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B-TECH-BACHELOR-OF-TECHNOLOGY-SIT-PUNE in Computer Science And Engineering at Symbiosis International University (SIU)
Pune, Maharashtra
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About the Specialization
What is Computer Science and Engineering at Symbiosis International University (SIU) Pune?
This Computer Science and Engineering program at Symbiosis Institute of Technology (SIT) Pune focuses on building a strong foundation in computational theories and practical applications. It prepares students for the rapidly evolving Indian tech industry by emphasizing core CS concepts, modern software development, data science, AI, and cybersecurity. The program integrates theoretical knowledge with hands-on experience, fostering innovation and problem-solving skills highly sought after in the Indian market.
Who Should Apply?
This program is ideal for fresh graduates from the 10+2 system with a strong aptitude for mathematics and science, aspiring to build careers in software development, data analytics, or emerging technologies. It also caters to individuals seeking to upskill in specialized areas like AI/ML or cybersecurity. Students passionate about coding, logic, and solving complex computational problems will thrive in this curriculum, positioning them for success in India''''s dynamic IT sector.
Why Choose This Course?
Graduates of this program can expect diverse career paths in India, including Software Engineer, Data Scientist, AI/ML Engineer, Cybersecurity Analyst, and Cloud Architect. Entry-level salaries typically range from INR 6-12 LPA, with experienced professionals earning significantly higher. The program aligns with industry demands, preparing students for professional certifications and growth trajectories in leading Indian and multinational companies operating in the country.
Student Success Practices
Foundation Stage
Master Core Programming Fundamentals- (Semester 1-2)
Dedicate significant time to thoroughly understand C/C++ and Object-Oriented Programming (OOP) concepts. Practice extensively with coding problems to build a strong logical foundation, which is crucial for all subsequent CS topics. Actively participate in labs and ensure clear understanding of data structures.
Tools & Resources
HackerRank, GeeksforGeeks, LeetCode (Easy problems), SIT Pune Coding Clubs
Career Connection
A solid foundation in programming and data structures is the cornerstone for cracking technical interviews for entry-level software development roles at top Indian IT firms and startups.
Build Strong Mathematical and Analytical Skills- (Semester 1-3)
Focus on Engineering Mathematics (Calculus, Linear Algebra, Probability & Statistics) and Discrete Mathematics. These subjects form the analytical backbone for advanced algorithms, machine learning, and data science. Practice problem-solving rigorously to develop critical thinking abilities.
Tools & Resources
Khan Academy, NPTEL lectures, Reference textbooks for practice problems
Career Connection
Exceptional analytical skills are vital for roles in data science, research, and for excelling in competitive exams like GATE, which can open doors to postgraduate studies and PSUs.
Engage in Interdisciplinary Project-Based Learning- (Semester 2-3)
Actively participate in Interdisciplinary Project Based Learning (IPBL) initiatives. Collaborate with peers from different engineering branches to understand diverse perspectives and integrate knowledge. This builds teamwork and practical problem-solving skills early on.
Tools & Resources
Github, Trello/Asana for project management, SIT Pune Innovation Cell
Career Connection
Early exposure to project work enhances portfolio, demonstrates practical application of concepts, and improves collaboration skills, valuable for any engineering role.
Intermediate Stage
Deep Dive into Core CS Specializations- (Semester 3-5)
Beyond mandatory courses like DBMS, OS, and Algorithms, start exploring professional electives in areas like Machine Learning, Information Security, or Web Technology. Build personal projects related to your chosen niche to demonstrate expertise and practical application.
Tools & Resources
Coursera/edX (specialized courses), Kaggle for ML datasets, OWASP for security standards, GitHub for open-source contributions
Career Connection
Specializing early helps you stand out, leading to targeted internship opportunities and job roles in niche areas like AI/ML Engineering or Cybersecurity Analysis, often with higher compensation in the Indian market.
Seek Industry Internships and Mini-Projects- (Semester 4-6)
Actively apply for internships (ID301) during summer breaks or through college placement cells. Even a small mini-project (ID201, ID302) with industry relevance can significantly boost your resume. Network with professionals and mentors during this phase.
Tools & Resources
LinkedIn, Internshala, SIT Pune Placement Cell, Industry conferences and workshops
Career Connection
Internships provide invaluable real-world experience, often leading to pre-placement offers (PPOs) in Indian companies, reducing job search efforts post-graduation and providing a competitive edge.
Participate in Coding Competitions and Hackathons- (Semester 3-6)
Regularly participate in competitive programming challenges and hackathons. This sharpens your problem-solving skills under pressure, exposes you to diverse problems, and allows you to build innovative solutions. Such participations are highly valued by tech recruiters in India.
Tools & Resources
CodeChef, Codeforces, Google Hash Code, Major tech company hackathons (e.g., TCS, Infosys)
Career Connection
Success in these platforms is a direct indicator of strong algorithmic thinking and coding prowess, making candidates highly attractive for product-based companies and R&D roles in India.
Advanced Stage
Undertake Impactful Major Projects- (Semester 7-8)
Choose your Major Project (Phase-I & II) wisely, focusing on a problem with significant real-world impact or research potential. Work closely with faculty mentors and industry experts. Aim for publications or a demonstrable prototype that showcases your expertise.
Tools & Resources
Research papers (IEEE Xplore, ACM Digital Library), Advanced development frameworks, Cloud platforms (AWS, Azure, GCP)
Career Connection
A strong major project is a key differentiator for placements, especially for R&D, innovation-focused roles, or further academic pursuits like M.Tech/PhD in India or abroad.
Focus on Comprehensive Placement Preparation- (Semester 7-8)
Intensify efforts on aptitude tests, group discussions, and technical interview preparation. Practice mock interviews, refine your resume, and work on soft skills. Stay updated with current industry trends and company-specific interview patterns.
Tools & Resources
SIT Pune Placement Cell workshops, Online aptitude platforms (e.g., Indiabix), Mock interview platforms/peers, Industry news websites
Career Connection
Thorough preparation ensures securing a desirable placement with a good package in leading Indian IT services, product, or consulting companies.
Explore Entrepreneurship or Higher Studies- (Semester 7-8)
For those with an entrepreneurial bent, leverage college resources for startup incubation and mentorship. Alternatively, prepare for competitive exams like GATE, GRE, or IELTS for pursuing postgraduate studies in India or internationally, building on your specialized knowledge.
Tools & Resources
SIT Pune Incubation Center, Startup India initiatives, Coaching for competitive exams
Career Connection
This stage enables career diversification, either into building your own venture within India''''s thriving startup ecosystem or advancing academic expertise for specialized roles and research opportunities.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 (or equivalent) with Physics, Mathematics, and English as compulsory subjects, along with Chemistry or Biotechnology or Biology or Technical Vocational subject or Computer Science or Information Technology or Informatics Practices or Agriculture or Engineering Graphics or Business Studies as optional subjects, with at least 45% marks in aggregate (40% for reserved category). Mandatory to appear in SITEEE (Symbiosis Institute of Technology Engineering Entrance Examination) or JEE (Main) or any other state-level Engineering Entrance Examination.
Duration: 4 years (8 semesters)
Credits: 152 Credits
Assessment: Internal: 50% (Continuous Evaluation), External: 50% (Semester End Examination)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BM101 | Engineering Mathematics-I | Core | 4 | Differential Calculus, Integral Calculus, Sequences and Series, Multiple Integrals, Vector Calculus |
| PH101 | Engineering Physics | Core | 3 | Wave Optics, Quantum Mechanics, Solid State Physics, Lasers and Fiber Optics, Superconductivity |
| CH101 | Engineering Chemistry | Core | 3 | Water Technology, Electrochemistry, Corrosion and its Control, Engineering Materials, Fuels and Combustion |
| EE101 | Basic Electrical Engineering | Core | 3 | DC Circuits, AC Fundamentals, Three Phase Circuits, Magnetic Circuits, Electrical Machines |
| ME101 | Engineering Graphics | Core | 3 | Introduction to Engineering Graphics, Orthographic Projections, Isometric Projections, Sections of Solids, Development of Surfaces |
| HS101 | Communication Skills | Core | 2 | Fundamentals of Communication, Verbal Communication, Non-verbal Communication, Presentation Skills, Report Writing |
| PH151 | Engineering Physics Lab | Lab | 1 | Experiments on Wave Optics, Experiments on Quantum Physics, Experiments on Semiconductor Devices, Experiments on Magnetic Materials, Experiments on Lasers |
| CH151 | Engineering Chemistry Lab | Lab | 1 | Titrimetric Analysis, Instrumental Analysis, Water Quality Analysis, Synthesis of Polymers, Fuels Analysis |
| CS151 | Computer Programming Lab | Lab | 2 | Introduction to C Programming, Conditional Statements, Looping Constructs, Functions, Arrays and Pointers |
| HS151 | Communication Skills Lab | Lab | 1 | Phonetics, Group Discussions, Presentation Practice, Role Play, Interview Skills |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BM102 | Engineering Mathematics-II | Core | 4 | Differential Equations, Laplace Transforms, Fourier Series, Partial Differential Equations, Complex Analysis |
| CS101 | Object Oriented Programming (OOP) | Core | 3 | Introduction to OOP, Classes and Objects, Inheritance, Polymorphism, Exception Handling |
| EC101 | Basic Electronics Engineering | Core | 3 | Semiconductor Diodes, Transistors (BJT & FET), Operational Amplifiers, Digital Electronics, Communication Systems |
| ME102 | Engineering Mechanics | Core | 4 | Forces and Moments, Equilibrium of Rigid Bodies, Friction, Kinematics of Particles, Kinetics of Particles |
| CS102 | Data Structures | Core | 3 | Introduction to Data Structures, Arrays and Linked Lists, Stacks and Queues, Trees, Graphs |
| EN101 | Environmental Studies | Core | 2 | Natural Resources, Ecosystems, Environmental Pollution, Social Issues and the Environment, Environmental Ethics |
| CS152 | Object Oriented Programming Lab | Lab | 1 | Classes and Objects Implementation, Inheritance and Polymorphism Exercises, Operator Overloading, File I/O, Exception Handling |
| CS153 | Data Structures Lab | Lab | 1 | Array and Linked List Operations, Stack and Queue Implementations, Tree Traversal Algorithms, Graph Algorithms, Sorting and Searching |
| EE151 | Basic Electrical Engineering Lab | Lab | 1 | DC Circuit Analysis, AC Circuit Analysis, Power Measurement, Transformer Experiments, Motor Characteristics |
| EC151 | Basic Electronics Engineering Lab | Lab | 1 | Diode Characteristics, Transistor Characteristics, Rectifiers, Logic Gates, Op-Amp Applications |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BM201 | Engineering Mathematics-III | Core | 4 | Linear Algebra, Probability and Statistics, Random Variables, Regression and Correlation, Queueing Theory |
| CS201 | Database Management Systems | Core | 3 | Introduction to DBMS, Relational Model, SQL, Database Design, Transaction Management |
| CS202 | Computer Organization and Architecture | Core | 3 | Digital Logic Circuits, Data Representation, CPU Organization, Memory Hierarchy, I/O Organization |
| CS203 | Design and Analysis of Algorithms | Core | 3 | Algorithm Analysis, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms |
| HS201 | Universal Human Values | Core | 2 | Self-exploration, Human Values, Professional Ethics, Harmony in Family and Society, Co-existence with Nature |
| BT201 | Biology for Engineers | Core | 2 | Cell Biology, Biomolecules, Genetics, Microbiology, Bioengineering Applications |
| CS251 | Database Management Systems Lab | Lab | 1 | SQL Queries, Database Creation, Joins, Triggers and Stored Procedures, PL/SQL |
| CS252 | Computer Organization and Architecture Lab | Lab | 1 | Logic Gate Simulation, CPU Simulation, Memory Interfacing, Assembly Language Programming, Microprocessor Experiments |
| CS253 | Design and Analysis of Algorithms Lab | Lab | 1 | Sorting Algorithms Implementation, Graph Traversal, Shortest Path Algorithms, Dynamic Programming Problems, Greedy Algorithms |
| GE201 | Interdisciplinary Project Based Learning - I | Project | 1 | Project Scoping, Problem Definition, Literature Survey, Methodology Design, Report Writing |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BM202 | Discrete Mathematics | Core | 4 | Logic and Proofs, Set Theory, Relations and Functions, Graph Theory, Algebraic Structures |
| CS204 | Operating Systems | Core | 3 | OS Structure, Process Management, CPU Scheduling, Memory Management, File Systems |
| CS205 | Theory of Computation | Core | 3 | Finite Automata, Regular Languages, Context-Free Grammars, Turing Machines, Undecidability |
| CS206 | Software Engineering | Core | 3 | Software Process Models, Requirements Engineering, Software Design, Software Testing, Project Management |
| GE202 | Research Based Learning – I | Project | 2 | Research Problem Identification, Literature Review, Data Collection Methods, Data Analysis, Scientific Report Writing |
| CS254 | Operating Systems Lab | Lab | 1 | Shell Scripting, Process Management, CPU Scheduling Algorithms, Deadlock Avoidance, File System Operations |
| CS255 | Software Engineering Lab | Lab | 1 | Requirement Gathering Tools, Design Tools (UML), Testing Tools, Version Control Systems, Project Planning |
| ID201 | Mini Project | Project | 1 | Project Planning, Design, Implementation, Testing, Documentation |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS301 | Computer Networks | Core | 3 | Network Models, Physical Layer, Data Link Layer, Network Layer, Transport Layer |
| CS302A | Professional Elective I - Cloud Computing | Elective | 3 | Introduction to Cloud Computing, Virtualization, Cloud Services (IaaS, PaaS, SaaS), Cloud Security, Cloud Deployment Models |
| CS302B | Professional Elective I - Information Security | Elective | 3 | Security Goals, Cryptographic Algorithms, Authentication and Authorization, Network Security, Cyber Attacks and Defenses |
| CS302C | Professional Elective I - High Performance Computing | Elective | 3 | Parallel Computing Architectures, Parallel Programming Models, Cluster Computing, GPU Computing, Performance Optimization |
| CS302D | Professional Elective I - Cyber Security | Elective | 3 | Cybercrime and Legal Aspects, Cyber Forensics, Malware Analysis, Vulnerability Assessment, Security Policies and Standards |
| CS303A | Professional Elective II - Web Technology | Elective | 3 | HTML, CSS, JavaScript, Client-side Scripting, Server-side Programming (e.g., Node.js, Python), Database Connectivity, Web Security |
| CS303B | Professional Elective II - Machine Learning | Elective | 3 | Introduction to ML, Supervised Learning, Unsupervised Learning, Model Evaluation and Validation, Introduction to Deep Learning |
| CS303C | Professional Elective II - Mobile Application Development | Elective | 3 | Android/iOS Architecture, UI/UX Design for Mobile, Activity Lifecycle, Data Storage, Networking and APIs |
| CS303D | Professional Elective II - Data Analytics | Elective | 3 | Data Collection and Cleaning, Exploratory Data Analysis, Statistical Methods, Data Visualization, Predictive Modeling |
| CS304 | Open Elective – I | Elective | 3 | |
| CS351 | Computer Networks Lab | Lab | 1 | Network Configuration, Socket Programming, Protocol Implementation, Network Security Tools, Packet Analysis |
| CS352 | Professional Elective – I Lab | Lab | 1 | Lab experiments corresponding to chosen Professional Elective I |
| CS353 | Professional Elective – II Lab | Lab | 1 | Lab experiments corresponding to chosen Professional Elective II |
| ID301 | Internship I | Project | 2 | Industry Exposure, Project Implementation, Professional Skills, Report Writing, Presentation |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS305 | Compiler Design | Core | 3 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization |
| CS306A | Professional Elective III - Digital Image Processing | Elective | 3 | Image Fundamentals, Image Enhancement, Image Restoration, Image Segmentation, Object Recognition |
| CS306B | Professional Elective III - Natural Language Processing | Elective | 3 | NLP Fundamentals, Text Preprocessing, Syntactic Analysis, Semantic Analysis, Information Extraction |
| CS306C | Professional Elective III - Blockchain Technology | Elective | 3 | Blockchain Fundamentals, Cryptocurrency Concepts, Smart Contracts, Consensus Mechanisms, Blockchain Platforms |
| CS306D | Professional Elective III - Data Science | Elective | 3 | Introduction to Data Science, Data Wrangling, Statistical Inference, Predictive Analytics, Ethical Considerations |
| CS307A | Professional Elective IV - Deep Learning | Elective | 3 | Neural Network Architectures, Convolutional Neural Networks, Recurrent Neural Networks, Generative Models, Deep Learning Frameworks |
| CS307B | Professional Elective IV - Internet of Things | Elective | 3 | IoT Architecture, Sensors and Actuators, IoT Communication Protocols, Cloud Platforms for IoT, IoT Security and Privacy |
| CS307C | Professional Elective IV - Software Architecture | Elective | 3 | Architectural Patterns, Design Principles, Service-Oriented Architecture, Microservices, Architectural Documentation |
| CS307D | Professional Elective IV - Game Development | Elective | 3 | Game Design Principles, Game Engines (e.g., Unity, Unreal), Graphics and Animation, Physics and AI in Games, Game Monetization |
| CS308 | Open Elective – II | Elective | 3 | |
| GE301 | Research Based Learning – II | Project | 2 | Advanced Research Methodologies, Experimental Design, Data Interpretation, Thesis Writing, Publication Ethics |
| CS354 | Compiler Design Lab | Lab | 1 | Lexical Analyzer Implementation, Parser Implementation, Intermediate Code Generation, Code Optimization Techniques, Compiler Construction Tools |
| CS355 | Professional Elective – III Lab | Lab | 1 | Lab experiments corresponding to chosen Professional Elective III |
| CS356 | Professional Elective – IV Lab | Lab | 1 | Lab experiments corresponding to chosen Professional Elective IV |
| ID302 | Minor Project | Project | 1 | Project Scope, Design Principles, Implementation, Testing, Technical Report |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS401A | Professional Elective V - Big Data Analytics | Elective | 3 | Introduction to Big Data, Hadoop Ecosystem, Spark, NoSQL Databases, Data Visualization |
| CS401B | Professional Elective V - Robotics | Elective | 3 | Robot Kinematics, Robot Dynamics, Robot Control, Sensors and Actuators, Robot Programming |
| CS401C | Professional Elective V - Information Retrieval | Elective | 3 | IR Models, Text Preprocessing, Indexing and Searching, Query Processing, Evaluation of IR Systems |
| CS401D | Professional Elective V - Quantum Computing | Elective | 3 | Quantum Mechanics Basics, Qubits and Superposition, Quantum Gates, Quantum Algorithms, Quantum Error Correction |
| CS402A | Professional Elective VI - Virtual & Augmented Reality | Elective | 3 | Introduction to VR/AR, VR Hardware, AR Principles, 3D Graphics for VR/AR, VR/AR Applications |
| CS402B | Professional Elective VI - Human Computer Interaction | Elective | 3 | HCI Principles, User-Centered Design, Usability Evaluation, Interaction Styles, Prototyping |
| CS402C | Professional Elective VI - Pattern Recognition | Elective | 3 | Pattern Recognition Basics, Feature Extraction, Classification Techniques, Clustering Algorithms, Deep Learning for PR |
| CS402D | Professional Elective VI - Compiler Optimization | Elective | 3 | Intermediate Representations, Control Flow Analysis, Data Flow Analysis, Code Transformation Techniques, Optimization for Parallelism |
| CS403A | Professional Elective VII - Wireless Sensor Networks | Elective | 3 | WSN Architecture, Sensor Node Hardware, MAC Protocols for WSN, Routing Protocols for WSN, Localization and Time Synchronization |
| CS403B | Professional Elective VII - Digital Forensics | Elective | 3 | Forensic Investigation Process, Digital Evidence Collection, Disk Forensics, Network Forensics, Mobile Forensics |
| CS403C | Professional Elective VII - Cryptography | Elective | 3 | Classical Ciphers, Symmetric Key Cryptography, Asymmetric Key Cryptography, Hashing, Digital Signatures |
| CS403D | Professional Elective VII - Computer Vision | Elective | 3 | Image Formation, Feature Detection, Image Segmentation, Object Recognition, Motion Analysis |
| CS404 | Major Project Phase-I | Project | 6 | Project Proposal, Literature Survey, System Design, Prototype Development, Mid-term Presentation |
| ID401 | Internship – II | Project | 2 | Advanced Industry Exposure, Specialized Project Work, Professional Networking, Technical Documentation, Final Presentation |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS405A | Professional Elective VIII - Distributed Systems | Elective | 3 | Introduction to Distributed Systems, Client-Server Model, Distributed File Systems, Consistency and Replication, Fault Tolerance |
| CS405B | Professional Elective VIII - Speech & Natural Language Processing | Elective | 3 | Speech Recognition, Speech Synthesis, Morphological Analysis, Syntactic Parsing, Semantic Role Labeling |
| CS405C | Professional Elective VIII - Embedded Systems | Elective | 3 | Embedded System Architecture, Microcontrollers, Real-time Operating Systems, Embedded System Programming, Sensors and Actuators Interfacing |
| CS405D | Professional Elective VIII - Ethical Hacking | Elective | 3 | Introduction to Ethical Hacking, Footprinting and Reconnaissance, Scanning Networks, System Hacking, Web Application Hacking |
| CS406A | Professional Elective IX - DevOps | Elective | 3 | Introduction to DevOps, Version Control (Git), CI/CD Pipelines, Containerization (Docker), Orchestration (Kubernetes) |
| CS406B | Professional Elective IX - Enterprise Application Development | Elective | 3 | Enterprise Architectures, Java EE/Spring Framework, Microservices Development, Enterprise Integration Patterns, Security in Enterprise Applications |
| CS406C | Professional Elective IX - Software Quality Assurance | Elective | 3 | SQA Fundamentals, Software Testing Types, Test Automation, Quality Metrics, Process Improvement |
| CS406D | Professional Elective IX - GPU Computing | Elective | 3 | GPU Architecture, CUDA Programming, OpenCL, Parallel Algorithms, Applications in Scientific Computing |
| CS407 | Open Elective – III | Elective | 3 | |
| CS408 | Major Project Phase-II | Project | 6 | Advanced Implementation, Testing and Debugging, Performance Evaluation, Thesis Writing, Final Project Defense |
