out the application form.
Step 3: Enter your name, phone number, email ID, DOB, the exam percentage in 10th, 12th and graduation.
Step 4: Finally, select your centre, city and state and click on ‘Enquire now’ to submit the form.
The Syllabus
- Quantum Bits
- Dirac Notation
- Single and Multiple Qubit Gates
- No Cloning Theorem
- Quantum Teleportation
- Quantum Interference
- Quantum State
- Quantum Evolution
- Quantum Measurement
- POVM Operators
- Density Operators
- Hamiltonian Simulation and Trotterization
- Cirq
- Qiskit
- Quantum Random Number Generator
- Deutsch-Jozsa Algorithm Implementation
- Bernstein-Vajirani Algorithm
- Bell’s Inequality Test
- Simon’s Algorithm
- Grover’s Algorithm
- Quantum Fourier Transform
- QFT Implementation in Cirq
- Quantum Phase Implementation
- Quantum Phase Estimation in Cirq
- Shor’s Period Finding Algorithm and Factoring
- Hidden Subgroup Problem
- HHL Algorithm
- HHL Algorithm Implementation using Cirq
- Quantum Linear Regression
- Quantum Swap Test Subroutine
- Swap Test Implementation
- Quantum Euclidean Distance Calculation
- Quantum K-Means Clustering
- Quantum Principal Component Analysis
- Quantum Support Vector Machines
- SVM Implementation using Qiskit
- Hybrid Quantum-Classical Neural Networks
- MNIST Classification using Hybrid Quantum-Classification Neural Network
- Quantum Neural Network for Classification of Near-Term Processors
- MNSIT Classification Using TensorFlow Quantum
- Variational Quantum EigenSolver
- Expectation Computation
- Isling Model and its Hamiltonian
- Isling Model for a Quantum System
- Implementation of the VQE Algorithm
- Quantum Max-Cut Graph Clustering
- Quantum Adiabatic Theorem
- Quantum Approximate Optimisation Algorithm
- Quantum Random Walk
Evaluation process
The participants are required to complete assessments and a capstone project to earn the certification. These evaluations are designed to test the understanding and application of quantum computing and machine learning concepts covered in the course.