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B-E-COMPUTER-SCIENCE-ENGINEERING in General at Vivekananda Institute of Technology
Bengaluru, Karnataka
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About the Specialization
What is General at Vivekananda Institute of Technology Bengaluru?
This B.E. Computer Science & Engineering program at Vivekananda Institute of Technology focuses on foundational and advanced computing concepts, essential for navigating India''''s rapidly evolving tech landscape. The curriculum is designed to equip students with strong programming, algorithmic thinking, and system design skills, crucial for meeting the demands of diverse Indian industries. It covers core areas from software development to artificial intelligence, reflecting current industry trends.
Who Should Apply?
This program is ideal for ambitious fresh graduates seeking entry into the dynamic IT sector, particularly those with a strong aptitude for mathematics and problem-solving. It also caters to individuals looking to build a robust career foundation in software development, data science, cybersecurity, or cloud computing. Aspiring innovators and technocrats who wish to contribute to India''''s digital transformation will find this course highly beneficial.
Why Choose This Course?
Graduates of this program can expect to pursue rewarding career paths as Software Developers, Data Analysts, AI/ML Engineers, Cybersecurity Analysts, or Cloud Architects in leading Indian and multinational companies. Entry-level salaries typically range from INR 4-8 LPA, with experienced professionals earning INR 15-30+ LPA. The program aligns with industry certifications like AWS, Azure, and Google Cloud, enhancing career growth trajectories in the burgeoning Indian tech market.
Student Success Practices
Foundation Stage
Master Programming Fundamentals and Data Structures- (Semester 1-2)
Dedicate significant time to mastering core programming concepts (C/Python) and fundamental data structures and algorithms. Participate actively in coding challenges on platforms to build logical thinking and problem-solving skills.
Tools & Resources
HackerRank, CodeChef, GeeksforGeeks, Online tutorials like freeCodeCamp
Career Connection
A strong foundation in programming and DSA is paramount for cracking coding rounds in placements at top tech companies in India. It''''s the gateway to entry-level software development roles.
Build Strong Peer Learning Networks- (Semester 1-2)
Form study groups and engage in collaborative learning. Discuss complex topics, work on assignments together, and prepare for exams collectively. Mentorship from senior students can also provide valuable guidance.
Tools & Resources
Discord/WhatsApp groups, College library study rooms, Departmental common areas
Career Connection
Effective teamwork and communication are highly valued in the Indian IT industry. Peer learning enhances these skills while also solidifying academic understanding, improving overall academic performance.
Develop Technical Communication Skills- (Semester 1-2)
Actively participate in technical English sessions and presentations. Practice writing clear and concise reports, project documentation, and emails. Good communication is vital for expressing technical ideas effectively.
Tools & Resources
Toastmasters clubs, Technical writing workshops, Grammarly, College''''s English language lab
Career Connection
Beyond coding, Indian companies seek engineers who can articulate their solutions. Strong communication skills are crucial for interviews, client interactions, and team collaboration in any tech role.
Intermediate Stage
Engage in Mini-Projects and Internships- (Semester 3-5)
Start working on small, real-world projects, either individually or in teams, based on subjects like Data Structures, Databases, or Web Technologies. Seek out mini-internships or summer training programs to gain practical industry exposure.
Tools & Resources
GitHub, Kaggle, Open-source projects, LinkedIn for internship search, College''''s placement cell
Career Connection
Practical project experience and internships are critical differentiators for placements in India, demonstrating applied knowledge and readiness for industry challenges. They strengthen resumes for product-based and service-based companies.
Participate in Tech Hackathons and Competitions- (Semester 3-5)
Join college-level or national hackathons and coding competitions. This provides a platform to apply theoretical knowledge, learn new technologies quickly, and work under pressure in a competitive environment.
Tools & Resources
Devpost, Major League Hacking (MLH), College tech clubs
Career Connection
Winning or even participating in such events showcases initiative, problem-solving prowess, and teamwork, which are highly attractive to recruiters from Indian startups to established MNCs.
Explore Specialization-Specific Skills- (Semester 3-5)
Begin to delve deeper into areas of interest like Machine Learning, Cybersecurity, or Cloud Computing beyond the curriculum. Utilize online courses and certifications to build expertise in a chosen domain.
Tools & Resources
Coursera, edX, NPTEL, Udemy, AWS/Azure/Google Cloud certifications
Career Connection
Developing specialized skills makes you a more targeted candidate for specific roles in India''''s diverse tech ecosystem, from AI/ML engineering to cloud development and cybersecurity roles, leading to better career prospects.
Advanced Stage
Undertake a Comprehensive Major Project- (Semester 6-8)
Work on a significant final-year project that integrates knowledge from multiple subjects, ideally solving a real-world problem. Focus on robust design, implementation, testing, and documentation. Consider an industry-sponsored project.
Tools & Resources
GitHub, Jira/Trello, Latest IDEs and frameworks, Faculty advisors
Career Connection
A strong major project is a cornerstone of an Indian engineering resume. It demonstrates practical skills, innovation, and ability to deliver, often acting as a primary discussion point in technical interviews and opening doors to R&D roles.
Intensive Placement Preparation and Mock Interviews- (Semester 6-8)
Engage in rigorous aptitude test preparation, resume building workshops, and numerous mock technical and HR interviews. Focus on company-specific preparation and review core CSE subjects thoroughly.
Tools & Resources
Quantitative Aptitude books, GeeksforGeeks interview section, LinkedIn, College placement cell workshops
Career Connection
This stage is directly geared towards securing a strong placement. Thorough preparation for all stages of the Indian recruitment process significantly increases the chances of landing coveted jobs.
Build a Professional Online Presence and Network- (Semester 6-8)
Create and maintain an active professional profile on platforms like LinkedIn and GitHub. Showcase projects, contributions, and skills. Network with alumni, industry professionals, and recruiters, attending webinars and tech talks.
Tools & Resources
LinkedIn, GitHub, Personal portfolio website, Industry meetups and conferences (online/offline)
Career Connection
A strong online presence and professional network are invaluable for discovering opportunities, receiving referrals, and establishing credibility within the Indian tech community, facilitating job searches and long-term career growth.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 or equivalent examination with Physics, Mathematics, and one of Chemistry/Biotechnology/Biology/Electronics/Computer Science/Information Technology/Informatics Practices/Agriculture Engineering as optional subjects with English as one of the languages, and obtained a minimum of 45% marks in aggregate (40% for SC/ST/OBC category candidates of Karnataka state) of the subjects mentioned. Admission through KCET/COMEDK/Management Quota.
Duration: 8 semesters (4 years)
Credits: 160 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21MAT11 | Calculus and Differential Equations | Core | 4 | Differential Calculus, Integral Calculus, Differential Equations, Vector Calculus, Partial Differential Equations |
| 21PHY12 | Engineering Physics | Core | 4 | Quantum Mechanics, Lasers and Fiber Optics, Semiconductor Physics, Material Science, Wave Optics |
| 21ELN13 | Basic Electrical and Electronics Engineering | Core | 3 | DC Circuits, AC Circuits, Transformers and Motors, Semiconductor Devices, Operational Amplifiers |
| 21CIV14 | Elements of Civil Engineering and Mechanics | Core | 3 | Building Materials, Surveying and Mapping, Engineering Mechanics, Fluid Mechanics basics, Environmental Engineering |
| 21PCD15 | Programming for Problem Solving | Core | 3 | Introduction to C, Control Structures, Functions and Arrays, Pointers and Strings, Structures and File Handling |
| 21PCDL16 | Programming for Problem Solving Lab | Lab | 1 | C Programming exercises, Debugging techniques, Algorithm implementation, Data structures basics, Problem solving with C |
| 21PHYSL17 | Engineering Physics Lab | Lab | 1 | Optics experiments, Electricity and Magnetism experiments, Semiconductor device characteristics, Material property measurements, Wave phenomena observation |
| 21VEG18 | Technical English | Ability Enhancement | 1 | Communication skills, Technical report writing, Presentation skills, Grammar and vocabulary, Soft skills development |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21MAT21 | Linear Algebra and Transforms | Core | 4 | Matrices and Determinants, Vector Spaces, Linear Transformations, Laplace Transforms, Fourier Series |
| 21CHE22 | Engineering Chemistry | Core | 4 | Electrochemistry, Corrosion and its Control, Water Technology, Polymer Chemistry, Fuels and Combustion |
| 21CPL23 | Computer Aided Engineering Graphics | Core | 3 | Orthographic Projections, Isometric Projections, Sectional Views, Solid Modeling, Assembly Drawings |
| 21EME24 | Elements of Mechanical Engineering | Core | 3 | Thermodynamics, Fluid Mechanics, Power Plants, Manufacturing Processes, Material Properties |
| 21EGD25 | Elements of Computer Science and Engineering | Core | 3 | Computer Organization, Operating Systems Introduction, Networking Fundamentals, Database Concepts, Web Technologies Basics |
| 21EGDL26 | Elements of Computer Science and Engineering Lab | Lab | 1 | Linux commands, HTML and CSS exercises, SQL basic queries, Shell scripting, Network configuration basics |
| 21CHELS27 | Engineering Chemistry Lab | Lab | 1 | Volumetric analysis, Instrumental analysis, Material characterization, Water quality testing, Corrosion experiments |
| 21HSM28 | Constitution of India, Professional Ethics & Cyber Law | Ability Enhancement | 1 | Indian Constitution, Fundamental Rights and Duties, Professional Ethics, Cyber Law, Intellectual Property Rights |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21CS31 | Data Structures and Applications | Core | 4 | Arrays and Pointers, Stacks and Queues, Linked Lists, Trees and Graphs, Sorting and Searching Algorithms |
| 21CS32 | Analog and Digital Electronics | Core | 4 | Diode Circuits, Transistor Amplifiers, Logic Gates, Combinational Circuits, Sequential Circuits |
| 21CS33 | Computer Organization and Architecture | Core | 3 | Basic Computer Organization, Processor Design, Memory System, Input/Output Organization, Pipelining |
| 21CS34 | Discrete Mathematical Structures | Core | 3 | Set Theory and Logic, Relations and Functions, Graph Theory, Algebraic Structures, Combinatorics |
| 21CSL35 | Data Structures Lab | Lab | 1 | Stack and Queue implementation, Linked list operations, Tree traversal algorithms, Graph algorithms, Sorting algorithm implementations |
| 21CSL36 | Analog and Digital Electronics Lab | Lab | 1 | Diode characteristics, Transistor amplifier design, Logic gate verification, Combinational circuit design, Sequential circuit implementation |
| 21KSK37 | Kannada (Ability Enhancement Course) | Ability Enhancement | 1 | Basic Kannada grammar, Conversational Kannada, Reading and writing Kannada, Kannada literature basics, Karnataka culture |
| 21CIP38 | Universal Human Values | Ability Enhancement | 1 | Understanding harmony, Family and society relationships, Ethics and moral values, Professional competence, Holistic development |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21CS41 | Design and Analysis of Algorithms | Core | 4 | Algorithm Complexity, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms |
| 21CS42 | Operating Systems | Core | 4 | Process Management, Memory Management, File Systems, I/O Systems, Concurrency and Deadlocks |
| 21CS43 | Microcontroller and Embedded Systems | Core | 3 | 8051 Microcontroller Architecture, Assembly Language Programming, Embedded C Programming, Interfacing Techniques, Real-Time Operating Systems |
| 21CS44 | Database Management Systems | Core | 3 | Database Architecture, ER Modeling, Relational Algebra, SQL Queries, Transaction Management |
| 21CSL45 | Microcontroller and Embedded Systems Lab | Lab | 1 | 8051 assembly programs, Interfacing LED, LCD, Keypad, Timer/Counter programming, Serial communication, Embedded system projects |
| 21CSL46 | Database Management Systems Lab | Lab | 1 | DDL and DML commands, SQL joins and subqueries, Database triggers and procedures, ER model implementation, Database application development |
| 21CSI47 | Environmental Studies | Ability Enhancement | 1 | Ecosystems, Environmental Pollution, Natural Resources, Social Issues and Environment, Environmental Protection |
| 21SK48 | Professional Skill Development | Ability Enhancement | 1 | Communication skills, Teamwork and collaboration, Problem-solving, Critical thinking, Interview preparation |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21CS51 | Automata Theory and Computability | Core | 3 | Finite Automata, Regular Expressions, Context-Free Grammars, Turing Machines, Undecidability |
| 21CS52 | Computer Networks | Core | 4 | Network Topologies, OSI and TCP/IP Models, Data Link Layer, Network Layer, Transport and Application Layers |
| 21CS53 | Software Engineering | Core | 3 | Software Development Life Cycle, Requirements Engineering, Software Design, Software Testing, Software Project Management |
| 21CS54X | Professional Elective - 1 (e.g., Artificial Intelligence) | Elective | 3 | Search Algorithms, Knowledge Representation, Machine Learning Basics, Neural Networks Introduction, Natural Language Processing |
| 21CS55X | Open Elective - 1 (e.g., Entrepreneurship and Startup Management) | Elective | 3 | Startup Ecosystem, Business Models, Funding Strategies, Legal Aspects of Startups, Marketing and Sales |
| 21CSL56 | Computer Networks Lab | Lab | 1 | Network configuration, Socket programming, Routing protocols, Network security tools, Packet analysis |
| 21CSL57 | Mini Project | Project | 2 | Problem identification, Project design, Implementation and testing, Report writing, Presentation skills |
| 21INT58 | Internship (Non-Credit) | Internship | 0 | Industry exposure, Skill application, Professional communication, Teamwork in corporate setting, Report submission |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21CS61 | Compiler Design | Core | 3 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization |
| 21CS62 | Machine Learning | Core | 4 | Supervised Learning, Unsupervised Learning, Reinforcement Learning, Neural Networks and Deep Learning, Model Evaluation |
| 21CS63X | Professional Elective - 2 (e.g., Web Technologies) | Elective | 3 | HTML5 and CSS3, JavaScript and DOM, Server-side scripting (Node.js/Python), Database Integration, Web Security |
| 21CS64X | Open Elective - 2 (e.g., Introduction to Data Science) | Elective | 3 | Data Collection and Cleaning, Exploratory Data Analysis, Statistical Modeling, Data Visualization, Introduction to Big Data |
| 21CSL65 | Machine Learning Lab | Lab | 1 | Data preprocessing, Implementing classification algorithms, Clustering algorithms, Regression models, Using ML libraries (Scikit-learn, TensorFlow) |
| 21CSL66 | Project Work Phase I | Project | 2 | Literature Survey, Problem Definition, System Design, Module Planning, Feasibility Study |
| 21CSRM67 | Research Methodology and IPR | Ability Enhancement | 1 | Research design, Data collection methods, Statistical analysis, Technical writing, Intellectual Property Rights |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21CS71 | Data Warehousing and Data Mining | Core | 3 | Data Warehousing Concepts, OLAP, Data Mining Techniques, Association Rule Mining, Classification and Clustering |
| 21CS72X | Professional Elective - 3 (e.g., Cloud Computing) | Elective | 3 | Cloud Service Models (IaaS, PaaS, SaaS), Cloud Deployment Models, Virtualization, Cloud Security, Big Data on Cloud |
| 21CS73X | Professional Elective - 4 (e.g., Internet of Things) | Elective | 3 | IoT Architecture, Sensors and Actuators, IoT Communication Protocols, Data Analytics in IoT, IoT Security |
| 21CS74X | Open Elective - 3 (e.g., Financial Management) | Elective | 3 | Financial Markets, Investment Analysis, Working Capital Management, Capital Budgeting, Risk Management |
| 21CSL75 | Project Work Phase II | Project | 6 | System Implementation, Testing and Debugging, Performance Evaluation, Project Report Writing, Viva-Voce |
| 21INT76 | Internship (Credit-based) | Internship | 3 | Industry problem solving, Professional skill enhancement, Team project contribution, Technical documentation, Presentation of work |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 21CS81 | Big Data Analytics | Core | 3 | Introduction to Big Data, Hadoop Ecosystem, MapReduce, Spark Programming, NoSQL Databases |
| 21CS82X | Professional Elective - 5 (e.g., Deep Learning) | Elective | 3 | Neural Network Architectures, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, Deep Learning Frameworks |
| 21CS83X | Professional Elective - 6 (e.g., Cyber Security) | Elective | 3 | Network Security, Cryptography, Web Security, Malware Analysis, Security Policies |
| 21CSP84 | Major Project Work | Project | 8 | Advanced system design, Large-scale implementation, Robust testing strategies, Comprehensive documentation, Innovation and research |
