The School of Engineering and Applied Sciences offers a two-year MTech programme in Computer Science and Engineering, or CSE, with a specialisation in data science and analytics.
Eligibility and Admission Criteria
The candidate must have passed any one of the following:
Aggregate marks in the qualifying degree must be no less than 60% or equivalent cumulative grade point average (CGPA). Undergraduate candidates appearing for their final semester/year may also apply. If admitted, students in this category must submit their provisional degree certificate within 30 days of commencement.
Admission to MTech is open to those who have a valid GATE score in any of these subjects: Computer Science, Information Technology, Electronics and Communication, Electrical Engineering, Instrumentation Engineering, Physics and Mathematics. The merit list will be generated on the basis of applicants' valid GATE scores. A list of short-listed candidates, in order of merit on valid GATE scores, will be posted on the website. All admissions will be managed by Ahmedabad University. To apply: click here.
Candidates selected for aid on the basis of applications, GATE scores and an interview will be provided monthly financial assistance of up to Rs. 12,000 a month during Monsoon and Winter semesters in the form of a teaching assistant-ship (TA-ship).
In an increasingly competitive marketplace, organizations need skilled professionals to interpret a growing stream and variety of data. Increasingly, industry focuses on how "big data" can be used to help decision makers improve organizational competitiveness.
The MTech programme’s data science and analytics specialisation is designed to meet this growing need. Our students gain hands-on experience with a variety of analytical tools available for the purpose of structuring large data sets, to unearth hidden information and patterns key to enterprise. Students also gain experience using different software tools and functions, including data mining, predictive modelling, and visual analytics using large data sets. Commercial and open-source tools are used to conduct analyses and build prototypes using real-world case studies and data sets. Case studies cover building predictive models in a variety of industries.
Students must demonstrate thorough knowledge of computer programming, data structures, file organization, database management systems, computer algorithms, computer organization, operating systems, computer networks, calculus, linear algebra, and statistical methods.
To design and implement databases, dimensional models, and data warehousing strategies.
To apply advanced methods of data warehousing and data mining in a variety of organizational environments.
To transform large data sets into actionable information in an easy-to-understand format.
To support organizational decision-making through the use of advanced analytical tools.
To manage the quality, security, and privacy of data relevant to an organization to enhance its value.
To manage real life complex data analytics projects.
Students will be enabled to:
Assess alternative approaches and infrastructures for implementing big data analytics.
Evaluate the appropriate methods and tools for data analysis in specific organizational contexts, including selecting a modeling approach, building a model using appropriate tools, validating the model, and deploying the model for prediction and analysis.
Develop experience tackling industry and organization-specific problems and challenges using advanced analytics and computational methods.
For the semester-wise curriculum of the M. Tech. in CSE, please click here.
MTech (CSE) Research Internships / Placements
Students of the Engineering School have had the opportunity to pursue their one year research internship at esteemed organisations like ABB, COVIAM, ISRO and eInfochips as well as with faculty members of SEAS - AU.
Our graduating students go on to become data scientists, data analytics specialists, and software engineers at companies and research labs. Their experience spans Indian industry, from e-commerce, financial services and online retail to meteorology, agriculture and entertainment.