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B-E in Information Science Engineering at Cambridge Institute of Technology
Bengaluru, Karnataka
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About the Specialization
What is Information Science & Engineering at Cambridge Institute of Technology Bengaluru?
This Information Science & Engineering program at Cambridge Institute of Technology focuses on equipping students with robust skills in data management, computational intelligence, and software development. It integrates theoretical foundations with practical applications, addressing the growing demand for skilled professionals in India''''s digital transformation journey. The curriculum is designed to foster innovation and problem-solving abilities.
Who Should Apply?
This program is ideal for high school graduates with a strong aptitude for mathematics and logical reasoning seeking entry into the dynamic IT industry. It also caters to individuals passionate about developing software solutions, managing complex data systems, and exploring emerging fields like AI and Machine Learning. Aspiring engineers looking to contribute to India''''s technological advancements will find this course highly rewarding.
Why Choose This Course?
Graduates of this program can expect diverse career paths in India as software developers, data analysts, system architects, and AI/ML engineers in top tech companies and startups. Entry-level salaries typically range from INR 4-8 lakhs per annum, with experienced professionals earning significantly more. The strong curriculum aligns with industry certifications and fosters growth trajectories in product development and technical leadership roles.
Student Success Practices
Foundation Stage
Build a Strong Programming and Mathematical Foundation- (Semester 1-2)
Focus rigorously on mastering fundamental programming concepts (C, Data Structures) and engineering mathematics. Regularly practice coding problems on platforms like HackerRank or LeetCode, and solve complex mathematical problems from textbooks and previous year''''s papers.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, NPTEL courses on Data Structures and Algorithms, MATLAB
Career Connection
A solid foundation is crucial for excelling in technical interviews, competitive programming, and advanced subjects, opening doors to top IT roles.
Cultivate Effective Communication and Professional Skills- (Semester 1-2)
Actively participate in professional communication labs, group discussions, and presentations. Join college clubs focused on public speaking or debate to enhance soft skills. Practice writing professional emails, reports, and resumes to prepare for corporate interactions.
Tools & Resources
Toastmasters International clubs, Grammarly, LinkedIn, Institutional career guidance workshops
Career Connection
Strong communication and interpersonal skills are highly valued by employers for roles in consulting, project management, and client-facing positions.
Explore Core Engineering Disciplines and Interdisciplinary Learning- (Semester 1-2)
Engage with basic electrical, electronics, and mechanical engineering concepts beyond just exam preparation. Attend introductory workshops on robotics, IoT, or basic circuit design. Understand how different engineering fields interconnect, even if your specialization is IS.
Tools & Resources
Coursera, Udemy, Departmental workshops, Science exhibitions
Career Connection
A broad understanding of engineering principles helps in designing holistic solutions and fosters innovation in interdisciplinary projects.
Intermediate Stage
Master Data Management and Object-Oriented Paradigms- (Semester 3-5)
Deep dive into Object-Oriented Programming (Java/Python) and Database Management Systems. Work on mini-projects involving database design, SQL querying, and Java/Python application development. Contribute to open-source projects or create personal projects to apply concepts.
Tools & Resources
GitHub, MySQL/PostgreSQL, Eclipse/IntelliJ IDEA, PyCharm, HackerEarth contests
Career Connection
Essential for roles like Backend Developer, Database Administrator, Full-Stack Developer, and software engineers in any domain.
Gain Practical Exposure to Operating Systems and Networking- (Semester 4-5)
Understand the internals of operating systems through lab exercises and virtual machine experiments. Implement network protocols and secure communication channels in the Computer Networks lab. Participate in hackathons focused on system programming or network security.
Tools & Resources
Linux OS, Wireshark, Cisco Packet Tracer, VirtualBox/VMware, NPTEL courses on OS and Networks
Career Connection
Crucial for careers in DevOps, Network Engineering, System Administration, and cybersecurity, which are high-demand fields in India.
Develop Problem-Solving Skills with Algorithms and Web Technologies- (Semester 4-5)
Regularly practice algorithm design and analysis, solving problems on platforms like Codeforces or TopCoder. Build dynamic websites using HTML, CSS, JavaScript, and server-side scripting. Participate in web development bootcamps or build a personal portfolio website.
Tools & Resources
Codeforces, TopCoder, VS Code, Google Chrome Developer Tools, freeCodeCamp, Udemy courses on Web Development
Career Connection
Directly prepares students for roles in competitive programming, software development (frontend/backend), and product-based companies.
Advanced Stage
Specialize in AI/ML and Data Science- (Semester 6-8)
Focus on advanced subjects like Machine Learning, Deep Learning, and Data Science. Work on significant projects using real-world datasets, participate in Kaggle competitions, and pursue relevant certifications. Explore research papers and attend webinars on emerging trends.
Tools & Resources
Kaggle, TensorFlow, PyTorch, Scikit-learn, Google Colab, Coursera/edX specializations in AI/ML
Career Connection
Qualifies students for high-demand roles like Data Scientist, Machine Learning Engineer, AI Researcher, and Business Intelligence Analyst in India.
Engage in Industry Internships and Major Projects- (Semester 7-8)
Secure multiple internships in relevant industries to gain hands-on experience and build a professional network. Undertake a comprehensive final year project addressing a real-world problem, potentially in collaboration with an industry partner. Document thoroughly and present effectively.
Tools & Resources
LinkedIn for internship search, College placement cell, GitHub for project showcase, Professional mentors
Career Connection
Internships often lead to pre-placement offers, significantly boosting employability and providing practical skills valued by employers.
Prepare for Placements and Professional Growth- (Semester 7-8)
Actively participate in campus recruitment drives, practice aptitude tests, technical interviews, and group discussions. Develop a strong resume and LinkedIn profile. Network with alumni and industry professionals. Continuously learn new technologies and stay updated with industry trends.
Tools & Resources
Placement cell resources, Mock interview platforms, Resume builders, LinkedIn Learning, Industry newsletters
Career Connection
Direct path to securing desired job roles in leading tech companies, fostering long-term career growth and professional development in India.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 with Physics and Mathematics as compulsory subjects, along with Chemistry/Biotechnology/Biology/Electronics/Computer Science/Technical Vocational subject. Minimum 45% marks in aggregate (40% for SC/ST/OBC of Karnataka). Must have appeared for CET/COMEDK/JEE Mains/Any other equivalent entrance examination.
Duration: 8 semesters / 4 years
Credits: 172 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BSC101 | Engineering Mathematics – I | Basic Science | 3 | Differential Calculus, Integral Calculus, Partial Derivatives, Multiple Integrals, Vector Calculus |
| 23BHS102 | Professional Communication & Ethics | Humanities & Social Science | 2 | Introduction to Communication, Written Communication, Oral Communication, Professional Ethics, Environmental Ethics |
| 23BCE103 | Basic Electrical & Electronics Engineering | Core | 3 | DC Circuits, AC Circuits, Transformers, Diodes and Rectifiers, Transistors |
| 23BCS104 | Programming for Problem Solving | Core | 3 | Introduction to C, Operators and Expressions, Control Statements, Functions and Arrays, Pointers and Structures |
| 23BME105 | Elements of Mechanical Engineering | Core | 3 | Fundamentals of Thermodynamics, IC Engines, Refrigeration, Power Transmission, Material Science |
| 23BSC1L1 | Engineering Mathematics – I Lab | Lab | 1 | MATLAB basics, Numerical methods, Data visualization, Calculus applications, Differential equations solving |
| 23BHS1L2 | Professional Communication & Ethics Lab | Lab | 1 | Presentation skills, Group discussions, Resume writing, Interview techniques, Professional email writing |
| 23BCE1L3 | Basic Electrical & Electronics Engineering Lab | Lab | 1 | Ohm''''s law verification, Diode characteristics, Rectifier circuits, Transistor biasing, Op-amp circuits |
| 23BCS1L4 | Programming for Problem Solving Lab | Lab | 1 | C programs for control structures, Array operations, String manipulation, Function implementation, Pointers |
| 23BME1L5 | Elements of Mechanical Engineering Lab | Lab | 1 | Lathe operations, Welding, Sheet metal working, Foundry operations, Measurement tools |
| 23BHS106 | Universal Human Values | Humanities & Social Science | 1 | Self-exploration, Human values, Harmony in relationships, Society and nature, Professional ethics |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BSC201 | Engineering Mathematics – II | Basic Science | 3 | Linear Algebra, Eigenvalues and Eigenvectors, Vector Spaces, Complex Analysis, Laplace Transforms |
| 23BHS202A | Scientific Kannada | Mandatory Non-Credit | 0 | Basic Kannada grammar, Conversational Kannada, Technical vocabulary, Reading Kannada scripts |
| 23BCS203 | Data Structures | Core | 3 | Arrays and Pointers, Linked Lists, Stacks and Queues, Trees, Graphs |
| 23BEH204 | Engineering Chemistry | Basic Science | 3 | Electrochemistry, Corrosion, Water Technology, Fuels and Combustion, Polymers |
| 23BPC205 | Engineering Physics | Basic Science | 3 | Quantum Mechanics, Laser Physics, Fiber Optics, Semiconductor Physics, Nanoscience |
| 23BCS206 | Digital Logic Design | Core | 3 | Boolean Algebra, Logic Gates, Combinational Circuits, Sequential Circuits, Registers and Counters |
| 23BSC2L1 | Engineering Mathematics – II Lab | Lab | 1 | MATLAB for linear algebra, Complex numbers, Laplace transforms, Numerical methods, Vector operations |
| 23BCS2L3 | Data Structures Lab | Lab | 1 | Array implementation, Linked list operations, Stack/Queue applications, Tree traversals, Graph algorithms |
| 23BEH2L4 | Engineering Chemistry Lab | Lab | 1 | Water quality analysis, pH measurement, Viscosity determination, Polymer synthesis, Electroplating |
| 23BPC2L5 | Engineering Physics Lab | Lab | 1 | Laser experiments, Optical fiber communication, Semiconductor device characteristics, Photoelectric effect, Magnetic field measurement |
| 23BCS2L6 | Digital Logic Design Lab | Lab | 1 | Logic gate verification, Adders/Subtractors, Encoders/Decoders, Flip-flops, Counters |
| 23BHS207 | Technical English | Humanities & Social Science | 1 | Technical writing, Report writing, Research paper structure, Presentation skills, Group discussion strategies |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23ISE301 | Object Oriented Programming with JAVA | Core | 3 | Java Fundamentals, Classes and Objects, Inheritance and Polymorphism, Exception Handling, Collections |
| 23ISE302 | Operating Systems | Core | 3 | OS Structure, Process Management, CPU Scheduling, Deadlocks, Memory Management |
| 23ISE303 | Database Management Systems | Core | 3 | DBMS Architecture, ER Model, Relational Algebra, SQL, Normalization |
| 23ISE304 | Discrete Mathematical Structures | Core | 3 | Logic and Proofs, Set Theory, Relations and Functions, Graph Theory, Combinatorics |
| 23ISE305 | Automata Theory and Computability | Core | 3 | Finite Automata, Regular Expressions, Context-Free Grammars, Pushdown Automata, Turing Machines |
| 23ISE3L1 | Object Oriented Programming with JAVA Lab | Lab | 1 | Java program development, Object-oriented concepts, GUI programming, Database connectivity, Exception handling |
| 23ISE3L2 | Operating Systems Lab | Lab | 1 | Shell scripting, Process creation, Thread synchronization, Deadlock avoidance, Memory allocation |
| 23ISE3L3 | Database Management Systems Lab | Lab | 1 | SQL queries, Database design, ER diagram implementation, Stored procedures, Transaction management |
| 23ISE3P4 | Mini Project – I | Project | 1 | Problem identification, Requirement analysis, System design, Implementation, Project documentation |
| 23BHS306 | Kannada Language (Balake Kannada)/Aadalita Kannada | Mandatory Non-Credit | 0 | Spoken Kannada, Reading comprehension, Basic writing skills, Official correspondence (Aadalita Kannada) |
| 23BSC307 | Technical Skill Development | Mandatory Non-Credit | 0 | Problem-solving approaches, Analytical thinking, Basic debugging techniques, Teamwork and collaboration |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23ISE401 | Design and Analysis of Algorithms | Core | 3 | Algorithm analysis, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Backtracking |
| 23ISE402 | Computer Networks | Core | 3 | Network Topologies, OSI Model, TCP/IP Protocol Suite, Routing Algorithms, Network Security |
| 23ISE403 | Software Engineering | Core | 3 | Software Life Cycle, Requirements Engineering, Design Principles, Testing Strategies, Project Management |
| 23ISE404 | Python Programming | Core | 3 | Python Fundamentals, Data Structures in Python, Object-Oriented Programming, File Handling, Web Scraping |
| 23ISE405 | Web Technologies | Core | 3 | HTML, CSS, JavaScript, Web Servers, Database Connectivity (Web) |
| 23ISE4L1 | Design and Analysis of Algorithms Lab | Lab | 1 | Sorting algorithms, Graph traversal, Shortest path, Minimum spanning tree, Dynamic programming problems |
| 23ISE4L2 | Computer Networks Lab | Lab | 1 | Network configuration, Socket programming, Protocol implementation, Packet analysis, Network security tools |
| 23ISE4L4 | Python Programming Lab | Lab | 1 | Python scripts, Data analysis libraries, Web development with Python, GUI applications, Machine learning basics |
| 23ISE4L5 | Web Technologies Lab | Lab | 1 | HTML/CSS design, JavaScript interactivity, AJAX, Server-side scripting, Web application development |
| 23BHS406 | Environmental Science | Mandatory Non-Credit | 0 | Ecosystems, Biodiversity, Pollution control, Environmental protection, Sustainable development |
| 23BHS407 | Innovation and Design Thinking | Mandatory Non-Credit | 0 | Design thinking process, Ideation techniques, Prototyping, Innovation strategies, Problem-solving frameworks |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23ISE501 | Artificial Intelligence | Core | 3 | Problem Solving Agents, Search Algorithms, Knowledge Representation, Machine Learning Basics, Neural Networks |
| 23ISE521 | Advanced Java | Elective (Professional Elective – I) | 3 | AWT and Swing, Servlets and JSP, JDBC, Networking, RMI |
| 23BEC515 | Cyber Security | Elective (Open Elective – I) | 3 | Network Security, Cryptography, Web Security, Cyber Laws, Digital Forensics |
| 23ISE504 | Data Communication | Core | 3 | Signal Transmission, Digital Data Communication, Analog Data Communication, Multiplexing, Error Detection |
| 23ISE505 | Cloud Computing | Core | 3 | Cloud Architecture, Virtualization, Cloud Services (IaaS, PaaS, SaaS), Cloud Security, Deployment Models |
| 23ISE5L1 | Artificial Intelligence Lab | Lab | 1 | Search algorithm implementation, Knowledge representation, Machine learning algorithms, Neural network basics, AI project |
| 23ISE521L | Advanced Java Lab | Lab (Professional Elective – I Lab) | 1 | AWT/Swing applications, Servlet/JSP development, JDBC connectivity, RMI programming, Socket programming |
| 23ISE5P3 | Mini Project – II | Project | 1 | Advanced problem solving, Project planning, Implementation of complex modules, Testing, Technical report writing |
| 23ISE5S1 | Internship (Self Study) | Skill/Self-Study | 1 | Industry exposure, Project report, Presentation, Skill enhancement |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23ISE601 | Machine Learning | Core | 3 | Supervised Learning, Unsupervised Learning, Deep Learning, Reinforcement Learning, Model Evaluation |
| 23ISE621 | Big Data Analytics | Elective (Professional Elective – II) | 3 | Hadoop Ecosystem, MapReduce, HDFS, Spark, NoSQL Databases |
| 23BCE610 | Internet of Things | Elective (Open Elective – II) | 3 | IoT Architecture, Sensors and Actuators, Communication Protocols, Cloud Platforms for IoT, IoT Security |
| 23ISE604 | Data Science | Core | 3 | Data Collection, Data Cleaning, Exploratory Data Analysis, Statistical Modeling, Data Visualization |
| 23ISE605 | Information Storage and Management | Core | 3 | Storage Systems, Data Center Infrastructure, Backup and Recovery, Storage Networking, Cloud Storage |
| 23ISE6L1 | Machine Learning Lab | Lab | 1 | Python for ML, Supervised learning models, Unsupervised learning models, Deep learning frameworks, Model deployment |
| 23ISE621L | Big Data Analytics Lab | Lab (Professional Elective – II Lab) | 1 | Hadoop configuration, MapReduce programming, Spark applications, Hive queries, NoSQL operations |
| 23ISE6P3 | Mini Project – III | Project | 1 | Real-world problem solving, Advanced tool usage, Team collaboration, Project reporting, Presentation skills |
| 23ISE6S1 | Internship (Self Study) | Skill/Self-Study | 1 | Industry best practices, Advanced technical skills, Professional networking, Career planning |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23ISE701 | Deep Learning | Core | 3 | Neural Network Architectures, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, Deep Learning Frameworks |
| 23ISE724 | Blockchain Technology | Elective (Professional Elective – III) | 3 | Cryptocurrencies, Blockchain Architecture, Smart Contracts, Distributed Ledgers, Blockchain Applications |
| 23BHS711 | Intellectual Property Rights | Elective (Open Elective – III) | 3 | Patents, Copyrights, Trademarks, Trade Secrets, IPR Laws in India |
| 23ISE7L1 | Deep Learning Lab | Lab | 1 | TensorFlow/Keras, CNN implementation, RNN for sequence data, GANs, Transfer learning |
| 23ISE7P2 | Internship | Internship | 3 | Industry project, Professional skills, Report writing, Presentation, Real-world problem solving |
| 23ISE7P3 | Project Work Phase – I | Project | 3 | Problem definition, Literature survey, Design architecture, Module development, Preliminary results |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23ISE821 | Quantum Computing | Elective (Professional Elective – IV) | 3 | Quantum Mechanics Basics, Qubits, Quantum Gates, Quantum Algorithms, Quantum Cryptography |
| 23ISE8P2 | Project Work Phase – II | Project | 8 | Project implementation, Testing, Performance evaluation, Technical report, Viva-voce |
| 23ISE8S1 | Internship (Self Study) | Skill/Self-Study | 1 | Advanced industry practices, Skill specialization, Portfolio building, Career planning |
