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B-TECH in Computer Science Engineering at ST. JOSEPH ENGINEERING COLLEGE
Dakshina Kannada, Karnataka
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About the Specialization
What is Computer Science & Engineering at ST. JOSEPH ENGINEERING COLLEGE Dakshina Kannada?
This B.Tech Computer Science & Engineering program at St Joseph Engineering College focuses on equipping students with a robust foundation in computational theories, algorithms, data structures, and software development methodologies. It''''s designed to meet the evolving demands of the Indian IT industry, emphasizing practical skills alongside theoretical knowledge. The curriculum is regularly updated to align with global technological advancements and local industry needs.
Who Should Apply?
This program is ideal for aspiring software engineers, data scientists, cybersecurity specialists, and AI/ML enthusiasts. It caters to fresh 10+2 graduates with a strong aptitude for mathematics and problem-solving, seeking entry into the dynamic IT sector. The program also benefits individuals keen on research and development in cutting-edge computing fields, providing a comprehensive pathway to innovation.
Why Choose This Course?
Graduates of this program can expect to secure roles in leading Indian and multinational companies, with entry-level salaries typically ranging from INR 4-8 lakhs per annum, escalating significantly with experience. Career paths include Software Developer, Data Analyst, Network Engineer, AI Engineer, and Cloud Architect. The strong curriculum also prepares students for higher studies (M.Tech, MS) and aligns with certifications in areas like AWS, Azure, and Google Cloud.
Student Success Practices
Foundation Stage
Master Core Programming Fundamentals- (Semester 1-2)
Dedicate significant time to thoroughly understand C programming and data structures. Practice extensively on online coding platforms to build strong logical thinking and problem-solving skills.
Tools & Resources
GeeksforGeeks, HackerRank, CodeChef, NPTEL courses on Programming in C
Career Connection
A strong foundation in C and Data Structures is crucial for almost all technical interviews and forms the bedrock for advanced topics like algorithms and system design.
Develop Foundational Mathematical & Logical Aptitude- (Semester 1-3)
Focus on Engineering Mathematics and Discrete Mathematics. Solve a variety of problems regularly to improve analytical skills, which are vital for algorithm design and competitive programming.
Tools & Resources
Khan Academy, Reference textbooks for problem sets, Practice quizzes
Career Connection
Robust mathematical skills are essential for excelling in advanced subjects like Machine Learning, Data Science, and also for passing quantitative aptitude rounds in placements.
Engage in Peer Learning and Collaborative Projects- (Semester 1-3)
Form study groups, discuss complex topics with peers, and collaborate on small academic projects. This enhances understanding, communication skills, and exposes you to different problem-solving approaches.
Tools & Resources
GitHub for project collaboration, Microsoft Teams/Google Meet for discussions, College technical clubs
Career Connection
Teamwork and collaboration are highly valued in the IT industry. Early exposure helps in adapting to team-based project environments in internships and jobs.
Intermediate Stage
Apply Theoretical Knowledge through Mini-Projects- (Semester 3-5)
Beyond lab assignments, identify real-world problems and develop mini-projects using learned concepts in OOP (Java), DBMS, and Web Technologies. Document your work on platforms like GitHub.
Tools & Resources
Java IDEs (IntelliJ, Eclipse), MySQL/PostgreSQL, HTML/CSS/JS frameworks, GitHub
Career Connection
Practical project experience showcases your application skills to recruiters and provides talking points in interviews. A strong project portfolio is key for internships.
Participate in Coding Competitions & Hackathons- (Semester 4-6)
Actively participate in college-level, regional, and national coding competitions and hackathons. This sharpens problem-solving, time management, and innovative thinking under pressure.
Tools & Resources
Competitive programming platforms (LeetCode, TopCoder), DevPost for hackathons
Career Connection
Success in these events is a significant differentiator on resumes, demonstrating quick thinking, problem-solving prowess, and the ability to work in fast-paced environments.
Build a Professional Network and Seek Mentorship- (Semester 4-6)
Attend technical workshops, seminars, and industry events. Connect with alumni and industry professionals on LinkedIn. Seek mentorship for career guidance and internship opportunities.
Tools & Resources
LinkedIn, College Alumni Network, Industry meetups and conferences
Career Connection
Networking opens doors to internships, job referrals, and insights into industry trends, providing a significant advantage in the job market.
Advanced Stage
Undertake Industry Internships and Major Projects- (Semester 6-8)
Secure a relevant industry internship in your preferred domain (e.g., AI/ML, Cloud, Web Dev) during summer breaks. For your final year project, choose a challenging problem and deliver a robust solution.
Tools & Resources
College Placement Cell, Internshala, Naukri.com, Industry standard tools for chosen domain
Career Connection
Internships provide invaluable real-world experience, often leading to Pre-Placement Offers (PPOs). A significant final year project is a crucial asset for placements and further studies.
Specialize and Acquire Relevant Certifications- (Semester 7-8)
Based on your career interests (e.g., Machine Learning, Cybersecurity, Cloud Computing), pursue specialized courses and industry certifications to validate your skills and expertise.
Tools & Resources
Coursera, edX, Udemy, AWS Certified Cloud Practitioner, Google Cloud Associate Engineer, Certified Ethical Hacker
Career Connection
Specialized certifications enhance your resume, demonstrate commitment to a specific domain, and significantly boost your employability in niche tech roles.
Focus on Placement Preparation and Soft Skills- (Semester 7-8)
Engage in mock interviews, aptitude test practice, and resume building workshops. Develop strong communication, presentation, and critical thinking skills, which are essential for campus placements.
Tools & Resources
Placement training modules, Online aptitude test platforms, Public speaking clubs
Career Connection
Holistic preparation, combining technical depth with refined soft skills, ensures you stand out during the rigorous campus placement process and succeed in your professional journey.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 examination with Physics, Mathematics, and one of Chemistry/Biology/Biotechnology/Technical Vocational subject, obtained at least 45% marks (40% for reserved categories in Karnataka) in the above subjects taken together, and obtained a valid rank in Karnataka CET/JEE Main.
Duration: 4 years / 8 semesters
Credits: 163 Credits
Assessment: Internal: 50% (Continuous Internal Evaluation), External: 50% (Semester End Examination)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BPLUE101 | Basic Programming for Engineers (Physics Cycle) | Core | 3 | Introduction to C Programming, Control Structures and Loops, Functions and Pointers, Arrays and Strings, Structures and Unions |
| BPLUL101 | Basic Programming for Engineers Laboratory (Physics Cycle) | Lab | 1 | C program execution, Conditional and Looping statements, Functions and Arrays implementation, Pointers and Structures exercises, Basic algorithm implementation |
| BPLUE102 | Engineering Physics (Physics Cycle) | Core | 3 | Quantum Mechanics principles, Laser physics and applications, Optical Fibers and communication, Material Science (superconductors, dielectrics), Nanotechnology and applications |
| BPLUL102 | Engineering Physics Laboratory (Physics Cycle) | Lab | 1 | Measurement of Planck''''s constant, Laser characteristics and parameters, Optical fiber Numerical Aperture, Series and parallel LCR circuits, Verification of laws |
| BPLUE103 | Engineering Mathematics-I (Physics Cycle) | Core | 4 | Differential Calculus (Taylor''''s, Maclaurin''''s), Partial Differentiation and applications, Vector Calculus (gradient, divergence, curl), Multiple Integrals (double, triple), Ordinary Differential Equations |
| BPLUE104 | Elements of Mechanical Engineering (Physics Cycle) | Core | 3 | Thermodynamics principles, IC Engines and power plants, Refrigeration and Air Conditioning, Power Transmission systems, Introduction to Robotics |
| BPLUL104 | Elements of Mechanical Engineering Lab (Physics Cycle) | Lab | 1 | IC Engine performance testing, Refrigeration cycle demonstration, Lathe machine operations, Welding processes and safety, Measurement instruments usage |
| BPLUE105 | Engineering Drawing (Physics Cycle) | Core | 3 | Orthographic projections of points, lines, planes, Projections of solids, Sectional views of solids, Isometric projections, Development of surfaces |
| BPLEE106 | Professional English (Physics Cycle) | Core | 2 | Technical Communication skills, Report Writing and Documentation, Presentation Skills, Group Discussion techniques, Resume and Cover Letter writing |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BPLEL201 | Basic Programming for Engineers Lab (Chemistry Cycle) | Lab | 1 | C program execution, Conditional and Looping statements, Functions and Arrays implementation, Pointers and Structures exercises, Basic algorithm implementation |
| BPLEE201 | Basic Programming for Engineers (Chemistry Cycle) | Core | 3 | Introduction to C Programming, Control Structures and Loops, Functions and Pointers, Arrays and Strings, Structures and Unions |
| BPLEE202 | Engineering Chemistry (Chemistry Cycle) | Core | 3 | Electrochemistry and Batteries, Corrosion and its control, Polymers and Polymerization, Water Technology and Treatment, Fuels and Combustion |
| BPLEL202 | Engineering Chemistry Lab (Chemistry Cycle) | Lab | 1 | Potentiometric titration, Viscosity measurements, Acid value of oil, Hardness of water determination, Conductivity experiments |
| BPLEE203 | Engineering Mathematics-II (Chemistry Cycle) | Core | 4 | Linear Algebra (matrices, determinants), Laplace Transforms and applications, Fourier Series and Transforms, Numerical Methods (root finding, integration), Probability and Statistics |
| BPLEE204 | Elements of Electrical Engineering (Chemistry Cycle) | Core | 3 | DC Circuits (Ohm''''s, Kirchhoff''''s laws), AC Circuits (single-phase, three-phase), Transformers principles, DC Machines (motors, generators), Induction Motors |
| BPLEL204 | Elements of Electrical Engineering Lab (Chemistry Cycle) | Lab | 1 | Verification of Network Theorems, R-L-C circuit analysis, Single phase transformer testing, Measurement of power and energy, Basic wiring practices |
| BPLEE205 | Engineering Graphics (Chemistry Cycle) | Core | 3 | Introduction to CAD software, Orthographic views using CAD, Sectional views and assembly drawings, Isometric projections, 3D Modeling basics |
| BPLEE206 | Communicative English (Chemistry Cycle) | Core | 2 | Basic English grammar and usage, Listening and Reading comprehension, Oral Communication and Public Speaking, Interpersonal communication skills, Formal and Informal writing |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BCCSE301 | Data Structures and Applications | Core | 3 | Arrays, Stacks, Queues, Linked Lists (Singly, Doubly, Circular), Trees (Binary, BST, AVL), Graphs (representation, traversals), Hashing and Collision Resolution |
| BCCSL302 | Data Structures Laboratory | Lab | 1 | Implementation of Stacks and Queues, Linked List operations, Binary Search Tree operations, Graph traversals (BFS, DFS), Sorting and Searching algorithms |
| BCCSE303 | Analog and Digital Electronics | Core | 3 | Diode circuits and applications, Transistors (BJT, FET) characteristics, Operational Amplifiers, Boolean algebra and Logic Gates, Combinational and Sequential circuits |
| BCCSL304 | Analog and Digital Electronics Laboratory | Lab | 1 | Diode and Zener diode characteristics, Transistor biasing circuits, Logic gate realization using ICs, Flip-flops and counters implementation, Analog to Digital conversion |
| BCCSE305 | Computer Organization and Architecture | Core | 3 | Basic computer functions and operations, CPU organization and control unit, Instruction formats and addressing modes, Memory hierarchy and cache memory, Input/Output organization |
| BCCSE306 | Discrete Mathematics | Core | 3 | Mathematical Logic (propositions, predicates), Set Theory and Relations, Functions and Pigeonhole Principle, Graph Theory (paths, cycles, trees), Combinatorics (permutations, combinations) |
| BCCSE307 | Object Oriented Programming with JAVA | Core | 3 | OOP concepts (abstraction, encapsulation), Classes, Objects, Methods, Inheritance and Polymorphism, Exception Handling, Multithreading and File I/O |
| BCCSL308 | Object Oriented Programming with JAVA Laboratory | Lab | 1 | Java program development and debugging, Class and object implementation, Inheritance and polymorphism examples, Exception handling mechanisms, GUI programming with Swing/AWT |
| BCCSC309 | Constitution of India and Professional Ethics | Ability Enhancement Course | 1 | Indian Constitution structure and features, Fundamental Rights and Duties, Directive Principles of State Policy, Professional Ethics in engineering, Cyber laws and intellectual property |
| BCCSC310 | Engineering Statistics | Ability Enhancement Course | 1 | Probability theory, Random Variables and distributions, Sampling distributions, Hypothesis testing, Correlation and Regression |
| BCCSP311 | Design and Engineering | Project | 1 | Problem identification and analysis, Design thinking methodology, Prototyping and testing, Technical documentation and reporting, Project presentation |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BCCSE401 | Design and Analysis of Algorithms | Core | 3 | Algorithm analysis (time, space complexity), Sorting and searching techniques, Greedy algorithms, Dynamic Programming, Graph algorithms (DFS, BFS, shortest path) |
| BCCSL402 | Design and Analysis of Algorithms Laboratory | Lab | 1 | Implementation of sorting algorithms, Graph traversal algorithms, Dynamic programming problems, Divide and conquer algorithms, Analysis of algorithm efficiency |
| BCCSE403 | Operating Systems | Core | 3 | Operating System structures, Process management and scheduling, CPU scheduling algorithms, Deadlocks and concurrency control, Memory management and virtual memory |
| BCCSL404 | Operating Systems Laboratory | Lab | 1 | Linux commands and shell scripting, Process creation and termination, Inter-process communication, CPU scheduling algorithm simulations, Memory allocation strategies |
| BCCSE405 | Microcontrollers and Embedded Systems | Core | 3 | Microcontroller architecture (e.g., ARM Cortex), Instruction set and assembly language, Interrupts and Timers, Memory organization, Interfacing I/O devices |
| BCCSL406 | Microcontrollers and Embedded Systems Lab | Lab | 1 | Embedded C programming, GPIO control and LED interfacing, UART communication, Timer and counter applications, Sensor data acquisition |
| BCCSE407 | Software Engineering | Core | 3 | Software process models (Waterfall, Agile), Requirements engineering, Software design concepts, Software testing techniques, Software project management |
| BCCSE408 | Environmental Studies | Ability Enhancement Course | 1 | Ecosystems and their dynamics, Biodiversity and conservation, Environmental pollution and control, Waste management, Sustainable development |
| BCCSE409 | Universal Human Values | Ability Enhancement Course | 1 | Understanding self and human aspirations, Harmony in family and society, Professional ethics and value education, Relationship with nature, Holistic development |
| BCCSP410 | Mini Project | Project | 1 | Problem definition and scope, Requirement gathering, System design, Implementation and testing, Documentation and presentation |
| BCCSE411 | Data Communication | Core | 3 | Data transmission modes, Network models (OSI, TCP/IP), Physical layer (signals, media), Data Link Control (error, flow control), Switching techniques (circuit, packet) |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BCCSE501 | Database Management Systems | Core | 3 | Database architecture and models, Entity-Relationship modeling, Relational Algebra and Calculus, Structured Query Language (SQL), Normalization and transaction management |
| BCCSL502 | Database Management Systems Laboratory | Lab | 1 | SQL DDL, DML, DCL commands, Advanced SQL queries (joins, subqueries), PL/SQL programming basics, Database design and implementation, Transaction management commands |
| BCCSE503 | Computer Networks | Core | 3 | Network layers (TCP/IP model), IP addressing and subnetting, Routing protocols (RIP, OSPF), Transport layer (TCP, UDP), Application layer protocols (HTTP, DNS) |
| BCCSL504 | Computer Networks Laboratory | Lab | 1 | Network configuration and commands, Socket programming (Client-Server), Protocol analysis using Wireshark, Routing table configuration, Network security tools basics |
| BCCSE505 | Web Technologies | Core | 3 | HTML5 and CSS3 fundamentals, JavaScript and DOM manipulation, XML and JSON, Client-side and Server-side scripting (basics), Web security concepts |
| BCCSL506 | Web Technologies Laboratory | Lab | 1 | Developing responsive web pages, JavaScript form validation, AJAX requests implementation, Server-side scripting with database connectivity, Web application deployment |
| BCCSE507A | Artificial Intelligence (Professional Elective – 1) | Elective | 3 | Introduction to AI and Intelligent Agents, Problem-solving by Search, Knowledge Representation and Reasoning, Machine Learning fundamentals, Natural Language Processing basics |
| BCCSE507B | Data Mining (Professional Elective – 1) | Elective | 3 | Data Preprocessing and cleaning, Association Rule Mining, Classification techniques (Decision Trees, SVM), Clustering algorithms (K-Means, Hierarchical), Outlier detection |
| BCCSE507C | Cryptography and Network Security (Professional Elective – 1) | Elective | 3 | Classical encryption techniques, Symmetric Key Cryptography (DES, AES), Asymmetric Key Cryptography (RSA), Hash Functions and Digital Signatures, Network Security Applications (IPSec, SSL/TLS) |
| BCCSE507D | Internet of Things (Professional Elective – 1) | Elective | 3 | IoT architecture and paradigms, IoT devices and sensors, IoT communication protocols (MQTT, CoAP), IoT data analytics, Cloud platforms for IoT |
| BCCSO508A | Internet of Things (Open Elective – 1) | Elective (Open) | 3 | IoT fundamentals and applications, Sensors and actuators, Communication protocols (Zigbee, Bluetooth), IoT security and privacy, Smart city applications |
| BCCSC509 | Introduction to Cyber Security | Ability Enhancement Course | 1 | Cybercrime and types of attacks, Network security threats, Malware (viruses, worms, ransomware), Phishing and social engineering, Cybersecurity best practices |
| BCCSC510 | Research Methodology | Ability Enhancement Course | 1 | Formulating research problem, Literature review techniques, Data collection methods, Statistical analysis basics, Technical report writing |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BCCSE601 | Compiler Design | Core | 3 | Lexical Analysis (Scanners), Syntax Analysis (Parsers - LL, LR), Semantic Analysis, Intermediate Code Generation, Code Optimization and Code Generation |
| BCCSL602 | Compiler Design Laboratory | Lab | 1 | Implementation of Lexical Analyzer, Parsing techniques (Top-down, Bottom-up), Symbol table management, Intermediate code generation, Simple code optimization |
| BCCSE603 | Cloud Computing | Core | 3 | Cloud service models (IaaS, PaaS, SaaS), Cloud deployment models (private, public, hybrid), Virtualization technologies, Cloud security and privacy, Cloud storage and data management |
| BCCSL604 | Cloud Computing Laboratory | Lab | 1 | Virtual machine creation and management, Deploying applications on PaaS, Cloud storage services (S3, Blob), Load balancing and auto-scaling, Containerization with Docker |
| BCCSE605 | Artificial Intelligence | Core | 3 | Introduction to AI and its applications, Problem Solving by Search (informed, uninformed), Knowledge Representation (logic, rules), Machine Learning basics, Neural Networks introduction |
| BCCSE606A | Deep Learning (Professional Elective – 2) | Elective | 3 | Neural Network fundamentals, Perceptrons and activation functions, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Learning frameworks (TensorFlow, PyTorch) |
| BCCSE606B | Big Data Analytics (Professional Elective – 2) | Elective | 3 | Introduction to Big Data, Hadoop Ecosystem (HDFS, MapReduce), Spark for Big Data processing, NoSQL databases, Big Data visualization |
| BCCSE606C | Cyber Security (Professional Elective – 2) | Elective | 3 | Network Security fundamentals, Intrusion Detection and Prevention Systems, Web Application Security, Operating System Security, Security policies and standards |
| BCCSE607A | Natural Language Processing (Professional Elective – 3) | Elective | 3 | Language models and N-grams, Part-of-Speech Tagging, Parsing (Constituency, Dependency), Text Classification, Information Extraction |
| BCCSE607B | Reinforcement Learning (Professional Elective – 3) | Elective | 3 | Introduction to Reinforcement Learning, Markov Decision Processes, Dynamic Programming, Monte Carlo methods, Q-learning and SARSA |
| BCCSE607C | Blockchain Technology (Professional Elective – 3) | Elective | 3 | Cryptography for Blockchain, Distributed Ledger Technology, Bitcoin and Cryptocurrencies, Smart Contracts (Ethereum), Consensus Mechanisms |
| BCCSO608A | Renewable Energy Systems (Open Elective – 2) | Elective (Open) | 3 | Solar energy systems, Wind energy generation, Hydroelectric power, Geothermal energy, Bioenergy and fuel cells |
| BCCSP609 | Technical Seminar | Project | 1 | Literature review and research, Technical presentation skills, Report writing and documentation, Oral communication and Q&A, Identifying emerging technologies |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BCCSE701 | Machine Learning | Core | 3 | Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Model evaluation and validation, Ensemble methods (Bagging, Boosting), Feature engineering and selection |
| BCCSL702 | Machine Learning Laboratory | Lab | 1 | Implementation of Linear/Logistic Regression, Decision Tree and SVM classifiers, K-Means clustering, Model training and testing, Using Python libraries (Scikit-learn) |
| BCCSE703A | Advanced Database Management Systems (Professional Elective – 4) | Elective | 3 | Distributed Databases, NoSQL Databases (MongoDB, Cassandra), Data Warehousing and OLAP, Database Security, Big Data management |
| BCCSE703B | Mobile Application Development (Professional Elective – 4) | Elective | 3 | Android/iOS development environment, UI/UX design for mobile, Activity Lifecycle and Intents, Data storage (SQLite, Shared Preferences), RESTful APIs for mobile apps |
| BCCSE703C | Computer Graphics and Visualization (Professional Elective – 4) | Elective | 3 | Graphics pipeline, 2D and 3D Transformations, Clipping and Projections, Rendering techniques (lighting, shading), Visualization techniques |
| BCCSE704A | Quantum Computing (Professional Elective – 5) | Elective | 3 | Quantum mechanics for computing, Qubits and superposition, Quantum gates and circuits, Quantum algorithms (Shor''''s, Grover''''s), Quantum programming platforms (Qiskit) |
| BCCSE704B | High Performance Computing (Professional Elective – 5) | Elective | 3 | Parallel processing concepts, Multicore architectures, GPU computing (CUDA, OpenCL), Distributed computing (MPI), Performance metrics and optimization |
| BCCSE704C | Soft Computing (Professional Elective – 5) | Elective | 3 | Fuzzy Logic systems, Artificial Neural Networks, Genetic Algorithms, Hybrid Soft Computing approaches, Applications in pattern recognition |
| BCCSP705 | Internship | Internship | 4 | Industry exposure and professional development, Practical application of theoretical knowledge, Project execution in real-world setting, Communication and teamwork skills, Internship report and presentation |
| BCCSP706 | Project Phase-I / Professional Practice | Project | 2 | Problem identification and literature survey, Defining project objectives and scope, Methodology and design proposal, Preliminary implementation and data collection, Project proposal presentation |
| BCCSE707 | Innovation and Entrepreneurship | Ability Enhancement Course | 2 | Concept of innovation and creativity, Business model canvas, Market analysis and feasibility study, Startup ecosystem in India, Intellectual property rights and funding |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BCCSP801 | Project Work | Project | 6 | Full-scale system development, Module integration and testing, Performance evaluation and debugging, Comprehensive documentation, Project demonstration and Viva-Voce |
| BCCSE802A | Augmented Reality / Virtual Reality (Professional Elective – 6) | Elective | 3 | AR/VR fundamentals and display devices, 3D modeling and rendering for AR/VR, Interaction techniques in AR/VR, AR/VR application development platforms, Human factors in AR/VR |
| BCCSE802B | Ethical Hacking and Penetration Testing (Professional Elective – 6) | Elective | 3 | Ethical hacking concepts and methodologies, Footprinting and Reconnaissance, Scanning and Enumeration, Vulnerability analysis and exploitation, Penetration testing tools and reports |
| BCCSE802C | Information Retrieval (Professional Elective – 6) | Elective | 3 | Boolean and Vector Space models, Text processing and indexing, Ranking algorithms, Evaluation of IR systems, Web search and social search |
| BCCSE803A | Distributed Systems (Professional Elective – 7) | Elective | 3 | Architectures of Distributed Systems, Inter-process communication, Distributed file systems, Consistency and Replication, Fault tolerance and recovery |
| BCCSE803B | Web Analytics (Professional Elective – 7) | Elective | 3 | Web analytics concepts and tools, Google Analytics platform, Website traffic analysis, Conversion rate optimization, Social media analytics |
| BCCSE803C | Social Network Analysis (Professional Elective – 7) | Elective | 3 | Graph theory fundamentals, Centrality measures, Community detection algorithms, Network visualization, Social media data analysis |
| BCCSE804 | Technical Report Writing | Skill Development | 1 | Principles of scientific writing, Structure of technical reports, Formatting and referencing styles, Abstract and executive summary writing, Proofreading and editing |
| BCCSP805 | Outcome Based Education and Pedagogy | Ability Enhancement Course | 1 | Introduction to OBE principles, Bloom''''s Taxonomy and cognitive levels, Course Outcome (CO) formulation, Program Outcome (PO) mapping, Assessment tools and strategies |
