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B-SC-DATA-SCIENCES in General at Saveetha Institute of Medical and Technical Sciences
Chennai, Tamil Nadu
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About the Specialization
What is General at Saveetha Institute of Medical and Technical Sciences Chennai?
This B.Sc. Data Sciences program at Saveetha Institute focuses on equipping students with a robust foundation in data analysis, machine learning, and big data technologies. It is tailored to meet the escalating demand for skilled data professionals in India''''s rapidly digitizing economy, offering a blend of theoretical knowledge and practical application vital for success in this dynamic field. The curriculum emphasizes industry-relevant tools and techniques.
Who Should Apply?
This program is ideal for fresh graduates with a strong aptitude for mathematics and analytical thinking, seeking entry into the burgeoning field of data science. It also caters to individuals looking to transition into data-driven roles or upskill their existing capabilities in areas like AI and cloud computing, preparing them for diverse career paths across various Indian industries.
Why Choose This Course?
Graduates of this program can expect to pursue lucrative India-specific career paths such as Data Analyst, Machine Learning Engineer, Business Intelligence Developer, or Big Data Specialist. Entry-level salaries typically range from INR 3.5 to 6 LPA, with significant growth potential up to INR 15+ LPA for experienced professionals, aligning with certifications like AWS Certified Data Analytics or Microsoft Certified Azure Data Scientist.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate consistent time to practice Python and R programming through platforms like HackerRank and LeetCode. Focus on understanding data structures and algorithms deeply to build a strong analytical problem-solving base, crucial for advanced data science concepts.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks
Career Connection
Strong programming skills are non-negotiable for data science roles, directly impacting your ability to implement algorithms and clean data for technical interviews and project work.
Build a Strong Mathematical & Statistical Core- (Semester 1-2)
Actively engage with courses in Basic Mathematics, Probability, and Statistics. Supplement classroom learning with online resources like Khan Academy and NPTEL. Regularly solve problems to solidify your understanding of the underlying principles of data science algorithms.
Tools & Resources
Khan Academy, NPTEL, MIT OpenCourseWare
Career Connection
A solid grasp of math and stats is fundamental for interpreting model results, understanding algorithm biases, and designing effective data experiments, enhancing your analytical credibility.
Participate in Academic Quizzes and Hackathons- (Semester 1-2)
Join college-level quizzes and small-scale hackathons, even those not directly data science focused. This helps develop quick problem-solving skills, teamwork, and competitive spirit. It''''s a low-pressure way to apply early learnings.
Tools & Resources
Internal College Clubs, TechFest events
Career Connection
These experiences demonstrate initiative and a proactive learning attitude to potential employers, and the competitive environment mirrors real-world project deadlines and challenges.
Intermediate Stage
Undertake Practical Data Projects- (Semester 3-5)
Start building a portfolio of small data projects using Python libraries (Pandas, NumPy, Scikit-learn) and R. Focus on real-world datasets from platforms like Kaggle, applying concepts from DBMS, Machine Learning, and Data Visualization courses. Document your code and insights on GitHub.
Tools & Resources
Kaggle, GitHub, Jupyter Notebooks
Career Connection
A robust project portfolio showcases your practical skills and problem-solving abilities to recruiters, making you a strong candidate for internships and entry-level positions in Indian tech companies.
Network with Industry Professionals- (Semester 3-5)
Attend industry workshops, guest lectures, and career fairs organized by the institution or local tech communities in Chennai. Connect with data scientists and engineers on LinkedIn. Seek mentorship and insights into current industry trends and job requirements.
Tools & Resources
LinkedIn, Meetup groups, College Career Fairs
Career Connection
Networking opens doors to internship opportunities, informs career decisions, and provides valuable industry contacts, often leading to referrals for job openings.
Pursue Electives Strategically- (Semester 3-5)
Choose professional and open electives that align with your specific interests within data science, such as Deep Learning, NLP, or Big Data. This allows for early specialization and builds a unique skill set that stands out in the job market.
Tools & Resources
Syllabus Elective List, Online Course Platforms
Career Connection
Specialized knowledge makes you more competitive for niche roles and demonstrates a clear career direction, attracting employers looking for specific expertise.
Advanced Stage
Complete a Meaningful Internship/Industrial Training- (Semester 5-6)
Actively seek and complete a 4-6 month internship at a reputed company (MNC or prominent Indian startup). Focus on contributing significantly to a real project, understanding the business context, and learning from experienced professionals. Treat it as an extended interview.
Tools & Resources
College Placement Cell, LinkedIn, Internshala
Career Connection
Internships are often a direct pathway to pre-placement offers (PPOs) in Indian companies, providing invaluable real-world experience and strengthening your resume significantly.
Prepare Rigorously for Placements- (Semester 6)
Engage in intensive placement preparation, including mock interviews (technical and HR), aptitude test practice, and resume building workshops. Refine your communication skills and ability to articulate project experiences clearly. Focus on core data science concepts and recent trends.
Tools & Resources
TalentSprint, Online Aptitude Tests, InterviewBit
Career Connection
Comprehensive preparation is crucial for navigating competitive campus placements and securing desirable roles with top employers in the Indian data analytics landscape.
Develop a Capstone Project with Industry Relevance- (Semester 5-6)
For your final year project, choose a complex problem statement that is highly relevant to current industry needs or emerging technologies (e.g., AI in healthcare, financial fraud detection). Aim for a deployable solution and present it professionally, highlighting its impact.
Tools & Resources
Open-source datasets, Cloud platforms (AWS/Azure/GCP), Domain Experts
Career Connection
A well-executed capstone project serves as your ultimate showcase of skills, demonstrating your ability to tackle significant challenges and deliver impactful solutions, highly valued by Indian employers.
Program Structure and Curriculum
Eligibility:
- HSC / Equivalent with Minimum 50% aggregate in Physics, Chemistry & Biology/Mathematics or Vocational Stream with a minimum 50% aggregate mark in the qualifying examination
Duration: 3 years / 6 semesters
Credits: 138 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HS1121 | Professional English | Humanities and Social Sciences | 3 | Grammar and Vocabulary, Listening and Speaking Skills, Reading Comprehension, Writing for Professional Contexts, Presentation Skills |
| BS1121 | Basic Mathematics | Basic Science Course | 4 | Matrices and Determinants, Calculus Fundamentals, Differential Equations, Vector Algebra, Laplace Transforms |
| BS1122 | Environmental Science | Basic Science Course | 3 | Ecosystems and Biodiversity, Environmental Pollution, Natural Resources, Sustainable Development, Environmental Ethics |
| ES1121 | Introduction to Programming | Engineering Science Course | 4 | Programming Paradigms, Control Flow and Functions, Data Structures Introduction, Object-Oriented Programming Concepts, Debugging and Testing |
| DS1121 | Digital Marketing | Professional Core Course | 4 | Marketing Fundamentals, SEO and SEM Strategies, Social Media Marketing, Content Marketing, Email Marketing |
| ES1122 | Introduction to Programming Lab | Engineering Science Course - Lab | 2 | Basic Syntax and Data Types, Conditional Statements, Looping Constructs, Functions and Modules, Error Handling |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HS1221 | Professional Ethics | Humanities and Social Sciences | 3 | Ethical Theories, Professionalism and Ethics, Ethical Dilemmas, Cyber Ethics, Corporate Social Responsibility |
| BS1221 | Probability and Statistics | Basic Science Course | 4 | Probability Theory, Random Variables, Probability Distributions, Statistical Inference, Regression Analysis |
| ES1221 | Data Structures | Engineering Science Course | 4 | Arrays and Linked Lists, Stacks and Queues, Trees and Graphs, Hashing Techniques, Sorting and Searching Algorithms |
| DS1221 | R Programming | Professional Core Course | 4 | R Language Fundamentals, Data Manipulation in R, Statistical Modeling in R, Data Visualization with R, Advanced R Programming |
| DS1222 | Data Science Fundamentals | Professional Core Course | 4 | Introduction to Data Science, Data Collection and Cleaning, Exploratory Data Analysis, Machine Learning Overview, Big Data Concepts |
| DS1223 | Data Structures and R Programming Lab | Professional Core Course - Lab | 3 | Implementing Data Structures, R Data Import and Export, R Functions and Packages, Statistical Analysis in R, R Graphics |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HS1321 | Business Communication | Humanities and Social Sciences | 3 | Verbal and Non-verbal Communication, Report Writing, Presentation Skills, Interview Techniques, Cross-Cultural Communication |
| BS1321 | Discrete Mathematics | Basic Science Course | 4 | Set Theory, Logic and Proofs, Combinatorics, Graph Theory, Recurrence Relations |
| DS1321 | Database Management System | Professional Core Course | 4 | Database Concepts, Relational Model, SQL Queries, Database Design, Transaction Management |
| DS1322 | Python Programming | Professional Core Course | 4 | Python Syntax and Semantics, Data Types and Structures, Functions and Modules, Object-Oriented Python, File Handling |
| DS1323 | Machine Learning | Professional Core Course | 4 | Supervised Learning, Unsupervised Learning, Model Evaluation, Feature Engineering, Ensemble Methods |
| DS1324 | Database Management System Lab | Professional Core Course - Lab | 2 | SQL Commands Practice, Database Creation and Manipulation, Stored Procedures and Triggers, Relational Database Design, Database Connectivity |
| DS1325 | Python and Machine Learning Lab | Professional Core Course - Lab | 2 | Python Scripting for Data, NumPy and Pandas, Scikit-learn for ML Algorithms, Data Preprocessing, Model Training and Prediction |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DS1421 | Operating System | Professional Core Course | 4 | OS Structures and Functions, Process Management, Memory Management, File Systems, I/O Systems |
| DS1422 | Big Data Technologies | Professional Core Course | 4 | Big Data Ecosystem, Hadoop Architecture, MapReduce Programming, Spark Framework, NoSQL Databases |
| DS1423 | Deep Learning | Professional Core Course | 4 | Neural Network Fundamentals, Backpropagation, Convolutional Neural Networks, Recurrent Neural Networks, Deep Learning Frameworks |
| DS1424 | Cloud Computing | Professional Core Course | 4 | Cloud Computing Paradigms, Service Models (IaaS, PaaS, SaaS), Deployment Models, Virtualization, Cloud Security |
| DS1425 | Operating System Lab | Professional Core Course - Lab | 2 | Linux Commands, Shell Scripting, Process Creation, Memory Allocation, File System Operations |
| DS1426 | Big Data Technologies Lab | Professional Core Course - Lab | 2 | Hadoop HDFS Operations, MapReduce Program Execution, Spark RDDs and DataFrames, Hive and Pig, NoSQL Database Interaction |
| DS1427 | Mini Project | Project | 3 | Problem Identification, Literature Review, Design and Implementation, Testing and Evaluation, Report Writing and Presentation |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DS1521 | Data Visualization | Professional Core Course | 4 | Principles of Data Visualization, Types of Charts and Graphs, Dashboard Design, Tools like Tableau/PowerBI, Interactive Visualizations |
| DS1522 | Natural Language Processing | Professional Core Course | 4 | Text Preprocessing, Tokenization and Stemming, Sentiment Analysis, Named Entity Recognition, Language Models |
| DS1523 | Web Technology | Professional Core Course | 4 | HTML, CSS, JavaScript, Client-Side Scripting, Server-Side Scripting, Web Frameworks, API Integration |
| DS152X | Professional Elective I | Professional Elective Course | 2 | Advanced Data Structures, Image Processing, Reinforcement Learning, Time Series Analysis, Bioinformatics |
| DS152Y | Open Elective I | Open Elective Course | 2 | Entrepreneurship Development, E-commerce, Human Rights, Basic Robotics, Foreign Language |
| DS1524 | Data Visualization Lab | Professional Core Course - Lab | 2 | Tableau/PowerBI Proficiency, Creating Interactive Dashboards, Storytelling with Data, Custom Visualizations, Data Reporting |
| DS1525 | Web Technology Lab | Professional Core Course - Lab | 2 | Designing Dynamic Web Pages, Implementing Client-Side Validation, Database Connectivity to Web, Building RESTful APIs, Deployment on Servers |
| DS1526 | Project Phase I | Project | 3 | Detailed Problem Formulation, System Requirement Specification, Architectural Design, Methodology Selection, Pilot Implementation |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| DS1621 | Internet of Things | Professional Core Course | 4 | IoT Architecture, Sensors and Actuators, IoT Protocols, Data Analytics for IoT, IoT Security and Privacy |
| DS1622 | Ethical Hacking and Cyber Security | Professional Core Course | 4 | Network Security, Vulnerability Assessment, Penetration Testing, Cyber Forensics, Security Best Practices |
| DS162X | Professional Elective II | Professional Elective Course | 2 | Quantum Computing Basics, Blockchain Technologies, Game Theory, Computer Vision, Econometrics |
| DS162Y | Professional Elective III | Professional Elective Course | 2 | Digital Image Processing, Speech Recognition, Advanced Database Systems, Robotics and AI, Business Intelligence |
| DS162Z | Open Elective II | Open Elective Course | 2 | Personality Development, Financial Management, Indian Constitution, Yoga and Meditation, Creative Writing |
| DS1623 | Internship / Industrial Training | Internship | 6 | Real-world Project Implementation, Industry Best Practices, Professional Networking, Problem-solving in Industry, Technical Report Writing |
| DS1624 | Project Phase II | Project | 5 | System Development and Coding, Testing and Debugging, Performance Evaluation, Documentation and Reporting, Final Project Presentation |
