Online PG Diploma in Advanced Communication Engineering with Quantum and AI Integration ( Batch 2 )
Features
Programme Overview
The Online Postgraduate Diploma in Advanced Communication Engineering with Quantum and AI Integration is designed to equip professionals with advanced knowledge and practical skills at the convergence of three transformative technologies: Artificial Intelligence (AI), Quantum Networking, and Wireless Communications. This multidisciplinary programme blends theoretical concepts with hands-on applications, enabling learners to tackle complex challenges in modern telecommunications, intelligent systems, and secure network infrastructures.
By integrating machine learning, advanced wireless communication systems, quantum communication protocols, and secure networking techniques, the programme empowers participants to stay ahead in the rapidly evolving tech landscape.
₹ 4,40,000 + 18 % GST
Registration Closed
Class Schedule
Session Timings: 8:30 AM – 1:15 PM 3-hour sessions conducted on Saturdays and Sundays
Eligibility Criteria
BE/BTech/MSc/MCA graduates in Electronics & Communication Engineering (ECE), Electrical Engineering (EE), Computer Science & Engineering (CSE), Information Technology (IT), Applied Physics / Engineering Physics, Telecommunications Engineering, Mathematics / Applied Mathematics, Data Science / AI & ML or closely related academic disciplines with minimum 60% marks and 6 CGPA or
Working professionals having greater than 2 years of experience with a minimum 55% marks or 5.5 CGPA or
Working professionals having greater than 5 years of experience with a minimum 50% marks or 5 CGPA
Programme Highlights
Online PG Diploma From Prestigious IIT Delhi
Gain Affiliate Alumni Status From IIT Delhi
First-Of-Its-Kind Curriculum Combining AI, Quantum Networking, And Advanced Wireless Communications
Rich Peer Group Learning And Networking
Earn Up To 27 Credits From IIT Delhi, Which Can Be Saved In The Academic Bank Of Credits (ABC)
Industry-Relevant 60 Hours Capstone Project
Hands-On Lab Experience
1 Day Campus Immersion Opportunity
Programme Modules
Course 1: Introduction to Machine Learning (3 Credits)
Supervised and unsupervised learning
Neural networks and deep learning
Reinforcement learning for network optimisation
ML for signal processing and noise reduction
AI-driven network traffic prediction and anomaly detection
Application of ML in 5G and IoT systems
Learning outcomes
Understand supervised and unsupervised learning, deep learning, and reinforcement learning.
Apply machine learning for signal processing, noise reduction, and network traffic prediction.
Implement AI-driven anomaly detection in communication systems.
Explore ML applications in 5G/6G and IoT networks for performance optimisation.
Course 2: Wireless Communications (3 Credits)
Cellular network evolution (4G, 5G, and 6G)
Channel modeling and estimation
Modulation and coding schemes
Spectrum efficiency and resource allocation
Interference management techniques, IoT/M2M communication protocols
Learning outcomes
Explain cellular network evolution (4G, 5G, 6G) and their technical advancements.
Understand channel modeling, modulation, coding, and spectrum efficiency in wireless networks.
Develop interference management techniques for IoT/M2M communication.
Analyse resource allocation strategies for optimising wireless communications.
Course 3: Selected Topics in Communication Systems and Networking-I (3 Credits)
Classical Security
Quantum entanglement and teleportation in communication
Quantum key distribution (QKD) protocols
Quantum repeaters and networking nodes
Integration of Quantum systems with classical networks
Applications of Quantum communication in secure networks
Learning outcomes
Understand the principles of quantum entanglement and quantum key distribution (QKD).
Analyse the role of quantum repeaters and quantum networking nodes in secure communication.
Explore hybrid classical-quantum networking models for data security.
Study real-world applications of quantum communication in secure networks.
Course 4: Wireless Communication Laboratory (3 Credits)
Basics of MATLAB/Python
To plot BER versus SNR plots for BPSK, QPSK, 16-QAM constellations over Rayleigh fading channel
To plot average capacity versus SNR plot for M-Ary constellations over Rician Fading Channel
To implement OFDM transmitter and receiver
To implement supervised learning detector for wireless channels
To evaluate performance of wireless channels using LDPC codes
To implement ISAC system in MATLAB
To implement QKD protocols
Learning outcomes
Learners will understand key concepts of quantum communication, including entanglement, teleportation, and Quantum Key Distribution (QKD) protocols for secure data transmission. They will explore the role of quantum repeaters and networking nodes in enhancing communication efficiency and analyse the integration of quantum systems with classical networks. Gain expertise in Software-Defined Radios (SDRs) and their applications.
Course 5: MIMO Wireless Communications (3 Credits)
Introduction to Space-Time Diversity
MIMO Channel
MIMO Information Theory
Error probability analysis
Transmit diversity and space time coding
Linear STBC design
Differential coding for MIMO
Precoding
Multiuser MIMO
Massive MIMO
Recent advancement in MIMO
Learning outcomes
Understand the fundamentals of MIMO systems, spatial multiplexing, and diversity gain
Implement MIMO systems for improved spectral efficiency and network reliability
Develop real-time signal processing techniques for 5G/6G networks
Test and analyse advanced beamforming techniques in wireless communication
Course 6: Selected Topics in Communication Systems and Networking-II (3 Credits)
Key 5G technologies
5G numerology
5G frame structure
Physical downlink shared channel(PDSCH)
Physical Downlink Control Channel(PDCCH)
Tansmit chain
Demoulation reference signal(DM-RS)
Sounding Reference Signal(SRS)
MIMO in 5G
Learning outcomes
Analyse and apply the principles of standards-based wireless system design
Design and implement a 5G-compliant wireless communication system using MATLAB
Evaluate and discuss current trends and emerging technologies in the evolution of 5G networks
Analyse energy-efficient and green communication strategies in wireless networks
Implement advanced beamforming algorithms for better network performance
Course 7: Selected Topics in Information Processing-I (3 Credits)
Advanced quantum error correction codes
Post-quantum cryptographic algorithms
Hybrid classical-quantum communication systems
Fault-tolerant quantum network designs
Quantum-enhanced protocols for secure data transmission
Learning outcomes
Understand advanced quantum error correction codes and post-quantum cryptography
Explore hybrid classical-quantum communication systems for secure data transmission
Design fault-tolerant quantum network architectures for real-world applications
Implement quantum-enhanced security protocols for future communication systems
Course 8: Major Project Part-I (Communication Engineering) (6 Credits)
Practical project work on quantum communication, network security, or advanced wireless systems.
Hands-on experimentation with quantum key distribution (QKD), hybrid classical-quantum systems, and testing of new communication protocols.
Learning outcomes
Apply theoretical concepts to practical projects in quantum communication, network security, or advanced wireless systems.
Gain hands-on experience with Quantum Key Distribution (QKD), hybrid classical-quantum systems, and the testing of new communication protocols.
Enhance problem-solving skills, research capabilities, and technical proficiency in cutting-edge communication technologies.
Total Credits: 27 credits
NOTE: The sessions will be delivered by IIT Delhi faculty and Industry Experts, bought by the Programme Coordinator only.
**Kindly Note: Curriculum is subject to change and modification, as per the requirements of the programme. IIT Delhi and the Programme Coordinator’s decision will be final.
Online PG Diplomas are the academic programme of IIT Delhi, and there is no campus placement or assistance provided from IIT Delhi in these programmes.
The evaluation of minor projects is subject to the faculty's discretion, based on academic guidelines and instructional objectives.
Assessment criteria may vary depending on the nature of the project and its alignment with the course framework.
Basics of MATLAB/Python
To plot BER versus SNR plots for BPSK, QPSK, and 16-QAM constellations over a Rayleigh fading channel
To plot average capacity versus SNR for M-ary constellations over a Rician fading channel
To implement an OFDM transmitter and receiver
To implement a supervised learning detector for wireless channels
To evaluate the performance of wireless channels using LDPC codes
To implement an ISAC system in MATLAB
To implement and visualise QKD protocols using the VisualQKD Pro simulator
Software Tools-Visual QKD Pro Simulator
VisualQKD Pro is an advanced, easy-to-use simulation platform that brings Quantum Key Distribution (QKD) to life through real-world-accurate modeling and intuitive visualization. Designed and validated within IIT Delhi’s academic ecosystem, it mirrors practical QKD behavior—matching noise effects, QBER trends, and eavesdropping scenarios with high fidelity. Backed by multiple research white papers, VisualQKD Pro simplifies complex quantum concepts and makes learning immersive, while remaining powerful enough for serious research. Its clean interface, actionable analytics, and exportable results make it a versatile tool for education, training, and R&D in quantum communication and quantum computing.
Software Tools- VisualML Lab Pro
VisualML Lab Pro is a powerful yet remarkably easy-to-use AI/ML platform that transforms data analysis into a fully visual experience. With its drag-and-drop pipeline designer, integrated visualizations, and comprehensive library of ML algorithms and deep-learning methods, the tool enables experts to quickly interpret raw data patterns and select the most suitable algorithm for optimum learning performance and model behavior. At the same time, its intuitive interface and real-time visual feedback significantly accelerate the learning curve for beginners, helping them grasp complex concepts without extensive coding. Visual ML Pro effectively bridges practical engineering and machine-learning theory, making it an ideal companion for education, research, and industry-ready AI development.
Learning Outcomes
Apply AI & ML for Next-Gen Communication Networks
Master Advanced Wireless Communication Systems
Achieve Proficiency in Quantum Communication & Security
Develop Hands-on Technical & Research Skills
Bridge Academia & Industry with Real-World Applications
Tools
Machine Learning
AI
Python
Qiskit
MATLAB
Programme Coordinator
Professor Manav Bhatnagar
Professor
Department of Electrical Engineering
Indian Institute of Technology Delhi
Prof. Manav Bhatnagar is currently a Professor with the Department of Electrical Engineering, IIT Delhi, New Delhi, India, where he is also a Brigadier Bhopinder Singh Chair Professor. He holds a global rank of 517 in the area of Networking and Telecommunications and features among the top 2% of scientists in a global list compiled by the prestigious Stanford University. He is a Fellow of IET, INAE, NASI, IETE, and OSI. He has received the prestigious NASI-Scopus Young Scientist Award, the Shri Om Prakash Bhasin Award, the Prof. Vikram Sarabhai Research Award, and the Prof. P. C. P Bhatt Faculty Research Award (IIT Delhi). He has been an Editor of the IEEE Transactions on Wireless Communications from 2011 to 2014. Currently, he is an Editor of the IEEE Transactions on Communications. He has published more than 120 high-quality IEEE journal papers, of which 10 are single-authored. His research interests include MIMO systems, FSO communication, satellite communications, quantum communication, 5G, 6G, and machine learning.
Professor Abhishek Dixit
Associate Professor
Department of Electrical Engineering
Indian Institute of Technology, Delhi
Prof. Abhishek Dixit received his M.Tech. degree in Opto-electronics and Optical Communication from the Indian Institute of Technology (IIT) Delhi in 2010, and his Ph.D. in Computer Science Engineering from the Department of Information Technology (INTEC), Ghent University, Belgium, in 2014.
He is currently an Associate Professor in the Department of Electrical Engineering at IIT Delhi, a position he has held since 2022. Prior to this, he served as an Assistant Professor at IIT Delhi from 2015 to 2022. Before joining IIT Delhi, he worked as an Assistant Professor at IIT Mandi (July–December 2015) and as a Post-doctoral Researcher at Ghent University (December 2014 – June 2015). At IIT Delhi, Prof. Dixit teaches courses in Optical Communications, Signal Processing, Communications Engineering, and Networking. He has also delivered an NPTEL course on Principles of Digital Communications.
Prof. Dixit leads active research efforts in Optical Communications and Networking, and his recent work explores the integration of Machine Learning techniques to enhance both conventional and quantum communication systems. He has been involved in numerous national research projects and has undertaken multiple consulting assignments in the area of railway signalling.
He has published over 30 papers in leading international journals, including IEEE JSAC, IEEE Communications Magazine, Journal of Lightwave Technology, Journal of Optical Communications and Networking, IEEE Transactions on Network and Service Management, IEEE Access, and IEEE Open Journal of the Communications Society, among others. Additionally, he has presented over 50 papers at international conferences. Prof. Dixit is also credited with three successful technology transfers in the areas of Free-Space Optics (FSO), LiFi, and software stacks for smart meters.
Programme Faculty
Professor Saif K. Mohammed
Associate Professor
Department of Electrical Engineering
Indian Institute of Technology, Delhi
Prof. Saif K. Mohammed is a distinguished academic in electrical engineering, currently a Professor at IIT Delhi. He holds a B.Tech. in Computer Science from IIT Delhi (1998) and a Ph.D. in Electrical and Communication Engineering from IISc Bangalore (2010). With experience in both academia and industry, he has worked at Philips Semiconductors, Ishoni Networks, and Texas Instruments before transitioning to academia at Linköping University, Sweden, and later IIT Delhi (2013). His research focuses on communication theory, wireless communications, OTFS modulation, and large MIMO systems for 5G. He has 27 IEEE journal papers, one IET journal paper, four US patents, and five filed Indian patents.
Professor Harshan Jagadeesh
Associate Professor
Department of Electrical Engineering
Indian Institute of Technology, Delhi
Prof. Harshan Jagadeesh is an Associate Professor in the Department of Electrical Engineering, Indian Institute of Technology Delhi. He is also the co-coordinator of the center of excellence on cybersecurity and information assurance at IIT Delhi. Prior to joining IIT Delhi, he worked as a Researcher in the CyberSecurity group at Advanced Digital Sciences Center, Singapore. Before that he worked as a Research Fellow in the Division of Mathematical Sciences, Nanyang Technological University, Singapore and in the Department of Electrical and Computer Systems Engineering at Monash University, Australia. He obtained the Ph.D. degree from the Department of Electrical Communication Engineering, Indian Institute of Science, India. His research interests are in the broad areas of security and privacy applied to wireless and storage networks.
Professor Gourab Ghatak
Assistant Professor
Department of Electrical Engineering
Indian Institute of Technology, Delhi
Prof. Gourab Ghatak is an Assistant Professor at the Department of Electrical Engineering at IIT Delhi, where he is also affiliated with the Bharti School of Telecommunication Technology and Management. He received his B.Tech degree in Electronics and Communication Engineering from NIT Durgapur, his M.Tech degree in Electrical Engineering from IIT Kanpur, India, and his Ph.D. degree with a thesis on multi-RAT 5G networks from Telecom ParisTech (ENST), France, in 2019. During his Ph.D., he was employed at CEA-LETI, Grenoble, where he developed statistical tools to analyze and develop algorithms for initial access procedures, adaptive beamforming, user association, and traffic distribution in dual-band networks. Prior to that, he was a DAAD Research Scholar with the Vodafone Chair Mobile Communications Systems, TU Dresden, Germany, from 2014 to 2015, where he worked on channel estimation schemes for GFDM. He is the co-inventor of six patents on 5G and the author of several journals and conference publications. His research interests include stochastic geometry and machine learning for wireless communications.
Professor Neel Kanth Kundu
Associate Professor
Centre for Applied Research in Electronics
Indian Institute of Technology, Delhi
Prof. Neel Kanth Kundu is currently working as an Assistant Professor (since Oct. 2023) at Indian Institute of Technology (IIT) Delhi in the Centre for Applied Research in Electronics (CARE). He received the B.Tech. degree in electrical engineering with a specialization in communication systems and networking from the Indian Institute of Technology Delhi, in 2018, and the Ph.D. degree in electronic and computer engineering (ECE) with a concentration in scientific computation from The Hong Kong University of Science and Technology (HKUST), in 2022. From Sept. 2022 to Jan. 2023, he was a postdoctoral research associate with the ECE department, HKUST and from Feb. 2023 to Oct. 2023 he was a postdoctoral research fellow with the Department of Electrical and Electronic Engineering, The University of Melbourne, Australia.
Professor Vivek Venkataraman
Associate Professor
Department of Electrical Engineering
Indian Institute of Technology, Delhi
Prof. Vivek Venkataraman is an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Technology (IIT) Delhi. He holds joint appointments in the Department of Physics and is an associated faculty member at the Bharti School of Telecom Technology & Management. His research interests encompass quantum and nonlinear optics, light-matter interaction, atomic physics, fiber-optics and integrated photonics, all-optical devices and novel light sources, as well as optical signal processing and communication. Prior to his tenure at IIT Delhi, Prof. Venkataraman served as a Research Associate and Postdoctoral Fellow at the Laboratory for Nanoscale Optics within the School of Engineering & Applied Sciences at Harvard University, Cambridge, USA.
Programme Sample Certificate
The above Online PG Diploma is for illustrative purpose only, and the format of the certificate may be changed at the discretion of IIT Delhi.
An online PG Diploma will be issued separately by the organizing department.
The Organizing Department of this Online PG Diploma is Bharti School of Telecommunications Technology and Management
Installment Schedule
Programme Fees: 4,40,000 + 18 % GST
Component | Date | Amount (in ₹)* |
Application Fee* | To be paid at the time of Application | 2,000 |
1st Instalment | To be paid within 5 days of the offer release | 80,000 |
2nd Instalment | 09th August 2026 | 90,000 |
3rd Instalment | 23rd October, 2026 | 90,000 |
4th Instalment | 22nd December, 2026 | 90,000 |
5th Instalment | 20th February, 2027 | 90,000 |
Affiliate Alumni Membership Fee* | To be paid within 7 days of offer release | 10,000/- +GST |
Re-examination fee (per course, per attempt) ₹10,000/- + GST | ||
**Please Note:
| ||
Refund Policy
Refund Policy:
All fees paid are non-refundable and non-transferable.
Re-appearing in the exam is allowed up to 3 attempts by paying the re-examination fee for each attempt in each course over the span of 3 years after completion of the regular examination.
A re-examination fee of ₹10,000/- + GST per module/course will be applicable.
Frequently asked questions
It is a 12-month online postgraduate diploma offered by Bharti School of Telecommunications and Technology, IIT Delhi, that focuses on the convergence of AI & ML, advanced wireless communication (5G/6G), and quantum communication & security, designed for professionals looking to lead next-gen telecom and networking innovations.
The programme is ideal for telecom and network engineers, AI & ML professionals, wireless communication engineers, quantum communication specialists, cybersecurity experts, researchers, academicians, and technical managers seeking advanced, future-ready expertise.
Applicants must hold a BE/BTech/MSc/MCA degree in relevant disciplines such as ECE, EE, CSE, IT, Applied Physics, Mathematics, Data Science, AI & ML, or related fields.
Work experience-based relaxation in academic scores is available as per IIT Delhi norms.
The programme runs for 12 months and is delivered through live online sessions (Direct-to-Device), along with recorded content, hands-on labs, assignments, and a capstone project.
The curriculum covers Machine Learning for communication systems, advanced wireless communication, MIMO systems, 5G technologies, quantum communication & security, post-quantum cryptography, hybrid classical-quantum networks, and an industry-relevant capstone project worth 60 hours.
Yes. Learners who successfully complete the programme will receive an Online PG Diploma issued by IIT Delhi, offered through the Bharti School of Telecommunication Technology and Management.
Yes. Learners receive Affiliate Alumni Status from IIT Delhi upon payment of a one-time alumni membership fee, enabling access to alumni benefits as per institute policy.
Yes. The programme includes a 1-day campus immersion (6–8 hours) at the IIT Delhi campus toward the end of the programme. Travel and accommodation costs are to be borne by participants.
IIT Delhi does not provide placements or placement assistance for this programme. However, career support services such as resume building, interview preparation, and personal branding are provided by TimesPro.