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The Center for Computational Engineering and Networking (CEN) offers MTech level course in Data Science.
Data science has critical applications across most industries, and it is one of the most in-demand careers in computer science. So this M.Tech course aims at preparing students in the area of computational sciences especially in data driven modeling and scientific computation.
Recent advances in computing-hardware platforms (NVIDIA CPU-GPUs, and Intel-Altera CPU-FPGA), Artificial Intelligence software platforms (like Torch, Theano and Tensor-flow) and sensor technology (camera, lidar, ultrasonic sensors) has resulted in rapid progress in machine -cognition tasks and is expected that machines will soon surpass the humans in visual and audio perception capabilities.
| Category | Code | Title | L | T | P | Credit |
|---|---|---|---|---|---|---|
| FC | 21MA602 | Computational Linear Algebra | 2 | 1 | 0 | 3 |
| FC | 21DS601 | Optimization Techniques for Data Science | 2 | 1 | 0 | 3 |
| FC | 21DS602 | Machine Learning | 3 | 0 | 3 | 4 |
| FC | 21DS603 | Data Structures and Algorithms for Data Science | 2 | 1 | 0 | 3 |
| SC | SC-1 | 2 | 1 | 0 | 3 | |
| SC | 21RM607 | Research Methodology | 2 | 1 | 0 | 2 |
| HU | 21HU601 | Amrita Value Programs | * | * | * | P/F |
| HU | 21HU602 | Career Competency – I | * | * | * | P/F |
| Total | 18 |
| Category | Code | Title | L | T | P | Credit |
|---|---|---|---|---|---|---|
| FC | 21DS611 | Deep Learning | 3 | 0 | 3 | 4 |
| SC | SC-2 | 2 | 1 | 0 | 3 | |
| SC | SC-3 | 2 | 1 | 0 | 3 | |
| SC | SC-4 | 2 | 1 | 0 | 3 | |
| E | Elective-I | 2 | 1 | 0 | 3 | |
| E | Elective-II | 2 | 1 | 0 | 3 | |
| HU | 21HU603 | Career Competency – II | 0 | 0 | 2 | 1 |
| Total | 20 |
| Category | Code | Title | L | T | P | Credit |
|---|---|---|---|---|---|---|
| E | * | Elective-III | 2 | 1 | 0 | 3 |
| E | * | Elective-IV | 2 | 1 | 0 | 3 |
| P | 21DS798 | Dissertation I | 0 | 0 | 10 | 10 |
| Total | 16 |
| Category | Code | Title | L | T | P | Credit |
|---|---|---|---|---|---|---|
| P | 21DS799 | Dissertation II | 0 | 0 | 16 | 16 |
| Total | 16 |
| Code | Title | L | T | P | Credit |
|---|---|---|---|---|---|
| 21MA602 | Computational Linear Algebra | 2 | 1 | 0 | 3 |
| 21DS601 | Optimization Techniques for Data Science | 2 | 1 | 0 | 3 |
| 21DS603 | Data Structures and Algorithms for Data Science | 2 | 1 | 0 | 3 |
| 21DS602 | Machine Learning | 3 | 0 | 3 | 4 |
| 21DS611 | Deep Learning | 3 | 0 | 3 | 4 |
| Code | Title | L | T | P | Credit |
|---|---|---|---|---|---|
| 20DS611 | Embedded Computing & Realtime OS for Data Science | 2 | 0 | 1 | 3 |
| 21RM607 | Research Methodology | 2 | 0 | 0 | 2 |
| 21DS632 | Introduction to Probabilistic Graphical Models | 2 | 0 | 1 | 3 |
| 21DS633 | Scientific Computing | 2 | 0 | 1 | 3 |
| 21DS634 | Text Mining and Analytics | 2 | 0 | 1 | 3 |
| 21DS635 | Big Data Framework for Data Science | 2 | 1 | 0 | 3 |
| 21DS636 | Statistical Modelling | 2 | 1 | 0 | 3 |
| 21DS637 | Advanced Data Visualization and Analytics | 3 | 0 | 0 | 3 |
| Code | Title | L | T | P | Credit |
|---|---|---|---|---|---|
| 21DS701 | AI Applications for Power Systems | 2 | 0 | 1 | 3 |
| 21DS702 | Deep Learning in Genomics and Biomedicine | 2 | 0 | 0 | 2 |
| 21DS703 | Deep Learning for Biomedical Data Analysis | 2 | 0 | 1 | 3 |
| 21DS704 | Deep Learning for Speech Signal Processing | 2 | 0 | 1 | 3 |
| 21DS705 | Social Media Analytics | 2 | 0 | 1 | 3 |
| 21DS706 | Deep Learning for Visual Recognition | 2 | 1 | 0 | 3 |
| 21DS707 | Deep Learning for Cyber Security | 2 | 1 | 0 | 3 |
| 21DS708 | Complex Systems in Engineering, Finance & Biology: Modelling & Analysis | 3 | 0 | 0 | 3 |
| 21DS709 | High Performance Computing | 2 | 1 | 0 | 3 |
| 21DS710 | Multiscale Fluid Modelling | 2 | 1 | 0 | 3 |
| 21DS711 | Computer Vision | 2 | 1 | 0 | 3 |
| 21DS712 | Reinforcement Learning | 2 | 1 | 0 | 3 |
| 21DS713 | Blockchain Technology | 2 | 1 | 0 | 3 |
| 21DS714 | Predictive Analytics for Internet of Things | 2 | 1 | 0 | 3 |
| 21DS715 | Cloud Computing and Security in the Cloud | 2 | 1 | 0 | 3 |
Duration: Two years
All branches of B.E /B.Tech Engineering / Post Graduate course in Sciences.
M Sc in Statistics, Computer Science.
(Knowledge of programming language is needed)
Center has long term collaboration with various national laboratories (C-DAC Pune – Artificial Intelligence as applied to computational linguistics, NPOL – Cochin – Artificial Intelligence applied to Signal Processing), various IIT’s (IIT Bombay – Natural Language Processing, IIT Guwahati – Speech Processing, IIT Madras – Spatio Temporal Data Analysis), various NIT’s (NIT Surathkal – Natural Language Processing, NIT Trichy – Smart Grids) and International research institutes (KTH- Sweden – Artificial Intelligence as applied to power grids, Potsdam Institute Berlin – Spatio-Temporal data analysis, University of Cincinnati – BioInformatics, University of Wyoming – Artificial Intelligence applied to Agriculture).
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I am an alumni of CEN; I completed my M Tech in Computational Engineering in 2012. My time at Amrita was a very different experience, especially the guidance of our beloved Soman Sir, which nurtured my interest into research in the fields of signal processing and optimization. After completing my Masters, I moved to New Zealand where I started exploring opportunities for pursuing my research interests. My PhD thesis supervisor at Victoria, impressed by the research that I carried out under the guidance of Soman Sir, agreed to supervise me for Doctoral research. I was also fortunate to get my research funded using the coveted Victoria Doctoral Scholarship. The scholarship is highly competitive and awarded mainly based on academic credentials and the quality of publications. I could get this scholarship primarily because of the publications from the research work done with Soman Sir
From my day one in CEN, I came to know a lot of people with full energy and enthusiasm towards research. CEN is a big family under the roof of outstanding professor Dr. Soman K.P, our dearest Soman sir. I learned many things from CEN. The syllabus we had was cutting edge. I was trained in writing technical papers and publications and also experienced many new technologies from here. I got a lot of opportunities and worldwide exposure here. The faculty and staffs were very supportive and are top rated. CEN played a major role in shaping my career. I really believe it is a privilege to be a part of CEN department.
CEN gave me step-by-step guidance on how to build my machine learning skills and master the state of the art machine learning problems. All the teachers and staffs are very friendly and its a great place for students who have a passion to work on current research problems.
Center for Computational Engineering and Networking (CEN) enlightened my life in so many ways, and opened up employment opportunities.I have chosen Natural Language Processing and Cognitive Learning as core subject in my master degree.I like the hands-on approach of the courses at CEN because it has taken my learning beyond theory. I have learned to apply my knowledge through experiences like publishing research paper’s, working with extremely talented Mathematicians and professors and also continuous participating in Artificial intelligence challenges.Thank you CEN!
I started my M.Tech program in Amrita University without knowing much about Computational Engineering and Networking (CEN). But now, I realize that the two years in CEN had really prepared me for a career in Artificial Intelligence. The interdisciplinary nature of the academic programs in CEN which includes Machine learning, Deep Learning, Remote Sensing, Image Processing, Big Data Analytics etc. and the research atmosphere is the highlight of the department. Unlike other post graduate programs, learning at CEN is really different. Apart from the classroom lessons, we had numerous workshops, paper presentations, seminars which helped me to nurture the latest trends in technology. The excellent faculty, having expertise in various backgrounds gave me proper guidance to learn. I am proud to be a part of the CEN family. My areas of interest includes Image processing, Machine learning, Deep learning, Natural Language Processing.
The top reasons to choose Amrita for your career
Email
mtech@amrita.edu
