M. Tech Computer Science and Engineering (Data Science)
Duration
2 Years Full-Time Program
Eligibility
Passed Bachelor’s Degree or equivalent. Obtained at least 50% marks (45% marks in case of candidates belonging to reserved category) in the qualifying examination, in relevant branch of Engineering and Technology as mentioned in the AICTE APH 2024-25.
Data science is an interdisciplinary field that uses techniques and theories from mathematics, statistics, computer science, domain knowledge, and information science. This program combines knowledge of machine learning, data analytics, and business intelligence with skills in modern tools and techniques in order to prepare students for the ever-changing demands of modern industry. Students gain hands-on experience building end-to-end solutions to computational problems as part of the curriculum, which provides a deep understanding of algorithms and their complexity. In addition, the specialization will provide exposure to fundamental research problems inspired by newly developed data science techniques.
Course Curriculum
01Advanced Engineering Mathematics - MAT6001
02English for Employability - ENG5001
03Artificial Intelligence - CSE5005
04Knowledge Engineering and Expert Systems - CSE5006
05Machine Learning Algorithms - CSE5007
06Discipline Elective – I - CSEXXXX
07Discipline Elective – II - CSEXXXX
08Seminar – I – SEM5001
01Deep Learning - CSE6001
02Natural Language Processing Techniques - CSE6002
03Discipline Elective – III - CSEXXXX
04Discipline Elective – IV - CSEXXXX
05Discipline Elective – V - CSEXXXX
06Open Elective – I
07Open Elective – II
08Seminar – II - SEM5002
01Dissertation/Internship – I - PIP6001
01Dissertation/Internship – II - PIP6002
Programme Educational Objectives
After four years of successful completion of the program, the graduates shall be:
PEO 01: To prepare graduates who will be successful professionals in industry, government, academia, research, entrepreneurial pursuit and consulting firms.
PEO 02: To prepare graduates who will contribute to society as broadly educated, expressive, ethical and responsible citizens with proven expertise.
PEO 03: To prepare graduates who will achieve peer recognition as individuals or in a team through demonstration of good analytical, research, design and implementation skills.
PEO 04: To prepare graduates who will thrive to pursue life-long reflective learning to fulfil their goals.
Programme Outcomes (POs)
PO 1:An ability to analyze, manage, and supervise engineering systems and processes with the aid of appropriate advanced tools.
PO 2:An ability to design a system and process within constraints of health, safety, security, economics, manufacturability to meet desired needs.
PO 3:An ability to carry out research in the respective discipline and publish the findings.
PO 4:An ability to effectively communicate and transfer the knowledge/skill to stakeholders.
PO 5:An ability to realize the impact of engineering solutions in a contemporary, global, economic, environmental, and societal context for sustainable development.
Programme Specific Outcomes
Upon completion of the M. Tech Computer Science and Engineering (Specialization in Data Science), students will be able to:
PSO 01: [Problem Analysis]: Identify, formulate, research literature, and analyze complex engineering problems related to Data science principles and practices, Programming and Computing technologies reaching substantiated conclusions using first principles of mathematics, natural sciences and engineering sciences.
PSO 02: [Design/development of Solutions]: Design solutions for complex engineering problems related to Data science principles and practices, Programming and Computing technologies and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, cultural, societal and environmental considerations.
PSO 03: [Modern Tool usage]: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities related to Data science principles and practices, Programming Data science Computing & analytics with an understanding of the limitations.
Advanced Curriculum covering big data analytics, machine learning, AI, deep learning, and cloud computing.
State-of-the-Art Data Science Labs equipped with Python, R, TensorFlow, Hadoop, Spark, and advanced analytics tools.
Expert Faculty & Research Mentorship providing hands-on experience in real-world data science applications.
Research & Innovation Focus with opportunities to work on AI-driven analytics, data modeling, and predictive algorithms.
Global Internship & Study Abroad Opportunities for international exposure and career growth.
Strong Industry Collaborations with leading tech firms for research projects, internships, and industry certifications.
Data Science & AI Certifications including AWS Data Analytics, Google Data Engineer, and TensorFlow for enhanced employability.
Excellent Placement Records with top recruiters in AI, data science, business intelligence, and analytics sectors.
Career Opportunities
Core Data Science Roles
Data Scientist: Extract insights from data, build predictive models, and communicate findings to drive business decisions.
Data Analyst: Perform exploratory data analysis (EDA) and generate actionable insights for organizations.
Machine Learning Engineer: Design and implement ML models for real-world applications, such as recommendation systems, fraud detection, and automation.
Big Data Engineer: Manage and optimize large-scale data pipelines and distributed computing environments.
Business Intelligence (BI) Developer: Develop BI solutions to transform raw data into meaningful visualizations and dashboards.
Industry-Specific Roles
Financial Analyst (Data Science Focus): Predict market trends, manage risks, and optimize investments using advanced data models.
Healthcare Data Scientist: Develop predictive models for patient diagnosis, treatment planning, and healthcare analytics.
Retail and E-commerce Analyst: Optimize inventory, pricing strategies, and customer segmentation using data science techniques.
Marketing Data Scientist: Analyze customer behavior and optimize digital marketing strategies through campaign analytics and customer sentiment analysis.
Sports Data Analyst: Analyze player performance, game strategies, and fan engagement using data models.
Emerging and Specialized Roles
AI/ML Specialist for Data Science: Focus on creating intelligent systems to process and analyze complex data.
IoT Data Analyst: Work on real-time data from IoT devices for smart cities, manufacturing, and connected vehicles.
Cloud Data Engineer: Design cloud-based data architectures and manage data storage solutions.
Data Privacy Officer/Consultant: Ensure compliance with data protection regulations like GDPR and CCPA.
Geospatial Data Scientist: Analyze spatial data for urban planning, environmental monitoring, and disaster management.
Academic and Research Roles
Data Science Research Scientist: Conduct research in data mining, deep learning, or algorithm optimization.
Lecturer/Professor in Data Science: Teach and mentor students in academic institutions while pursuing research.
Entrepreneurship
Data Science Startup Founder: Develop AI/data-driven solutions for niche problems in healthcare, finance, or logistics.
Your Next Move Awaits
Begin an extraordinary journey with Presidency University.
+91 9022092222
admission@presidencyuniversity.in
Itgalpura, Rajanukunte, Yelahanka, Bengaluru, Karnataka, Pin: 560119, India
+91 9022092222