B.Tech. Computer Science and Engineering

Curriculum

1ST SEMESTER SUBJECTS

Applied Physics provides fundamental knowledge of mechanics, waves, optics, electricity, magnetism, and modern physics, emphasizing practical applications and problem-solving skills essential for engineering and technological development.

Course Outcome:

At the end of the course, the student will be able to-
CO1: Acquire knowledge about the Maxwell equation and Electromagnetic spectrum
CO2: Understand laser system in industries, laboratories and in communication
CO3: Acquire knowledge about the Crystallography, superconductivity and Magnetic materials.
CO4: Appreciate the need for quantum mechanics, wave particle duality, uncertainty principle etc. and their applications.
CO5: Understand the properties and synthesis of nanomaterials.

Applied Physics Laboratory develops practical skills through experiments in mechanics, optics, electricity, magnetism, and semiconductor physics, enabling students to verify theoretical concepts, analyze experimental data, and understand physical phenomena.

Course Outcome:

At the end of the course, students will be:
CO1: Able to verify some of the theoretical concepts learnt in the theory courses.
CO2: Trained in carrying out precise measurements and handling sensitive equipment.
CO3: Introduced to the methods used for estimating and dealing with experimental uncertainties and systematic errors.
CO4: Learn to draw conclusions from data and develop skills in experimental design.
CO5: Write a technical report which communicates scientific information in a clear and concise manner.

Programming Concepts introduces the fundamentals of computer programming, including problem-solving techniques, algorithms, flowcharts, data types, operators, control structures, functions, and arrays, using a structured programming language.

Course Outcome:

At the end of the course, the students will able to be:
CO1: Describe the procedural and object-oriented paradigm with concepts of streams, classes, functions, data and objects.
CO2: Understand dynamic memory management techniques using pointers, constructors, destructors, etc.
CO3: Describe the concept of function overloading, operator overloading, virtual functions and polymorphism.
CO4: Understanding inheritance in OOP for code reusability and extensible design.
CO5: Demonstrate the use of various OOPs concepts with the help of programs.

Programming Concepts Lab provides hands-on practice in writing, debugging, and executing programs based on the concepts covered in programming Concepts, including control structures, functions, and arrays.

Course Outcome:

At the end of the course, the students will able to be:
CO1: Describe the procedural and object-oriented paradigm with concepts of streams, classes, functions, data and objects.
CO2: Understand dynamic memory management techniques using pointers, constructors, destructors, etc.
CO3: Describe the concept of function overloading, operator overloading, virtual functions and polymorphism.
CO4: Understanding inheritance in OOPs for code reusability and extensible design.
CO5: Demonstrate the use of various OOPs concepts with the help of programs.

This course provides evelops advanced concepts in multivariable calculus, vector calculus, differential equations, Laplace transforms, and numerical methods, equipping students with mathematical techniques for solving engineering problems.

Course Outcome:

At the end of the course, the students will be able to:
CO1: Able to verify some of the theoretical concepts learnt in the theory courses.
CO2: trained to visualize and conceptualize the engineering problems
CO3: Relate matrices and linear transformations, compute Eigen values and Eigen vectors of linear transformations.
CO4: Solve engineering problems by making use of ordinary differential equations.
CO5: Inter-relationship amongst the line integral, double and triple integral formulations.

Workshop Practices provides hands-on exposure to basic manufacturing trades such as carpentry, fitting, welding, sheet metal work, and plumbing, along with workshop safety practices.

Course Outcome:

At the end of the course, the students will be able to:
CO1: Prepare moulds, cores and wooden joints for basic manufacturing applications.
CO2: Perform basic welding operations and fabricate simple welded joints.
CO3: Carry out fitting and machining operations using conventional workshop tools and machines.
CO4: Fabricate simple products using sheet metal and forging processes.
CO5: Demonstrate basic electrical wiring, soldering and electronic circuit assembly practices.

Environmental Studies develops awareness of ecosystems, biodiversity, natural resources, pollution, climate change, environmental management, and sustainable development, encouraging responsible practices and informed solutions to environmental challenges.

Course Outcome:

At the end of the course, the students will be able to:
CO1: Analyse the impact of Biodiversity conservation on species and the environment.
CO2: Apply knowledge of environmental policies and legislations to evaluate and propose solutions for local and global environmental issues.
CO3: Implement environmental management plans to address campus environmental issues such as Waste disposal, water management, and sanitation.
CO4: Students will gain knowledge of the structure and function of ecosystems, biodiversity, and the importance of natural resources.
CO5: Recognize the interdependence between humans and the environment.

Communicative English-I develops foundational language skills in grammar, vocabulary, listening, speaking, reading, and writing for effective communication.

Course Outcome:

At the end of the course, the students will be able to:
CO1: Use standard English aptly in listening, speaking, and communicative situations
CO2: Write error-free sentences and short texts in English Language
CO3: Comprehend reading passages effectively
CO4: Demonstrate use of apt and relevant vocabulary at lower intermediate to intermediate level
CO5: Develop effective oral presentation skills, including audience analysis and body language
CO6: Apply audio-visual aids to enhance communication and improve pronunciation

This course develops an entrepreneurial mindset through self-awareness, creativity, innovation, opportunity recognition, problem-solving, communication, teamwork, leadership, and professional ethics. Students are introduced to the startup ecosystem, design thinking, business models, prototyping, value propositions, and idea pitching to encourage solution-oriented thinking and entrepreneurial initiative.

Course Outcome:

CO1: Demonstrate self-awareness, confidence and growth mindset.
CO2: Apply creativity and innovation tools to generate ideas and solutions.
CO3: Identify opportunities through analysis of real-life and community problems.
CO4: Demonstrate effective communication, teamwork and leadership skills.
CO5: Explain entrepreneurship concepts, startup ecosystem and support systems.
CO6: Develop and present a solution-oriented entrepreneurial project.

Open Source Technology covers the philosophy and practices of open-source software development, licensing models, collaborative development tools, and fundamentals of Linux-based operating systems.

Course Outcome:

CO1: To Gain thorough understanding of the fundamental concepts, history and principles of Open Source Software
CO2: Effectively use and contribute to open source projects
CO3: Apply best practices for managing Linux and deep understanding of Kernel and its processes
CO4: To understand the principles and applications of network security protocols in Linux.
CO5: Fair Understanding of Shell scripting and its fundamentals
CO6: To develop incident response plans and conduct forensic investigations to analyze and respond to security breaches.

Open-Source Technology Lab provides hands-on practice with Linux-based operating systems, open-source tools, and collaborative version-control platforms.

Course Outcome:

At the end of the course, the students will able to be:
CO1: Install and configure open-source virtualization software and Linux operating systems, and demonstrate familiarity with the Linux file system and shell environment.
CO2: Execute and manage Linux file and directory operations, and apply appropriate permission settings using command-line tools.
CO3: Work efficiently with Linux text editors (vi/vim) and understand their modes and operations for file editing and shell scripting.
CO4: Develop and execute basic shell scripts to perform arithmetic, file, string, and system-level operations using Bash scripting.
CO5: Build, compile, and execute C programs in a Linux environment using GCC and the Linux terminal.
CO6: Apply function-based logic in C programming to develop modular programs that perform tasks like swapping values, finding factorials, and reversing numbers.

2ND SEMESTER SUBJECTS

Applied Chemistry introduces fundamental chemical principles and their engineering applications, covering water chemistry, corrosion, materials, polymers, fuels, nanomaterials, spectroscopy, and green chemistry for sustainable technological development.

Course Outcome:

At the end of the course, the students will be able to achieve following outcomes:
CO1: Apply concepts of solution chemistry and water treatment for engineering applications and solve numerical problems related to concentration and hardness of water.
CO2: Describe the principles and applications of spectroscopic techniques (UV-Visible, IR, and NMR) for molecular characterization.
CO3: Explain the principles, classifications, and applications of chemical sensors used in environmental, biomedical, and industrial fields.
CO4: Classify polymers and explain their properties, synthesis, and applications in engineering and industrial sectors.
CO5: Analyze stereo chemical properties of organic molecules, determine molecular configurations, and interpret conformational stability.
CO6: Explain the mechanisms of organic reactions including substitution, addition, and elimination reactions, and apply them in basic organic synthesis.

Applied Chemistry Laboratory develops practical skills through experiments involving water analysis, corrosion, chemical reactions, material characterization, solution preparation, and analytical techniques, emphasizing safety, accuracy, and scientific interpretation.

Course Outcome:

At the end of the course, the students will be able to:
CO1: Demonstrate proficiency in laboratory safety practices, handling of chemical reagents, preparation of standard solutions, and the use of volumetric analysis apparatus.
CO2: Perform acid–base and redox titrations to determine the concentration or strength of unknown solutions and analyze experimental results accurately.
CO3: Determine physicochemical properties of samples, including pH, total hardness, total alkalinity, surface tension, viscosity, redox potential, and partition coefficient using appropriate analytical techniques.
CO4: Carry out organic chemistry experiments, including the preparation of iodoform, differentiation between aldehydes and ketones using qualitative tests, and separation of compounds by thin-layer chromatography.
CO5: Synthesize polymers or drugs and evaluate the properties of oils through saponification and acid value determination using standard laboratory methods.
CO6: Record experimental observations, perform calculations, interpret analytical data, and prepare laboratory reports while adhering to good laboratory practices and safety guidelines.

This course introduces fundamental concepts of electrical and electronic engineering, including circuits, electrical machines, semiconductor devices, digital systems, measurements, and practical applications in engineering and technology.

Course Outcome:

At the end of the course the students will be able to:
CO1: To Understand the fundamental concepts of electricity, such as voltage, current, resistance, power, and energy.
CO2: To understand AC and DC fundamentals and measure power factor in given circuit.
CO3: Describe the characteristics and applications of diodes and transistors.
CO4: To understand Electrical safety and explain the construction, working principle, performance and applications of transformers.
CO5: Understand number systems, logic gates, and basic combinational circuits.
CO6: Apply Boolean algebra and Karnaugh maps to simplify and design digital logic circuits.

This laboratory develops practical skills in electrical circuits, measurements, electronic components, semiconductor devices, digital circuits, and basic electrical systems through experiments, testing, analysis, and troubleshooting techniques.

Course Outcome:

At the end of the course, the students will be able to:
CO1: Understand the fundamental concepts of electricity, such as voltage, current, resistance, power, and energy
CO2: Develop the ability to analyze electrical circuits using techniques such as Ohm's law, Kirchhoff's laws, and network theorems.
CO3: Plot the I-V characteristics of various semiconductor devices.
CO4: Design electrical and electronic circuits by utilizing various components.
CO5: Verify the truth tables of various logic gates

This course provides advanced concepts in multivariable calculus, vector calculus, differential equations, Laplace transforms, and numerical methods, equipping students with mathematical techniques for solving engineering problems.

Course Outcome:

At the end of the course, the students will be able to:
CO1: Apply derivative tests in optimization problems appearing in social sciences, physical sciences, life sciences and a host of other disciplines.
CO2: Understand conceptual variations while advancing from one variable to several variables in calculus.
CO3: Find numerical solutions of system of linear equations and check the accuracy of the solutions.
CO4: Solve initial and boundary value problems in differential equations using numerical methods.
CO5: To find and analyze solution of Laplace equation using different numerical methods.

Engineering Drawing covers principles of orthographic projection, sectional views, isometric and pictorial drawings, and an introduction to computer-aided drafting (CAD).

Course Outcome:

At the end of the course, the students will be able to:
CO1: Identify and use engineering drawing instruments, symbols, and conventions.
CO2: Understand and apply projection methods for points, lines, planes, and solids.
CO3: Create accurate 2D drawings using scales and dimensioning techniques.
CO4: Generate isometric (3D) drawings from 2D orthographic views.
CO5: Use basic CAD tools to create and modify engineering drawings digitally.

Universal Human Values, covering self-awareness, love, compassion, truth, non-violence, righteousness, sacrifice, and inner transformation. Students will develop ethical decision-making, empathy, emotional intelligence, self-reflection, and value-based thinking for personal and professional life.

Course Outcome:

CO1: Define and identify core universal human values and relate them to their own lives.
CO2: Demonstrate self-awareness and initiate personal transformation (Human Revolution)
CO3: Appreciate the importance of Sewa (selfless service), compassion, and empathy.
CO4: Apply principles of truth, non-violence, and moral responsibility in real-life dilemmas.
CO5: Evaluate ethical decisions involving sacrifice and righteousness through case studies.
CO6: Reflect on the relevance of renunciation and simplicity in modern life for inner peace.

Communicative English II builds on foundational language skills with emphasis on advanced communication, presentation skills, group discussions, and technical writing.

Course Outcome:

CO1: Able to apply advanced English language skills for effective academic and professional communication.
CO2: Able to communicate ideas, information and opinions confidently through effective speaking and listening skills.
CO3: Able to comprehend, analyze and interpret various forms of written and spoken English.
CO4: Able to prepare effective professional documents such as emails, reports, presentations and resumes.
CO5: Able to demonstrate effective interpersonal, presentation and communication skills in academic and professional situations.

Entrepreneurship Mindset-II covers business planning, understanding the startup ecosystem, funding avenues, and effective pitching of business ideas.

Course Outcome:

CO1: Able to understand and apply entrepreneurial concepts, principles and practices in identifying business opportunities.
CO2: Able to develop an entrepreneurial mindset through creativity, innovation, critical thinking and effective decision-making.
CO3: Able to identify customer needs and evaluate business ideas based on market opportunities and feasibility.
CO4: Able to develop basic business models and strategies for starting and managing entrepreneurial ventures.
CO5: Able to demonstrate leadership, teamwork, risk-taking and problem-solving skills for successful entrepreneurial development.

Python Programming covers Python syntax and semantics, data structures, control flow, functions, object-oriented programming, file handling, and modules, with applications in data-driven programming.

Course Outcome:

At the end of the course, the students will able to be:
CO1: Explain Python syntax, programming constructs, and problem-solving methodologies.
CO2: Develop programs using control structures, functions, recursion, and functional programming concepts.
CO3: Apply Python data structures and string processing techniques to solve computational problems.
CO4: Design modular programs using packages, modules, and file processing techniques.
CO5: Implement object-oriented solutions using classes, inheritance, polymorphism, and abstraction.
CO6: Utilize Python libraries for data analysis, visualization, and basic application development.

Python Programming Lab provides hands-on practice in writing and executing Python programs covering data structures, control flow, functions, object-oriented programming, and file handling.

Course Outcome:

At the end of the course, the students will be able to:
CO1: Write simple Python programs using basic syntax, control structures, and loops.
CO2: Apply Python’s data structures such as lists, dictionaries, tuples, and sets for data organization.
CO3: Implement modular programs using user-defined functions and recursion.
CO4: Handle file operations and apply exception handling for robust programs.
CO5: Demonstrate object-oriented programming concepts such as class, inheritance, and polymorphism.
CO6: Develop mini-projects using Python integrating multiple programming concepts.

3RD SEMESTER SUBJECTS

Covers fundamentals of database design, the relational model, SQL, normalization, and transaction management.

Course Outcome:

CO1: Understand basic concepts of database systems and the relational data model.
CO2: Design ER diagrams and convert them into relational schemas.
CO3: Formulate queries using SQL and relational algebra.
CO4: Apply normalization techniques to design efficient, redundancy-free databases.
CO5: Understand transaction management, concurrency control, and recovery techniques.
CO6: Explore concepts of indexing and query optimization.

Hands-on lab for designing databases and implementing SQL queries using RDBMS tools.

Course Outcome:

CO1: Create and manipulate databases using DDL and DML commands.
CO2: Write and execute simple to complex SQL queries.
CO3: Implement joins, subqueries, and views.
CO4: Design and implement PL/SQL procedures, functions, and triggers.
CO5: Apply normalization and ER modeling to real-world case studies.

Introduces linear and non-linear data structures along with algorithm design and analysis techniques.

Course Outcome:

CO1: Understand asymptotic notations and analyze the time/space complexity of algorithms.
CO2: Implement linear data structures such as arrays, stacks, queues, and linked lists.
CO3: Implement non-linear data structures such as trees and graphs.
CO4: Apply searching and sorting algorithms to solve computational problems.
CO5: Understand hashing techniques and their applications.
CO6: Design efficient algorithms using divide-and-conquer, greedy, and dynamic programming approaches.

Lab-based implementation of data structures and algorithmic problem-solving using a programming language.

Course Outcome:

CO1: Implement stacks, queues, and linked lists programmatically.
CO2: Implement tree and graph traversal algorithms.
CO3: Implement and compare various sorting and searching techniques.
CO4: Apply data structures to solve real-world computational problems.
CO5: Analyze the time complexity of implemented algorithms.

Covers advanced mathematical techniques including transforms, numerical methods, and probability essential for engineering applications.

Course Outcome:

CO1: Apply Laplace and Fourier transforms to solve engineering problems.
CO2: Solve differential equations using series solutions and special functions.
CO3: Apply numerical methods for solving algebraic and differential equations.
CO4: Understand concepts of probability and statistical distributions.
CO5: Apply vector calculus concepts to engineering problems.

Introduces core AI concepts, search techniques, knowledge representation, and intelligent agent design.

Course Outcome:

CO1: Understand the fundamentals of AI and intelligent agents.
CO2: Apply uninformed and informed search techniques to solve problems.
CO3: Represent knowledge using logic-based and semantic approaches.
CO4: Understand the basics of machine learning and its role in AI systems.
CO5: Apply AI techniques to design simple intelligent systems.
CO6: Understand ethical and societal implications of AI.

Builds entrepreneurial thinking, business planning, and innovation skills through practical exposure.

Course Outcome:

CO1: Understand the entrepreneurial mindset and identify business opportunities.
CO2: Develop a basic business model and plan for a venture idea.
CO3: Understand fundamentals of innovation, risk-taking, and value creation.
CO4: Apply financial and marketing basics to a proposed venture.
CO5: Present and pitch a business idea effectively.

Covers web development fundamentals including HTML, CSS, JavaScript, and modern frontend frameworks.

Course Outcome:

CO1: Design responsive web pages using HTML5 and CSS3.
CO2: Apply JavaScript for dynamic client-side interactivity.
CO3: Understand DOM manipulation and event handling.
CO4: Build responsive layouts using frameworks such as Bootstrap.
CO5: Develop simple single-page applications using a modern frontend framework.
CO6: Understand principles of UI/UX design for web applications.

Hands-on lab for building responsive and interactive web pages using HTML, CSS, JavaScript, and frontend frameworks.

Course Outcome:

CO1: Design and implement static and responsive web pages.
CO2: Implement client-side scripting using JavaScript.
CO3: Build interactive web components using DOM manipulation.
CO4: Develop a mini-project using a frontend framework.
CO5: Apply version control basics for web project development.

Introduces foundational concepts of Artificial Intelligence including problem-solving, search, and reasoning techniques.

Course Outcome:

CO1: Understand the history, scope, and applications of AI.
CO2: Apply problem-solving techniques using search strategies.
CO3: Understand knowledge representation and reasoning approaches.
CO4: Understand the basics of machine learning algorithms.
CO5: Explore real-world applications of AI across domains.

Practical lab exposure to AI programming tools, libraries, and basic machine learning implementations.

Course Outcome:

CO1: Implement basic AI search algorithms programmatically.
CO2: Use Python libraries for data handling and preprocessing.
CO3: Implement simple machine learning models using standard datasets.
CO4: Evaluate model performance using basic metrics.
CO5: Apply AI tools to solve a mini real-world problem.

4TH SEMESTER SUBJECTS

Covers algorithm design paradigms, complexity analysis, and advanced algorithmic techniques for problem-solving.

Course Outcome:

CO1: Analyze the time and space complexity of algorithms using asymptotic notations.
CO2: Design algorithms using divide-and-conquer, greedy, and dynamic programming strategies.
CO3: Apply graph algorithms for shortest path, spanning tree, and network flow problems.
CO4: Understand backtracking and branch-and-bound techniques.
CO5: Analyze NP-completeness and classify problems based on computational complexity.
CO6: Design and evaluate efficient algorithms for real-world computational problems.

Lab-based implementation and performance analysis of algorithm design techniques.

Course Outcome:

CO1: Implement divide-and-conquer algorithms and analyze their performance.
CO2: Implement greedy and dynamic programming based solutions.
CO3: Implement graph algorithms for traversal, shortest path, and spanning trees.
CO4: Implement backtracking algorithms for constraint satisfaction problems.
CO5: Compare and evaluate algorithm efficiency using empirical analysis.

Introduces networking concepts, protocols, and architectures across the OSI and TCP/IP layers.

Course Outcome:

CO1: Understand network architectures, topologies, and the OSI/TCP-IP reference models.
CO2: Analyze data link layer protocols including error detection and correction techniques.
CO3: Understand network layer concepts including routing algorithms and IP addressing.
CO4: Analyze transport layer protocols and congestion control mechanisms.
CO5: Understand application layer protocols and their real-world implementations.
CO6: Explore network security fundamentals and emerging networking technologies.

Hands-on lab for network configuration, simulation, and protocol analysis.

Course Outcome:

CO1: Configure basic networking devices and IP addressing schemes.
CO2: Simulate network topologies using networking tools/simulators.
CO3: Analyze network traffic and protocols using packet capture tools.
CO4: Implement socket programming for client-server communication.
CO5: Troubleshoot common networking issues in a lab environment.

Covers mathematical foundations including set theory, logic, graph theory, and combinatorics for computer science.

Course Outcome:

CO1: Apply propositional and predicate logic to solve reasoning problems.
CO2: Understand set theory, relations, and functions.
CO3: Apply combinatorics and counting principles to solve problems.
CO4: Understand graph theory concepts including trees, graphs, and their applications.
CO5: Apply algebraic structures such as groups and lattices to computer science problems.

Introduces operating system concepts including process management, memory management, and file systems.

Course Outcome:

CO1: Understand the structure, functions, and types of operating systems.
CO2: Apply process scheduling algorithms and understand process synchronization.
CO3: Understand deadlock detection, prevention, and avoidance techniques.
CO4: Apply memory management techniques including paging and segmentation.
CO5: Understand file system organization and disk scheduling algorithms.
CO6: Explore concepts of virtualization and modern operating systems.

Hands-on lab for implementing OS concepts using shell scripting and system calls.

Course Outcome:

CO1: Implement basic Linux/Unix commands and shell scripts.
CO2: Implement process creation and synchronization using system calls.
CO3: Implement CPU scheduling algorithms programmatically.
CO4: Implement memory management techniques such as paging.
CO5: Implement solutions for classical process synchronization problems.

Covers computer system architecture, instruction sets, memory hierarchy, and processor design.

Course Outcome:

CO1: Understand basic computer organization and functional units.
CO2: Analyze instruction set architectures and addressing modes.
CO3: Understand arithmetic and logic unit design and computer arithmetic.
CO4: Understand memory hierarchy including cache and virtual memory.
CO5: Understand pipelining and instruction-level parallelism.
CO6: Explore I/O organization and multiprocessor architectures.

Covers full-stack web development using MongoDB, Express.js, React, and Node.js.

Course Outcome:

CO1: Design responsive front-end interfaces using React.
CO2: Build RESTful APIs using Node.js and Express.js.
CO3: Design and integrate MongoDB databases with web applications.
CO4: Implement authentication and state management in MERN applications.
CO5: Deploy full-stack web applications using modern deployment practices.

Hands-on lab for building full-stack applications using the MERN stack.

Course Outcome:

CO1: Build React components and manage application state.
CO2: Develop and test RESTful APIs using Express.js and Node.js.
CO3: Design and query MongoDB collections.
CO4: Integrate front-end and back-end components into a full-stack application.
CO5: Develop a mini-project using the complete MERN stack.

Introduces SEO principles, techniques, and tools for improving website visibility and ranking.

Course Outcome:

CO1: Understand fundamentals of search engines and ranking algorithms.
CO2: Apply on-page SEO techniques including keyword research and content optimization.
CO3: Apply off-page SEO techniques including link building and outreach.
CO4: Analyze website performance using SEO tools and analytics.
CO5: Understand technical SEO concepts including site structure and mobile optimization.

Practical lab for implementing SEO strategies on real or sample websites.

Course Outcome:

CO1: Perform keyword research and competitor analysis.
CO2: Implement on-page optimization techniques on a sample website.
CO3: Use SEO tools to audit and analyze website performance.
CO4: Implement basic link-building and content marketing strategies.
CO5: Prepare an SEO performance report using analytics tools.

Builds entrepreneurial thinking and practical business skills through case studies and projects.

Course Outcome:

CO1: Understand advanced concepts of entrepreneurship and business growth.
CO2: Analyze case studies of successful startups and ventures.
CO3: Develop strategies for scaling and sustaining a business.
CO4: Apply leadership and team-building concepts to entrepreneurial ventures.
CO5: Present a refined business plan incorporating market feedback.

5TH SEMESTER SUBJECTS

Covers software development life cycle, requirement analysis, design, and project management principles.

Course Outcome:

CO1: Understand software process models and the software development life cycle.
CO2: Apply requirement elicitation and analysis techniques.
CO3: Apply software design principles including modularity and design patterns.
CO4: Understand software testing techniques and quality assurance practices.
CO5: Apply project management and estimation techniques for software projects.
CO6: Understand software maintenance and configuration management.

Introduces formal languages, automata theory, and computability concepts.

Course Outcome:

CO1: Understand finite automata and regular languages.
CO2: Design context-free grammars and analyze pushdown automata.
CO3: Understand Turing machines and their role in computability.
CO4: Classify problems based on decidability and undecidability.
CO5: Understand complexity classes including P and NP.

Covers object-oriented programming concepts and application development using Java.

Course Outcome:

CO1: Understand the history, features, and fundamental elements of Java programming.
CO2: Apply object-oriented concepts including classes, objects, and inheritance.
CO3: Implement interfaces, packages, and exception handling in Java.
CO4: Understand multithreading and concurrent programming in Java.
CO5: Implement GUI applications using AWT/Swing.
CO6: Handle file I/O and stream operations in Java.

Hands-on lab for developing Java applications using object-oriented concepts.

Course Outcome:

CO1: Implement basic Java programs using core language constructs.
CO2: Implement classes, objects, and inheritance-based programs.
CO3: Implement exception handling and multithreading programs.
CO4: Develop GUI-based applications using Java.
CO5: Implement file handling operations in Java.

Covers information security principles, cryptography basics, and cyber law frameworks.

Course Outcome:

CO1: Understand fundamentals of information security and threat models.
CO2: Apply cryptographic techniques for data confidentiality and integrity.
CO3: Understand network and application security mechanisms.
CO4: Understand cyber laws, IT Act provisions, and compliance requirements.
CO5: Analyze case studies of cybercrimes and security breaches.

Introduces ethical hacking methodologies, tools, and penetration testing techniques.

Course Outcome:

CO1: Understand the fundamentals and phases of ethical hacking.
CO2: Perform reconnaissance and scanning using penetration testing tools.
CO3: Identify and exploit common vulnerabilities in systems and networks.
CO4: Understand web application security testing techniques.
CO5: Prepare penetration testing reports following ethical and legal guidelines.

Hands-on lab for practicing ethical hacking and penetration testing techniques.

Course Outcome:

CO1: Perform network scanning and vulnerability assessment using standard tools.
CO2: Exploit system and application vulnerabilities in a controlled lab environment.
CO3: Perform web application penetration testing.
CO4: Use password cracking and social engineering awareness techniques.
CO5: Document findings in a professional penetration testing report.

Covers cloud computing concepts, service models, deployment models, and virtualization technologies.

Course Outcome:

CO1: Understand cloud computing fundamentals, service models, and deployment models.
CO2: Understand virtualization technologies and their role in cloud computing.
CO3: Explore cloud storage, security, and resource management concepts.
CO4: Understand cloud service platforms such as AWS/Azure/GCP.
CO5: Analyze cloud computing applications and emerging trends.

Hands-on lab for deploying and managing applications on cloud platforms.

Course Outcome:

CO1: Create and configure virtual machines/instances on a cloud platform.
CO2: Deploy web applications using cloud services.
CO3: Configure cloud storage and database services.
CO4: Implement basic cloud security configurations.
CO5: Monitor and manage cloud resources using platform tools.

Evaluation of industrial/summer training undertaken by students to assess practical exposure gained.

Course Outcome:

CO1: Demonstrate understanding of the industrial/organizational environment.
CO2: Apply theoretical knowledge to practical, real-world tasks undertaken during training.
CO3: Present and document the training experience through a report and viva-voce.
CO4: Reflect on skills gained and their relevance to career development.

Develops logical reasoning, quantitative aptitude, and analytical problem-solving skills.

Course Outcome:

CO1: Apply logical reasoning techniques to solve analytical problems.
CO2: Solve quantitative aptitude problems involving numbers and arithmetic.
CO3: Apply data interpretation techniques to analyze given data sets.
CO4: Develop problem-solving strategies for competitive examinations.

Advanced module on entrepreneurship focusing on innovation, funding, and venture execution.

Course Outcome:

CO1: Understand advanced funding options and investment readiness for startups.
CO2: Apply innovation management techniques to venture development.
CO3: Understand legal and regulatory aspects of starting a business.
CO4: Develop a comprehensive venture execution plan.
CO5: Present a pitch incorporating financial and operational planning.

6TH SEMESTER SUBJECTS

Covers cryptographic algorithms, network security protocols, and mechanisms to secure data communication.

Course Outcome:

CO1: Understand fundamentals of network security and cryptographic principles.
CO2: Apply symmetric and asymmetric encryption algorithms for data security.
CO3: Understand hash functions, digital signatures, and message authentication.
CO4: Apply key management and public key infrastructure concepts.
CO5: Understand network security protocols such as SSL/TLS, IPSec, and firewalls.
CO6: Analyze security threats and countermeasures in networked systems.

Hands-on lab for implementing cryptographic algorithms and network security techniques.

Course Outcome:

CO1: Implement classical and modern encryption algorithms.
CO2: Implement hashing and digital signature techniques.
CO3: Configure firewalls and basic network security tools.
CO4: Analyze network traffic for security vulnerabilities.
CO5: Implement secure communication using SSL/TLS concepts.

Covers advanced data structures and their applications in efficient algorithm design.

Course Outcome:

CO1: Understand advanced tree structures such as AVL, B-trees, and Red-Black trees.
CO2: Implement advanced graph algorithms and their applications.
CO3: Understand heap structures and priority queue implementations.
CO4: Apply hashing techniques and collision resolution strategies.
CO5: Understand advanced string matching and pattern searching algorithms.
CO6: Analyze the performance trade-offs of advanced data structures.

Lab-based implementation of advanced data structures and their applications.

Course Outcome:

CO1: Implement balanced tree structures such as AVL and B-trees.
CO2: Implement heap-based priority queues.
CO3: Implement advanced graph algorithms programmatically.
CO4: Implement hashing techniques with collision handling.
CO5: Implement string matching algorithms.

Introduces the phases of compiler construction including lexical analysis, parsing, and code generation.

Course Outcome:

CO1: Understand the phases and structure of a compiler.
CO2: Design lexical analyzers using regular expressions and finite automata.
CO3: Design parsers using context-free grammars and parsing techniques.
CO4: Understand syntax-directed translation and intermediate code generation.
CO5: Understand code optimization and target code generation techniques.
CO6: Explore error detection and recovery mechanisms in compilers.

Covers data warehouse architecture, OLAP concepts, and data mining techniques for knowledge discovery.

Course Outcome:

CO1: Understand data warehouse architecture and multidimensional data models.
CO2: Apply OLAP operations for data analysis.
CO3: Understand data preprocessing techniques for data mining.
CO4: Apply classification and clustering algorithms for pattern discovery.
CO5: Understand association rule mining techniques.
CO6: Explore applications of data mining in real-world domains.

Introduces user interface and user experience design principles for creating effective digital products.

Course Outcome:

CO1: Understand fundamentals of UI/UX design and design thinking.
CO2: Apply wireframing and prototyping techniques.
CO3: Understand usability principles and user research methods.
CO4: Design responsive and accessible user interfaces.
CO5: Evaluate designs through usability testing.

Hands-on lab for creating wireframes, prototypes, and interactive designs using design tools.

Course Outcome:

CO1: Create wireframes and mockups using design tools.
CO2: Develop interactive prototypes for web/mobile applications.
CO3: Apply usability heuristics to evaluate designs.
CO4: Conduct basic user research and testing.
CO5: Design a complete UI/UX case study project.

Covers business intelligence concepts, data analytics, and reporting tools for decision-making.

Course Outcome:

CO1: Understand fundamentals of business intelligence and decision support systems.
CO2: Apply ETL processes for data integration.
CO3: Design dashboards and reports using BI tools.
CO4: Apply data visualization techniques for business insights.
CO5: Understand predictive analytics concepts in a business context.

Hands-on lab for building dashboards and reports using business intelligence tools.

Course Outcome:

CO1: Perform data extraction, transformation, and loading using BI tools.
CO2: Build interactive dashboards using visualization tools such as Power BI.
CO3: Design reports for business decision-making.
CO4: Apply data modeling techniques in a BI tool.
CO5: Present business insights derived from data analysis.

Builds advanced logical reasoning, quantitative aptitude, and analytical problem-solving skills.

Course Outcome:

CO1: Apply advanced logical reasoning techniques to complex problems.
CO2: Solve advanced quantitative aptitude problems.
CO3: Apply data sufficiency and interpretation techniques.
CO4: Develop strategies for competitive and placement examinations.

Provides students hands-on experience in identifying, designing, and initiating a substantial project applying learned concepts.

Course Outcome:

CO1: Identify a real-world problem and formulate project objectives.
CO2: Conduct literature review and requirement analysis for the project.
CO3: Design the system architecture and methodology for the project.
CO4: Develop an initial working prototype of the proposed solution.
CO5: Present and document the project progress through reports and reviews.

Focuses on developing communication, interpersonal, and professional workplace skills.

Course Outcome:

CO1: Develop effective verbal and written communication skills.
CO2: Apply interpersonal and teamwork skills in professional settings.
CO3: Understand workplace etiquette and professional ethics.
CO4: Develop resume writing and interview preparation skills.

7TH SEMESTER SUBJECTS

Introduces image processing fundamentals and computer vision techniques for visual data analysis.

Course Outcome:

CO1: Understand fundamentals of digital image processing and representation.
CO2: Apply image filtering, enhancement, and edge detection techniques.
CO3: Understand feature extraction and object detection techniques.
CO4: Apply image segmentation and classification techniques.
CO5: Understand deep learning approaches for computer vision tasks.
CO6: Explore real-world applications of computer vision.

Covers Internet of Things architecture, protocols, and applications for connected devices.

Course Outcome:

CO1: Understand IoT architecture, components, and protocols.
CO2: Apply sensor and actuator interfacing concepts.
CO3: Understand communication protocols used in IoT systems.
CO4: Apply cloud integration concepts for IoT data management.
CO5: Understand IoT security challenges and solutions.
CO6: Explore real-world IoT application domains.

Hands-on lab for building IoT-based projects using microcontrollers, sensors, and connectivity modules.

Course Outcome:

CO1: Interface sensors and actuators with microcontroller boards.
CO2: Implement basic IoT communication protocols.
CO3: Develop IoT applications with cloud data integration.
CO4: Implement basic IoT security measures.
CO5: Build and demonstrate a working IoT-based mini-project.

Introduces principles of designing scalable, reliable, and maintainable software systems.

Course Outcome:

CO1: Understand fundamentals of system design and design trade-offs.
CO2: Apply scalability concepts including load balancing and caching.
CO3: Design database and storage solutions for large-scale systems.
CO4: Understand microservices architecture and distributed system design.
CO5: Design fault-tolerant and highly available systems.
CO6: Apply system design principles to real-world case studies.

Introduces blockchain concepts, architecture, and applications in decentralized systems.

Course Outcome:

CO1: Understand fundamentals of blockchain technology and distributed ledgers.
CO2: Understand consensus mechanisms used in blockchain networks.
CO3: Apply smart contract concepts for decentralized applications.
CO4: Understand cryptocurrency and blockchain-based financial systems.
CO5: Explore blockchain applications beyond cryptocurrency.

Hands-on lab for developing and deploying blockchain-based applications and smart contracts.

Course Outcome:

CO1: Set up a basic blockchain network environment.
CO2: Develop and deploy smart contracts.
CO3: Build a simple decentralized application (DApp).
CO4: Implement basic cryptocurrency transaction simulations.
CO5: Evaluate blockchain applications for real-world use cases.

Introduces research methods, ethics, and technical writing skills for academic and applied research.

Course Outcome:

CO1: Understand fundamentals of research design and methodology.
CO2: Apply literature review and research problem formulation techniques.
CO3: Understand data collection and analysis methods for research.
CO4: Apply research ethics and plagiarism-avoidance practices.
CO5: Develop skills for writing and presenting research papers.

Covers agile methodologies, frameworks, and practices for iterative software development.

Course Outcome:

CO1: Understand agile principles and the agile manifesto.
CO2: Apply Scrum framework practices including sprints and ceremonies.
CO3: Apply Kanban and other agile project management techniques.
CO4: Understand agile estimation and planning techniques.
CO5: Apply continuous integration and delivery practices in agile projects.

Hands-on lab for practicing agile ceremonies and tools in a simulated project environment.

Course Outcome:

CO1: Plan and execute sprints using agile project management tools.
CO2: Conduct agile ceremonies such as stand-ups and retrospectives.
CO3: Create and manage a product backlog.
CO4: Apply agile estimation techniques to project tasks.
CO5: Demonstrate incremental delivery of a mini-project using agile practices.

Introduces ad-hoc network architectures, routing protocols, and wireless sensor network concepts.

Course Outcome:

CO1: Understand fundamentals of ad-hoc and wireless sensor networks.
CO2: Analyze routing protocols used in ad-hoc networks.
CO3: Understand energy-efficient design considerations in sensor networks.
CO4: Understand data aggregation and communication techniques in WSNs.
CO5: Explore security challenges and applications of WSNs.

Hands-on lab for simulating ad-hoc networks and wireless sensor network scenarios.

Course Outcome:

CO1: Simulate ad-hoc network topologies using networking simulators.
CO2: Implement and analyze routing protocols in simulation.
CO3: Simulate sensor node deployment and data collection scenarios.
CO4: Analyze network performance metrics in simulated WSN scenarios.
CO5: Evaluate energy efficiency in simulated sensor network models.

Continuation of the capstone project focusing on implementation, testing, and final deployment.

Course Outcome:

CO1: Implement the complete proposed system based on the earlier design.
CO2: Conduct testing and validation of the developed system.
CO3: Refine the solution based on evaluation and feedback.
CO4: Document the complete project methodology, results, and outcomes.
CO5: Present and defend the final project through a viva-voce/demonstration.

Focuses on advanced professional skills including leadership, career readiness, and workplace communication.

Course Outcome:

CO1: Develop advanced presentation and public speaking skills.
CO2: Apply leadership and team management concepts in professional settings.
CO3: Prepare for competitive job interviews and group discussions.
CO4: Understand corporate work culture and professional networking practices.

8TH SEMESTER SUBJECTS

Provides students with industry exposure through a structured training/internship period to apply academic knowledge in a professional environment.

Course Outcome:

CO1: Demonstrate understanding of industry practices, tools, and work culture.
CO2: Apply academic knowledge and skills to real-world industrial tasks.
CO3: Develop professional and technical skills relevant to the chosen domain.
CO4: Present the outcomes of industrial training through a report and viva-voce.

Details	Amount
Programme Fees (per Semester)	₹75000
Examination Fees	₹3000
International Fees (per Year)	$4300

Admissions
Open 2026-27

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