School of Computer Science and Engineering (SCOPE) - PG
School of Computer Science and Engineering (SCOPE)
Postgraduate...
At the Masters level, the school offers programs in Computer Science and Engineering, Computer Science and Engineering (Information Security) and Computer Science and Engineering with Specialisation in Big Data Analytics.
B.Tech Computer Science and Engineering is accredited by the Computing Accreditation Commission and Engineering Accreditation Commission of ABET, http://www.abet.org. The School offers research programmes such as M.Tech. (by research) and Ph.D. All engineering, M.Sc. programmes have been accredited by Institution of Engineering and Technology, UK (IET- formerly known as IEE, UK) during the year 2004-05.
Courses Offered in Vellore Campus:
- M.Tech. Computer Science and Engineering
- M.Tech. Computer Science and Engineering (Big Data Analytics)
- M.Tech. Computer Science and Engineering (Information Security)
- M.Tech. Computer Science and Engineering (Artificial Intelligence and Machine Learning)
- M. Tech. Computer Science and Engineering – 5 year Integrated [In Collaboration with Virtusa]
- M. Tech. Computer Science and Engineering (Data Science) – 5 year Integrated
Courses Offered in Chennai Campus:
- M.Tech. Computer Science and Engineering
- M. Tech. Computer Science and Engineering (Big Data Analytics)
- Master of Computer Applications (2 Years)
- M.Tech. Software Engineering (5 year Integrated Programme)
- M.Tech. Computer Science and Engineering (Business Analytics)(5 year integrated programme)
- M.Tech. Computer Science and Engineering (Artificial Intelligence and Machine Learning) (In collaboration with C-DAC, Pune)
- M.Tech. Computer Science and Engineering
- About the Programme
- Programme Core Courses
- Programme Elective Courses
- Infrastructure
- Scope of employment
- Curriculum
M. Tech - Computer Science and Engineering is a two year programme. A student needs to earn atleast 70 credits in the duration of his/her study. The goal of M. Tech CSE programme at VIT is to develop experts of high quality to cater to the needs of global and national industry, research and academia. The two year course of study will be based on strengthening the fundamentals of Computer Science and Engineering concepts with advancements and specializations. It provides capacity to solve new problems through research projects, and a capacity to learn and interact with multidisciplinary groups. It includes courses of study, laboratory sessions, project work, internships, and research leading to a thesis.
- Algorithms: Design and Implementation
- Operating Systems and Virtualization
- Database Systems: Design and Implementation
- Computer Networks
- Software Engineering and Modelling
- Multicore Architectures
- Big data Frameworks
- Information Security Foundations
- Web Services
- Machine Learning
- NoSQL Databases
- Distributed Systems
- IoT Technology and Applications
- Cloud Application Development and Management
- Image Processing and Analysis
- Advanced Software Testing
- Mobile Applicatio nand Development
- Wireless Sensor Networks
List of labs and significant Facilities
| LAB NAME | HARDWARE DETAILS | M.TECH CSELAB | SOFTWARE/TOOLS |
|---|---|---|---|
| Software Systems Lab | Intel i5 Processor – 3.20 GHz, 500 GB HDD, 8 GB RAM, Keyboard, Mouse,19”Monitor | OperatingSystems Lab | C, C++, Java |
| Database Design and Implementation Lab | Oracle 11g, Microsoft SQL Server2005,Mysql 8.0.23 | ||
| Computer NetworksLab | Cisco Packet Tracer 7.3.1 | ||
| Intel Multicore Lab | Dell-Intel(R)-Core(TM)2Quad-2.66GHz, 500GB HDD,4GB DDR3, Keyboard,Mouse, 18.5 TFTMonitor Intel core i5 Processor-7500 8Gb Ram, 1 Tb Hdd, Keyboard, Mouse, 19? Monitor | Multicore Architecture Lab | Microsoft Visual Studio .Net 2010/08 |
| ArtificialIntelligence and Machine Learning Lab | Intel® Core™ i9-9900K CPU @ 3.60GHz × 16 GRAPHICS QuadroRTX 5000/PCIe/SSE2 32GB Ram, 1 TB Hdd GNOME 3.28.2 | NoSQL Databases Lab –– | OpenCV, Python |
| Machine Learning Lab | MongoDB, Cassandra, Neo4J |
- As Developers and specialists in high-end services and IT-product companies.
- As Development Engineers, Technical Leaders and Managers.
- As Academicians and Researchers in India and abroad.
- As Consultants, Solution Developers and Entrepreneurs.
- As Computing Specialists in Research Labs and as Technology Providers
- M.Tech - Computer Science and Engineering (Big Data Analytics)
- About the Programme
- Programme Core Courses
- Programme Elective Courses
- Infrastructure
- Scope of employment
- Curriculum
Big Data is an on-demand and fast-growing field in the domain of Computer Science and Engineering. This is because of the rapid and constant growth of data volumes handled by various scientific and engineering applications, enterprise software, social websites, and so on. Big Data helps the organizations to create new growth opportunities and therefore they need highly skilled graduates. The M.Tech CSE with specialization in Big Data Analytics programme was started in the year 2016 with an intake of 54 students. The programme is offered by the Department of Database Systems from the School of Computer Science and Engineering.
2018-19
- Algorithms: Design and Implementation
- Database Systems: Design andImplementation
- Exploratory Data Analysis
- Bigdata Frameworks
- Machine Learning
2019-20
- Algorithms: Design and Implementation
- Database Systems: Design andImplementation
- Exploratory Data Analysis
- Bigdata Frameworks
- Machine Learning
2020-21
- Algorithms: Design and Implementation
- DatabaseSystems: Design and Implementation
- Exploratory Data Analysis
- Bigdata Frameworks
- Machine Learning
2018-19
- OperatingSystems and Virtualization
- No SQLDatabases
- Programming for Data Science
- Information Visualization
- MiningMassive Data
- StreamingData Analytics
- Text, Weband Social Media Analytic
- Big DataTechnologies
- DomainSpecific Predictive Analytics
- SoftComputing
- CloudComputing Fundamentals
- Analyticsof Things
2019-20
- Operating Systems and Virtualization
- No SQL Databases
- Programming for Data Science
- Information Visualization
- Mining Massive Data
- Streaming Data Analytics
- Text, Weband Social Media Analytic
- Big Data Technologies
- DomainSpecific Predictive Analytics
- Soft Computing
- Cloud Computing Fundamentals
- Analytics of Things
- Blockchain Technology
- Deep Learning
- Image and Video Analytics
- Network Science and Applications
2020-21
- Operating Systems and Virtualization
- Data Engineering
- No SQL Databases
- Programming for Data Science
- Information Visualization
- Mining Massive Data
- Streaming Data Analytics
- Text, Weband Social Media Analytic
- Big Data Technologies
- Domain Specific Predictive Analytics
- Soft Computing
- Cloud Computing Fundamentals
- Analytics of Things
- Blockchain Technology
- Deep Learning
- Image and Video Analytics
- Network Science and Applications
Two high end computing laboratories are available for the M.Tech CSE with Big Data Analytics program. One among them is equipped with 72 GPU machines that are used for high performance computations.
| LAB NAME | HARDWARE DETAILS | M.TECH CSE LAB | SOFTWARE/ TOOLS |
|---|---|---|---|
| Accenture Innovation Centre | HP z210 Workstation: Intel(R)Xeon(R)E31245@3.30GHZ, 4GBRAM, 500GBHDD, Mouse,Keyboard, 19?Monitor | Big Data Technologies Lab Big Data Frameworks Lab Mining Massive Data Lab | Apache Hadoop, Pig, Spark, Hive |
| Dell 3020: Intel i5 Processor ? 3.20 GHz, 500 GB HDD, 8 GB RAM, Keyboard,Mouse, 19? Monitor | Algorithms: Design and Implementation Operating Systems and Virtualization | C. C++, Java | |
| Hp z230 Workstation (sponsored from Accenture): Intel(R) Xeon(R) E31245@3.30GHZ,500GB HDD, 4 GB RAM, Mouse, Keyboard, 19? Monitor | Database Design and Implementation Lab | Oracle 11g,Microsoft SQL Server 2005,Mysql 8.0.23 | |
| Artificial Intelligence and Machine Learning Lab | Hp Z2GPU SYSTEMS: Intel® Core? i9-9900K, CPU @ 3.60GHz × 16, GRAPHICS Quadro RTX, 5000/PCIe/SSE2, 32GB Ram, 1 TB HDD, GNOME 3.28.2 | No SQL Databases Lab | OpenCV, Python |
| Machine Learning Lab | MongoDB, Cassandra, Neo4J |
The M.Tech CSE with Big Data Analytics program focusses on the need to create Big Data Professionals. The mammoth increase in the amount and heterogeneity of data demands exponential processing of this data for business intelligence. The curriculum includes specific courses like Big Data Frameworks, Exploratory Data Analysis, Mining Massive Data, etc., to address such needs. The graduates can opt to work in Industries as Big Data Engineer, Big Data Analyst, Big Data Analytics Architect, Big Data Solution Architect and Big Data Analytics Business Consultant or prefer a research career leading to doctoral studies.
- M.Tech - Computer Science and Engineering (Information Security)
- About the Programme
- Programme Core Courses
- Programme Elective Courses
- Infrastructure
- Scope of employment
- Curriculum
The technological development, the Internet, and availability and distribution of data have extremely augmented information threats to organizations, IT sectors, governments and individuals making it a challenge for manipulators and system administrators to preserve security. Due to the prerequisite of cultured knowledge and tools to preserve systems secure, there is an immense need around the world for information security professionals who are well educated about the various aspects of information security. The main objective of this program is to train students to become information security professionals for the high-end jobs in security industry.
- Cryptosystems
- Algorithms: Design and Implementation
- Operating Systems and Virtualization
- Database Systems: Design and Implementation
- Computer Networks
- Information Security Foundations
- Masters Thesis
- Mathematics for Computer Engineering
- Science, Engineering and Technology Project - I
- Science, Engineering and Technology Project - II
- English and Foreign Language
- Fundamentals of Communication Skills - LO
- Professional and Communication Skills - LO
- Francais fonctionnel - TH
- Deutsch fuer Anfaenger - TH
- Soft Skills M.Tech.
- Essentials of Business Etiquettes - SS
- Essentials of Business Etiquette and Problem Solving – SS
- Preparing for Industry - SS
- Programming and Problem Solving Skills - SS
- Cyber Attacks Detection and Prevention Systems
- Malware Analysis
- Penetration Testing and Vulnerability Assessment
- Wireless and Mobile Network Security
- Multimedia Security
- Cloud Security and Analytics
- Secure Software Systems
- Digital Forensics
- Trusted Network Systems
- Critical Infrastructure Protection
- Risk Detection, Management and Mitigation
- Computer Security Audit and Assurance
- Web Application Security
| LAB NAME | HARDWARE DETAILS | SOFTWARE/TOOLS |
|---|---|---|
| Computational Intelligence Lab | Intel i5 Processor - 3.20 GHz, 500 GB HDD, 8 GB RAM, Keyboard, Mouse,19-Monitor Intel core i5-7500 8Gb Ram, 1 Tb Hdd Keyboard, Mouse, 19-Monitor | Matlab 2015a (Academic License) Libre Office-4.2.8.2 Code Blocks - 13.12Eclipse - 3.8 Dosbox/Masm GnuSim8085 - 1.3.7 Netbeans IDE - 8.0.2Apache2 PhpmyAdmin-3.4.10 mysql - 5.6.19 Scilab - 5.5.0 Spyder - 2.2.5Python - 3.4 Yed Graphics Editor - 3.14.2 Anaconda 3.5 Calligra Flow -2.8.0 Oracle 11g -Client Java-1.8 SSh Shell Client Firefox - 35.0 |
| Information Security Lab | I5 processor 500GB HDD, 8GB RAM, Keyboard, Mouse, 19-Monitor Intel core i5-7500 8Gb Ram, 1 Tb Hdd Keyboard, Mouse, 19-Monitor Intel R Pentium R CPU G 2030 & 3.00Ghz 2GB Ram 500GB Hdd Keyboard,Mouse, 19-Monitor | Libre Office- 6.4.6.2 Code Blocks - 20.03 Eclipse IDE for JavaDevelopers 2019-12 (4.14.0) Matlab-2020b (Academic License) AnacondaNavigator 1.9.2 Netbeans IDE - 8.0.2 Apache NetBeans IDE 12.2PhpmyAdmin-7.4.3 Mysql - 8.0.23 Wireshark - 3.2.3 Spyder - 4.2.3 Python- 3.8.5 Yed Graphics Editor - 3.20.1 BlueFish - 2.2.11 GNUSIM8085- 1.4.1Oracle 12.1 - Client Java-1.8.0_51 Geany-1.36 Android Studio 4.1.2Rstudio - 1.3.1093 Cisco Packet Tracer 7.3.1 Dia-0.97+git R version3.6.3 DOSBox- 0.74-3 Mozila FireFox - 85.0.1 Google Chrome - 88.04 NS3 -3.30.1 Scilab - 5.3.3 |
| Data Analytic Lab | Intel i5 Processor - 3.20 GHz, 500 GB HDD, 8 GB RAM, Keyboard, Mouse,19-Monitor | Libre Office- 6.4.6.2 Code Blocks - 20.03 Eclipse IDE for JavaDevelopers 2019-12 (4.14.0) Matlab-2020b (Academic License) AnacondaNavigator 1.9.2 Netbeans IDE - 8.0.2 Apache NetBeans IDE 12.2PhpmyAdmin-7.4.3 Mysql - 8.0.23 Wireshark - 3.2.3 Spyder - 4.2.3 Python- 3.8.5 Yed Graphics Editor - 3.20.1 BlueFish - 2.2.11 GNUSIM8085- 1.4.1Oracle 12.1 - Client Java-1.8.0_51 Geany-1.36 Android Studio 4.1.2Rstudio - 1.3.1093 Cisco Packet Tracer 7.3.1 Dia-0.97+git R version3.6.3 DOSBox- 0.74-3 Mozila FireFox - 85.0.1 Google Chrome - 88.04 NS3 -3.30.1 Scilab - 5.3.3 |
| Software Systems Lab | Intel i5 Processor - 3.20 GHz, 500 GB HDD, 8 GB RAM, Keyboard, Mouse,19-Monitor | Flip Eclipse Keil Net Beans IDE Oracle 11g -Client Dev C++ Yed GraphicsEditor Python Java-1.8 Anaconda 3.5 SSh Shell Client Pencil tool Firefox/Chrome Rational Rose 2003 Microsoft Visual Studio .Net 2008 NetopSchool Teacher/Student Qualnet 5.0 Sybase Ms Visio 2007 Matlab-2015a(Academic License) Ms office-2007 |
The M.Tech CSE with Information Security offers the platform for learners to become Information Security analysts or researchers. In addition to reinstating advanced core concepts of Computer Science and Engineering, specific courses like Cyber Attacks Detection and Prevention, Penetration and Vulnerability Testing, Secure Software Systems etc., are offered. These courses along with their project and lab components prepare the students explicitly for contemporary Information Security scenarios. The graduates work as Information Security Analysts, Consultants etc., for financial and other IT embedded critical industries.
- M.Tech - Computer Science and Engineering (Artificial Intelligence and Machine Learning)
- About the Programme
- Programme Core Courses
- Programme Elective Courses
- Infrastructure
- Curriculum
The M.Tech programme in Artificial Intelligence (AI) and Machine Learning (ML) is a two year programme which provides the platform to comprehend basic, essential insights and skills for the development of effective AI and ML systems. The programme covers mathematics for artificial intelligence and Machine learning, deep learning, statistical natural language processing, soft computing techniques and many other disciplines. The programme includes courses of study, Lab sessions, project work, internships, and research leading to a thesis.
- Data Structures and Algorithms Analysis
- Operating Systems and Virtualization
- Database Systems and Design
- Mathematics for Machine Learning
- Artificial Intelligence: Principles and Techniques
- Machine Learning Techniques
- Big-data Analytics
- Advances in Cryptography and Network Security
- Web Technologies
- Data Warehousing and Mining
- Computer Networks
- Distributed Systems
- Cloud Computing
- Cognitive Science
- Soft Computing Techniques
- Digital Imaging Techniques and Analysis
- Knowledge Engineering and Expert Systems
- Statistical Natural Language Processing
- Deep Learning and its Applications
- Intelligent Information Retrieval
- Bio-Inspired Computing
- Pattern Recognition
- Reinforcement Learning
- Machine Learning for Signal Processing
- Machine Learning with Large Data sets
list of labs and significant facilities
| LAB NAME | HARDWARE | LIST OF LABS | SOFTWARE/TOOLS |
|---|---|---|---|
| Software Systems Lab | Intel i5 Processor - 3.20 GHz, 500 GB HDD, 8 GB RAM, Keyboard, Mouse,19-Monitor(66 Systems) | Data Structures and Algorithms Analysis | Python, Jupiternotebook, Java and C |
| Operating Systems and Virtualization | C programming, Linuxenvironment, virtual box | ||
| Database Systems and Design | MySQL, Oracle SQL | ||
| Artificial Intelligence and Machine Learning Lab | Intel Core i9- 9900k CPU @ 3.60Ghz X 16, Nvidia Graphics Quadro RTX5000/ PCLe/SSE2, 32 GB RAM, 1 TB HDD(72 Systems) | Artificial Intelligence: Principles and Techniques | Python, Anaconda, Tensor flow, Keras, Matlab R - Studio, Scilab, Net beans |
| Machine Learning Techniques | Python, Anaconda, Tensor flow, Keras, Matlab R - Studio, Scilab, Net beans | ||
| Data Analytics Lab | Intel i5 Processor - 3.20 GHz, 500 GB HDD, 8 GB RAM, Keyboard, Mouse,19-Monitor(70 Systems) | Big-data Analytics | Hadoop, Apache Spark,R-programming |
- M.Tech. Computer Science and Engineering – 5 year Integrated [In collaboration with Virtusa]
- About the Programme
- Programme Core Courses
- Programme Elective Courses
- Infrastructure
- Scope of employment
- Curriculum
The Integrated M.Tech. (CSE) is a Virtusa Collaborative programme distinctly designed to cater the diverse needs of IT industries. Students in this programme are trained in the cutting edge technologies within a span of 5 years. The early level courses come up with a core foundations of computer engineering and the later stage students will specialize in advanced fields. The program also provides a perfect blend of both theoretical, lab and project based learning for most the latest technologies such as Full Stack development, AI&ML, IOT, Cloud Computing, Deep Learning, Natural Language Processing, etc.,
- DiscreteMathematics and Graph Theory
- Linear Algebra
- Fundamentals ofElectrical and Electronics Engineering
- Digital logic and Computer Design
- ComputerOrganization and Architecture
- Data Structures and Algorithm Analysis
- AdvancedAlgorithms
- Advanced DatabaseManagement Systems
- Principles ofDatabase Systems
- SoftwareEngineering Principles
- Formal Languagesand Automata Theory
- Principles ofComplier Design
- Operating SystemPrinciples
- Cloud ComputingMethodologies
- Microprocessorand Interfacing Techniques
- DataCommunication and Networks
- AppliedCryptography and Network Security
- Programming inJava
- ArtificialIntelligence and Experts Systems
- Advanced CProgramming
- ApplicationDevelopment and Deployment Architecture
- Advanced ServerSide Programming
- SoftwareApplication Architecture
- Front End Designand Testing
- Machine Learning
- Applications ofDifferential and Difference Equations
- Internetworkingwith TCP/IP
- Natural LanguageProcessing and Computational Linguistics
- Logic andCombinatorics for Computer Science
- Computer Graphicsand Multimedia
- Computer OrientedNumerical Methods
- DistributedSystems
- Text Mining
- Internet ofEverything
- Soft ComputingTechniques
- Advanced WirelessNetworks
- Augmented Realityand virtual Reality
- Block chainTechnologies
- Quantum ComputingTechniques
- SoftwareVerification and Validation
- Advanced ComputerArchitecture
- Advances inPervasive Computing
- Game Theory
- GPU Programming
- Advanced DataCompression Techniques
- ProgrammingParadigms
- Cyber Securityand Application Security
- Advanced GraphAlgorithms
- Software projectManagement
- Robotics:Machines and Controls
- MathematicalModelling and Simulation
- AdavancedPredictive Analytics
- Data Warehousingand Data Mining
- R Programming
- Foundations ofData Science
- Advanced DataVisualization Techniques
- Deep Learning
- Fault TolerantComputing System
- Vision and ImageProcessing
- Cognitive Scienceand Decision Making
- Web Mining andsocial Network Analysis
- Advanced PythonProgramming
| S.NO | COURSE | LANGUAGE | TOOL |
|---|---|---|---|
| 1 | Problem solving and programming | PYHTON,C | Pythonide,Code blocks |
| 2 | Calculus for engineers | Matlab | Matlab |
| 3 | Applications of differential and difference equations | Matlab | Matlab |
| 4 | Problem solving and object oriented programming | C++ | Code blocks |
| 5 | Data structures | C,C++ | Code blocks |
| 6 | Digital Logic and Design | Verilog Hardware description language | Altera Quartus 2 and model simaltera |
| 7 | Operating Systems | C | Code blocks, Virtual box, linux, Cocalc |
| 8 | DBMS | SQL | Oracle |
| 9 | Statistics for engineers | R-Programming | R-studio |
| 10 | Advanced C programming | C | Code blocks, Turbo C(forgraphics),Linux |
| 11 | Advanced Algorithms | C,C++ | Code Blocks |
| 12 | Programminigin Java | JAVA | Eclipseide,netbean side |
| 13 | Data Communication and networks | C,C++,Python | Code Blocks, Pythonide, Cisco packet tracer |
| 14 | Machine Learning | Python, R | Anaconda,Tensor flow, Keras, Matlab, R - Studio, Scilab, Netbeans |
| 15 | Image Processing and Analysis | C,C++,Java | OpenCV,Matlab |
Virtusa Collaborated M.Tech(CSE) aims to develop students excel in IT specialized areas such as Full Stack developer, Data Science, Networking etc. As Full Stack Developer it does not limit to only development but also imbibe Test Driven Development / Behavior Driven Development (TDD/BDD) principles to build quality applications, specifically using various Cloud and DevOps tools. The field has a potential for continued growth in the years to come. M.Tech CSE (5 Years Integrated programme – VIRTUSA) students are offered the highest paying jobs that include the positions viz., Software developer, Full stack developer, Database Administrator and many more..
- M.Tech - Computer Science and Engineering (Data Science) - 5 year integrated
- About the Programme
- Programme Core Courses
- Programme Elective Courses
- Infrastructure
- Scope of employment
- Curriculum
The demand for data science experts is on the growing trend as the need to handle volumes of data is constantly increasing across all domains. From a start-up to a multinational corporation, every organisation relies on data scientists for proper usage of the huge amount of data they gather. This program is designed with an aim to equip the students to learn, understand and practice on the technologies related to data science and machine learning approaches, with a focus on rendering solutions to industrial applications. This integrated program is designed with an objective to offer the fundamental concepts of computer science and engineering and advanced subjects related to data science applications, which will offer a better placement opportunity to students. Started in the year 2019, the programme is offered by the Department of Database Systems from the School of Computer Science and Engineering. The course will focus on subjects in the data science, machine learning, algorithmic principles and would offer an opportunity for a clear understanding of related tools on data science domain.
2019-20
- Principles of Database Systems
- Operating System Principles
- Formal Languages and Automata Theory
- Computer Organization and Architecture
- Software Engineering Principles
- Digital logic and Computer Design
- Data Structures and Algorithm Analysis
- Advanced Algorithms
- Advanced Database Management Systems
- Principles of Compiler Design
- Microprocessor and Interfacing Techniques
- Data Communication and Networks
- Programming in Java
- Cloud Computing Methodologies
- Applied Cryptography and Network Security
- Artificial Intelligence and Expert Systems
- Data Science Programming
- Advanced Data Visualization Techniques
- Fundamentals of Electrical and Electronics Engineering
- Discrete Mathematics and Graph Theory
- Linear Algebra
- Applications of Differential and Difference Equations
- Advances in Web Technologies
- Machine Learning for Data Science
2020-21
- Principles of Database Systems
- Operating System Principles
- Formal Languages and Automata Theory
- Computer Organization and Architecture
- Software Engineering Principles
- Digital logic and Computer Design
- Data Structures and Algorithm Analysis
- Advanced Algorithms
- Advanced Database Management Systems
- Principles of Compiler Design
- Microprocessor and Interfacing Techniques
- Data Communication and Networks
- Programming in Java
- Cloud Computing Methodologies
- Applied Cryptography and Network Security
- Artificial Intelligence and Expert Systems
- Data Science Programming
- Advanced Data Visualization Techniques
- Fundamentals of Electrical and Electronics Engineering
- Discrete Mathematics and Graph Theory
- Linear algebra
- Advances in Web Technologies
- Machine Learning for Data Science
2019-20
- Advanced C Programming
- User Interface Design
- Soft Computing Techniques
- Internet of Everything
- Advanced Wireless Networks
- Data Warehousing and Data Mining
- Computer Graphics and Multimedia
- Distributed Systems
- Blockchain Technologies
- Software Verification and Validation
- Software Project Management
- Robotics: Machines and Controls
- Business Intelligence
- Advanced Java
- Advanced Data Compression Techniques
- Advanced Graph Algorithms
- Advanced Computer Architecture
- Cyber Security and Application Security
2020-21
- Advanced C Programming
- User Interface Design
- Soft Computing Techniques
- Internet of Everything
- Advanced Wireless Networks
- Data Warehousing and Data Mining
- Computer Graphics and Multimedia
- Distributed Systems
- Blockchain Technologies
- Software Verification and Validation
- Software Project Management
- Robotics: Machines and Controls
- Business Intelligence
- Advanced Java
- Advanced Data Compression Techniques
- Advanced Graph Algorithms
- Advanced Computer Architecture
- Cyber Security and Application Security
- Applications of Differential and Difference Equations
Higher end computing laboratories are available for the M. Tech. Computer Science and Engineering with Specialisation in Data Science (5 year integrated) program. The laboratories are equipped with 72 GPU machines.
| LAB NAME | HARDWARE DETAILS | NO. OF SYSTEMS | M.TECH INTEGRATED DATA SCIENCE LAB | SOFTWARE/TOOLS |
|---|---|---|---|---|
| Data Analytic Lab | Dell 3020 workstation : Intel i5 Processor - 3.20 GHz,8 GB RAM ,500GB HDD, Mouse, Keyboard, 19-Monitor - 70 systems | 70 | Data Science Programming | Rversion 3.6.3 Rstudio - 1.3.1093 Jupyter |
| Data warehousing and Data Mining | ||||
| Software Systems Lab | Intel i5 Processor - 3.20GHz, 500 GB HDD, 8 GB RAM, Keyboard, Mouse, 19-Monitor | 66 | Advanced C Programming | C , C++ |
| Artificial Intelligence and Machine Learning Lab | Intel® Core- i9-9900K CPU @3.60GHz × 16 GRAPHICS Quadro RTX 5000/PCIe/SSE2 32GB Ram, 1 TB Hdd GNOME3.28.2 | 72 | Machine Learning for Data Science | Tensor Flow , Keras , Python -3.8.5 |
| Advanced Python Programming | Python -3.8.5 | |||
| Advanced DataVisualization Techniques | Plotly , Candela, Polymaps , Java-1.8.0_51 |
The Master's program in Data Science is designed to cater the fastest-growing job scenarios with a big demand for Analytics, Data Mining and Data Science professionals. The curriculum emphases the principles of Data Science and it encompasses courses like Foundations of Data Science, Data Science Programming, Data Visualization, Statistics, Machine Learning, etc., The students get exposed to intuitively analyze data and equipped with marketable skills built on solid foundation to take up positions like Data Analysts, Data Scientists, Database Administrator, Data Engineer, Machine Learning Engineer, Business Intelligence Analyst, Business Analyst and Data Manager or pursue a research career.
