M. Tech Data Science

Name: M. Tech Data Science
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COURSE OVERVIEW

The M. Tech in Data Science is a cutting-edge postgraduate program designed to equip students with advanced knowledge and skills in the field of data analysis, machine learning, and computational intelligence. Blending theoretical foundations with hands-on training, the program emphasizes real-world applications of data science in diverse industries. With a strong focus on statistics, programming, big data technologies, and domain-specific analytics, students will emerge as proficient data professionals ready to tackle complex problems in a data-driven world.

Syllabus >

Programme Objectives

To develop a strong foundation in data science concepts including statistics, machine learning, and data mining.
To provide practical exposure to tools and technologies such as Python, R, SQL, Hadoop, Spark, and TensorFlow.
To encourage research and innovation in data-driven problem solving and intelligent systems.
To prepare students for interdisciplinary roles in academia, industry, and entrepreneurship involving data analytics and artificial intelligence.
To cultivate ethical and socially responsible data science professionals.

PROGRAMME HIGHLIGHTS

Industry-Relevant Curriculum designed in collaboration with leading experts and academic institutions.

Hands-On Learning through labs, case studies, and real-world projects.

Internship Opportunities with reputed organizations for practical exposure.

Workshops & Seminars by data scientists and industry leaders.

Research Opportunities in AI, deep learning, natural language processing, and more.

Programme Curriculum

Semester - I + -

3 Week Induction Program
Course Code	Course Name	Periods per week			Credits	Hours per week
Course Code	Course Name	L	T	P	Credits	Hours per week
MTDT6501	Mathematical Foundations of Data Science	2	1	0	3	3
SOTT6301	Advanced Data Structures and Algorithms	2	1	0	3	3
Program Elective-I
MTDT6601a	Programming for Data Science	3	0	0	3	3
MTDT6601b	Data Engineering and Databases
MTDT6601c	Machine Learning and AI
Program Elective-II
MTDT6602a	AI and Decision-Making Models	3	0	0	3	3
MTDT6602b	Data Preparation and Analysis
MTDT6602c	Data Visualization and Communication
SOTT6374	Research Methodology and IPC	2	0	0	2	2
SOTT6303	Human Values & Professional Ethics (Audit Course – I)	2	0	0	0	2
MTDS6501/MTDC6501	Technical Seminar/Case Study -1	1	0	0	1	1
SOTL6301	Advanced Data Structures and Algorithms Lab	0	0	4	2	4
MTDL6501	Programming for Data Science Lab	0	0	4	2	4
—	Mentoring	0	0	0	0	1
—	Library	0	0	0	0	2
—	Physical Activity	0	0	0	0	2
—	Extra-curricular activities	0	0	0	0	2
—	Co-curricular activity	0	0	0	0	2
—	Self-Learning	0	0	0	0	2
TOTAL		15	2	8	19	36

Semester - II + -

Course Code	Course Name	Periods per week			Credits	Hours per week
Course Code	Course Name	L	T	P	Credits	Hours per week
SOTT6304	Advanced Machine Learning	2	1	0	3	3
MTDT6504	Big Data Analytics	2	1	0	3	3
Program Elective-III
MTDT6603a	Ethical AI and Decision Making	3	0	0	3	3
MTDT6603b	Time Series Analysis
MTDT6603c	Text Analytics
Program Elective-IV
MTDT6604a	Predictive and Perspective Analytics	3	0	0	3	3
MTDT6604b	Edge AI and IoT Analytics
MTDT6604c	Data Privacy and Security
SOTT6305	English for Research Paper Writing (Audit Course-2)	2	0	0	0	2
MTDP6501	Mini project	0	0	8	4	8
SOTL6302	Advanced Machine Learning Lab	0	0	4	2	4
MTDL6502	Big Data Analytics Lab	0	0	4	2	4
—	Mentoring	0	0	0	0	1
—	Co-curricular activity	0	0	0	0	1
—	Self-Learning	0	0	0	0	1
—	Extra-curricular activities	0	0	0	0	2
—	Library	0	0	0	0	1
TOTAL		12	2	16s	18	36

Semester - III + -

Course Code	Course Name	Periods per week			Credits	Hours per week
Course Code	Course Name	L	T	P	Credits	Hours per week
MTDM7501	MOOC-1	3	0	0	3	3
MTDM7502	MOOC -2	3	0	0	3	3
MTDP7501	Dissertation I / Industrial Project	0	0	20	10	20
—	Mentoring	0	0	0	0	1
—	Co-curricular activity	0	0	0	0	2
—	Self-Learning	0	0	0	0	1
—	Physical Activity	0	0	0	0	2
—	Extra-curricular activities	0	0	0	0	2
—	Soft Skills Training	0	0	0	0	1
—	Certification Course	0	0	0	0	1
TOTAL		6	0	20	16	36

Semester - III + -
Course Code Course Name Periods
per week
Credits Hours per week
L T P
MTDP7502 Dissertation Phase II 0 0 32 16 32
TOTAL 0 0 32 16 32

PROGRAMME FEE AND SCHOLARSHIPS

PROGRAMME FEES SCHOLARSHIPS ADMISSION PROCESS

One Time Fee	Admission Fee	₹10,000
Year I	Tuition Fee + Annual Recurring Fee	₹ 1,50,000 + ₹ 13,000
Year II	Tuition Fee + Annual Recurring Fee	₹ 1,50,000 + ₹ 13,000
Total Programme Fee (2 Years)		₹ 3,36,000

Scholarship is available for eligible students

Admissions are conducted in two modes:
1. Convener Quota: As per the Andhra Pradesh Private Universities Act, through the Government of Andhra Pradesh.
2. University Quota: Based on the TAU entrance exam or recognized national-level exams.

Eligibility

Pass with 50% aggregate marks (45% for reserved categories) in B.Tech. (Computer Science and Engineering or Information Technology or Electronics and Communication Engineering or Electrical and Electronics Engineering) or MCA or M.Sc. (Information Technology or Computer Science) or equivalent.

EMPLOYABILITY AREAS

Graduates of the M. Tech in Data Science program can explore careers in:

Data Science Expert & Data Analyst
Artificial Intelligence & Machine Learning
Business Analyst
Big Data Engineering
Data Engineering
Research & Development
Healthcare Analytics
Financial Services & Fintech
Retail & E-commerce Analytics
Government & Smart City Projects