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M-TECH in Computational And Data Science at National Institute of Technology Karnataka, Surathkal
Dakshina Kannada, Karnataka
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About the Specialization
What is Computational and Data Science at National Institute of Technology Karnataka, Surathkal Dakshina Kannada?
This M.Tech Computational and Data Science program at NITK Mangaluru focuses on equipping students with advanced skills in handling, processing, and analyzing large datasets using computational methods. It addresses the growing demand for data scientists and computational experts across various Indian industries like e-commerce, finance, healthcare, and manufacturing, emphasizing both theoretical foundations and practical applications.
Who Should Apply?
This program is ideal for engineering graduates in Computer Science, IT, or related fields, and M.Sc./MCA professionals with strong analytical and programming aptitude. It caters to fresh graduates seeking entry into high-demand data science roles and working professionals aiming to upskill for advanced positions or transition into computational data analysis within the Indian tech landscape.
Why Choose This Course?
Graduates of this program can expect to pursue lucrative India-specific career paths as Data Scientists, Machine Learning Engineers, Big Data Architects, and Business Intelligence Analysts. Entry-level salaries typically range from INR 7-12 LPA, with experienced professionals earning significantly more. The program fosters growth trajectories in leading Indian and multinational companies, aligning with certifications in AI/ML and Big Data platforms.
Student Success Practices
Foundation Stage
Strengthen Core Programming and Math Skills- (Semester 1-2)
Dedicate early semesters to mastering Python, R, and C++ for data science, alongside rigorous practice in linear algebra, calculus, and probability. Utilize online platforms for problem-solving and coding challenges.
Tools & Resources
HackerRank, LeetCode, Coursera/edX courses on Calculus/Linear Algebra, Khan Academy
Career Connection
A strong foundation is crucial for tackling advanced algorithms and models, directly impacting your ability to pass technical interviews and contribute effectively to data-intensive projects.
Active Participation in Labs and Problem Sets- (Semester 1-2)
Engage deeply in all laboratory sessions, ensuring hands-on implementation of algorithms and data structures. Actively work through problem sets and assignments, seeking clarification from faculty and peers for challenging concepts.
Tools & Resources
Jupyter Notebook, Google Colab, GitHub for version control
Career Connection
Practical application of theoretical knowledge is highly valued in the industry. Proficiency in lab work builds a portfolio of executable code and problem-solving experience, essential for internships and job roles.
Join Technical Clubs and Peer Learning Groups- (Semester 1-2)
Become an active member of the college''''s coding clubs, data science societies, or form small peer study groups. Participate in internal hackathons and coding competitions to apply learned concepts in a collaborative environment.
Tools & Resources
Discord/WhatsApp groups for peer study, College technical clubs (e.g., Data Science Club)
Career Connection
Networking with peers, learning from different perspectives, and collaborating on projects enhances soft skills and exposes you to diverse problem-solving approaches, making you a well-rounded professional.
Intermediate Stage
Undertake Mini Projects and MOOCs for Specialization- (Semester 2-3)
Beyond coursework, embark on self-initiated mini-projects in areas like Natural Language Processing, Computer Vision, or Big Data processing. Supplement institutional learning with specialized MOOCs from platforms like Coursera or Udemy.
Tools & Resources
Kaggle for datasets and competitions, TensorFlow/PyTorch documentation, AWS/GCP Free Tiers
Career Connection
These projects demonstrate initiative and specialization to recruiters. MOOC certifications validate your expertise in specific domains, making your profile stand out for advanced roles and industry certifications.
Seek Internships and Industry Exposure- (Semester 2-3)
Actively apply for summer internships at Indian tech companies, startups, or research labs. Focus on gaining hands-on experience with real-world data problems and industrial-grade tools and practices.
Tools & Resources
LinkedIn Jobs, Internshala, College placement cell resources, Naukri.com
Career Connection
Internships are critical for industry exposure and often lead to pre-placement offers (PPOs). They provide invaluable insights into corporate culture and refine professional skills, making you industry-ready.
Participate in Data Science Competitions- (Semester 2-3)
Regularly participate in online data science competitions on platforms like Kaggle, Analytics Vidhya, or internal college competitions. This hones your problem-solving skills under pressure and exposes you to diverse datasets.
Tools & Resources
Kaggle Competitions, Analytics Vidhya Challenges, DrivenData
Career Connection
Winning or even actively participating in these competitions builds an impressive resume, showcases your practical skills, and can attract attention from top companies looking for skilled data professionals.
Advanced Stage
Focus on Dissertation and Research Publications- (Semester 3-4)
Choose a dissertation topic aligned with your career aspirations and work diligently towards significant contributions. Aim for publishing your research in reputable conferences or journals, even if it''''s a poster presentation.
Tools & Resources
LaTeX for thesis writing, Mendeley/Zotero for referencing, Scopus/Web of Science for journal search
Career Connection
A strong dissertation with potential for publication enhances your profile for R&D roles, academic positions, or PhD programs, showcasing your ability for independent research and innovation.
Network Professionally and Attend Conferences- (Semester 3-4)
Attend industry workshops, seminars, and data science conferences in India (e.g., Cypher, Data Science Congress). Network with professionals, researchers, and potential employers to build valuable connections.
Tools & Resources
LinkedIn for professional networking, Eventbrite/Townscript for event discovery
Career Connection
Professional networking opens doors to exclusive job opportunities, mentorship, and collaborations. It helps you stay updated with industry trends and positions you as a proactive professional.
Intensive Placement Preparation and Mock Interviews- (Semester 3-4)
Engage in rigorous placement preparation, focusing on revising core subjects, practicing aptitude tests, and undergoing multiple mock interviews (technical and HR). Work on communication skills and presentation of projects.
Tools & Resources
GeeksforGeeks/InterviewBit for interview questions, Mock interview platforms, NITK Placement Cell
Career Connection
Thorough preparation is paramount for securing desired placements in top-tier companies. It builds confidence and readiness, enabling you to articulate your skills and projects effectively during interviews.
Program Structure and Curriculum
Eligibility:
- B.E./B.Tech. in Computer Science & Engineering/ Information Technology/ Computer Engineering OR M.Sc./MCA in Computer Science/ Computer Applications/ Information Science/ Information Technology with valid GATE score in CS/IT. Minimum 6.5 CGPA or 60% aggregate marks (6.0 CGPA or 55% for SC/ST/PwD candidates).
Duration: 4 semesters / 2 years
Credits: 76 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
Semester 2
Semester 3
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS7013 | Dissertation Phase-II | Project | 16 | Advanced experimentation and model development, In-depth data analysis and interpretation of results, Comparative study with existing solutions, Technical thesis writing and structuring, Preparing for viva voce and defense, Publication of research findings |
