| 1 | Computer Organization | 24MC1T02 | First Semester | Theory | 5 | - CO1: Understand the basic types of computers and their key functional units
- CO2: Develop and implement programs using machine instructions and addressing modes, including stack and queue operations.
- CO3: Analyse various input/output techniques like interrupt-driven I/O, Direct Memory Access (DMA), and standard I/O interfaces.
- CO4: Understand and evaluate the performance trade-offs in memory systems, focusing on RAM, ROM, cache, and virtual memory.
- CO5: Explain the concepts of parallel processing, including pipeline processors and multiprocessor systems, and their impact on performance.
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| 2 | Data Structures | 24MC1T01 | First Semester | Theory | 5 | - CO1: Implement basic programs by using C concepts
- CO2: Implement C Program using Functions, Structures and
Unions, Pointers
- CO3: Design advanced Data Structures using Non Linear Data Structures
- CO4: Create Hash Table for storing data
- CO5: Apply appropriate Sorting technique for a problem
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| 3 | Database Management Systems | 24MC1T03 | First Semester | Theory | 5 | - CO1: Explain the purpose, architecture, and various applications of database systems, as well as the role of data models (ER models) and how they relate to database design.
- CO2: Demonstrate the application of the relational model, integrity constraints, and query relational data using relational algebra and calculus. Convert ER diagrams into relational schema and construct basic SQL queries.
- CO3: Analyze and construct SQL queries, including nested and aggregate queries, constraints, and triggers. Evaluate the normalization process using functional dependencies to achieve higher normal forms.
- CO4: Evaluate schema refinement methods, such as multivalued dependencies and normal forms, and assess transaction management strategies, including concurrency control and recovery protocols in database systems.
- CO5: Design and implement storage solutions and indexing mechanisms, such as hash-based and tree-based indexing (B+ trees, ISAM), optimizing file organization and performance for database queries.
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| 4 | Mathematical and Statistical Foundations | 24MC1T05 | First Semester | Theory | 5 | - CO1: Understand the basic concepts of probability, random variables, and probability distributions for discrete and continuous variables.
- CO2: Apply sampling methods and estimation techniques to compute population parameters and evaluate point and interval estimates.
- CO3: Analyze and conduct hypothesis tests, including significance tests for small and large samples, and apply chi-square tests for goodness of fit.
- CO4: Evaluate algebraic structures such as groups, monoids, and homomorphisms, and apply number theory concepts like Euclidean algorithms and modular arithmetic.
- CO5: Design and analyze graphs using concepts like Eulerian and Hamiltonian circuits, graph coloring, and spanning trees, applying algorithms for practical problems.
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| 5 | Operating Systems | 24MC1T04 | First Semester | Theory | 5 | - CO1: Explain the fundamental concepts and structure of operating systems, including types and system calls.
- CO2: Apply process scheduling algorithms and analyze process management concepts such as process control blocks and inter process communication.
- CO3: Analyze synchronization mechanisms and deadlock handling strategies to ensure safe process execution.
- CO4: Evaluate memory management techniques, such as paging and segmentation, and file system implementation strategies like allocation and disk scheduling.
- CO5: Design and compare the operating system architectures of Linux and Windows, focusing on their process management, file systems, and networking features.
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| 6 | Data Structures using C Lab | 24MC1L02 | First Semester | Lab | 5 | - CO1: Apply basic C programming concepts to solve mathematical problems like
even numbers, harmonic series, Armstrong numbers, and factorials.
- CO2: Apply C programming to perform matrix operations and recursion-based tasks such
as Fibonacci sequence generation and call-by-reference operations.
- CO3: Analyze and implement file handling operations, recursive algorithms, and
searching techniques like linear and binary search using both recursive and nonrecursive approaches.
- CO4: Design and implement data structures such as stacks, queues, and linked lists using
arrays and linked list techniques in C.
- CO5: Create and implement advanced data structures such as binary search trees, AVL
trees, and hash tables, and apply sorting algorithms like quicksort, merge sort, and
bubble sort in C.
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| 7 | Database Management Systems Lab | 24MC1L01 | First Semester | Lab | 5 | - CO1: Explain the purpose, architecture, and various applications of database
systems, as well as the role of data models (ER models) and how they relate
to database design.
- CO2: Demonstrate the application of the relational model, integrity constraints, and
query relational data using relational algebra and calculus. Convert ER
diagrams into relational schema and construct basic SQL queries.
- CO3: Analyze and construct SQL queries, including nested and aggregate queries,
constraints, and triggers. Evaluate the normalization process using functional
dependencies to achieve higher normal forms.
- CO4: Evaluate schema refinement methods, such as multivalued dependencies and
normal forms, and assess transaction management strategies, including
concurrency control and recovery protocols in database systems.
- CO5: Design and implement storage solutions and indexing mechanisms, such as
hash-based and tree-based indexing (B+ trees, ISAM), optimizing file
organization and performance for database queries.
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| 8 | Operating Systems and Linux Lab | 24MC1L03 | First Semester | Lab | 5 | - CO1: Understand and use basic Unix/Linux utility commands and shell environments
like Bash, Bourne, and C shell for effective system interaction.
- CO2: Apply C programming to simulate Unix/Linux file system operations and process
control functions, including command pipes and system calls like fork (), wait (),
and exec ().
- CO3: Apply and simulate various CPU scheduling algorithms (FCFS, SJF, Priority,
Round Robin) and memory management strategies like first-fit, best-fit, and
worst-fit in operating systems.
- CO4: Analyze and simulate deadlock avoidance/prevention techniques using the
Banker's Algorithm and implement page replacement algorithms like FIFO,
LRU, and LFU
- CO5: Design and develop shell scripts for various tasks, including checking prime
numbers, calculating Fibonacci series, handling file operations, and manipulating
student records with conditions and loops.
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| 9 | ADVANCED UNIX PROGRAMMING | 24MC2TE2 | Second Semester | Theory | 5 | - CO1: Describe UNIX utilities and develop basic shell scripts for file handling and
process management.
- CO2: Handle UNIX files and directories using system calls and directory
functions, and differentiate between system calls and library functions
- CO3: Analyze UNIX process management and signal handling, including
handling zombie and orphan processes
- CO4: Implement inter-process communication techniques such as pipes and
message queues for client-server programs.
- CO5: Evaluate the use of shared memory and sockets for client-server
communication using TCP and UDP protocols.
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| 10 | ARTIFICIAL INTELLIGENCE | 24MC2T05 | Second Semester | Theory | 5 | - CO1: Describe the foundational concepts of AI, including its definition,
problems, system components, applications, and intelligent agent types.
- CO2: Apply various search and optimization algorithms to solve complex AI
problems
- CO3: Analyze knowledge representation and reasoning techniques using logic
and their application in knowledge-based agents.
- CO4: Compare agent architectures and evaluate multi-agent systems for different
AI applications.
- CO5: Design and develop expert systems using their architecture, components,
and techniques for knowledge acquisition and heuristics
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| 11 | COMPUTER NETWORK | 24MC2T01 | Second Semester | Theory | 5 | - CO1: Describe network topologies, reference models, and physical layer
components, including different media types
- CO2: Apply error detection/correction and implement basic data link protocols for
reliable communication
- CO3: Compare multiple access protocols and evaluate their effectiveness in
various networking environments.
- CO4: Analyze routing algorithms and congestion control techniques to optimize
data transmission.
- CO5: Evaluate transport layer protocols and application services for end-to-end
communication and data security.
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| 12 | NETWORK SECURITY AND CYBER SECURITY | 24MC2T02 | Second Semester | Theory | 5 | - CO1: Explain basic cryptography principles, including security goals, attacks, and
symmetric encryption techniques like DES and AES.
- CO2: Apply asymmetric encryption methods and compare cryptographic hash
functions such as SHA and SHA-3.
- CO3: Analyze digital signature schemes and evaluate security measures for email
and IP security.
- CO4: Identify and classify cybercrimes and understand the roles and motivations
of cybercriminals
- CO5: Evaluate advanced cyber threats and propose security measures to counter
them.
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| 13 | OBJECT ORIENTED PROGRAMMING USING JAVA | 24MC2T03 | Second Semester | Theory | 5 | - CO1: Explain OOP concepts and basic Java programming skills, including data
types and control statements.
- CO2: Apply inheritance, packages, and interfaces in Java to organize and
modularize cod
- CO3: Analyze and implement exception handling and multithreading in Java for
error management and concurrent tasks.
- CO4: Design event-driven programs and GUIs using AWT components and the
delegation event model.
- CO5: Evaluate and use Swing for creating advanced Java GUIs with sophisticated
components.
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| 14 | SOFTWARE ENGINEERING | 24MC2T04 | Second Semester | Theory | 5 | - CO1: Describe the history and characteristics of software engineering and
compare SDLC methodologies like Waterfall, Spiral, and Agile.
- CO2: Apply techniques to gather and analyze software requirements and create a
Software Requirements Specification (SRS).
- CO3: Analyze design strategies and evaluate software design using metrics such
as coupling and cohesion.
- CO4: Develop and execute test cases using various techniques to ensure software
quality.
- CO5: Evaluate maintenance models and reengineering techniques to manage
software evolution and upkeep
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| 15 | EMPLOYABILITY SKILLS -1$ | 24MC2L03 | Second Semester | Lab | 5 | - CO1: Demonstrate effective communication techniques and strategies for
self-analysis and maintaining a positive attitude
- CO2: Apply self-management techniques and understand various etiquette
practices for personal and professional contexts
- CO3: Develop skills in note-making letter writing and verbal
- CO4: Analyze and apply techniques for effective group discussions and
evaluate personal performance through mock discussions
- CO5: Create a professional resume and demonstrate interview skills
through mock interviews
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| 16 | NETWORKS AND SECURITY LAB | 24MC2L02 | Second Semester | Lab | 5 | - CO1: Implement data link layer framing methods like character and bit stuffing in
C.
- CO2: Develop a C program to compute CRC checksums using CRC-16 and CRCCCITT.
- CO3: Implement Dijkstra's algorithm in C or Java to find the shortest path in a
graph.
- CO4: Calculate and present routing tables using the distance vector routing
algorithm.
- CO5: Write Java programs for encryption and decryption using various algorithms
and key exchange mechanisms
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| 17 | OBJECT ORIENTED PROGRAMMING USING JAVA LAB | 24MC2L01 | Second Semester | Lab | 5 | - CO1: To understand how to design, implement, test, debug, and document programs that use basic data types
and computation, simple I/O, structures, string handling and functions.
- CO2: To understand the importance of Classes & objects along with constructors, Arrays and Vectors
- CO3: Discuss the principles of inheritance, interface and packages and demonstrate through problem
analysis assignments how they relate to the design of methods, abstract classes and interfaces and
packages
- CO4: To learn experience of designing, implementing, graphical user interfaces in Java using applet and
AWT that respond to different user events.
- CO5: To understand Java Swings for designing GUI applications based on MVC architecture.
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| 18 | Big Data Technologies | 24MC3T03 | Third Semester | Theory | 5 | - CO1: Explain the classification, characteristics, and evolution of Big Data, compare traditional BI with Big Data, and describe Big Data analytics tools and technologies.(K2)
- CO2: Apply Hadoop concepts including HDFS, YARN, and MapReduce
programming to process and manage large-scale data efficiently. (K3)
- CO3: Analyze the features, data types, and query mechanisms of MongoDB to model and manage unstructured data effectively.(K4)
- CO4: Evaluate and implement Hive and Pig for data warehousing and processing, including query design, UDFs, and data transformation techniques. (K5)
- CO5: Design Big Data applications using Apache Spark, and create solutions for text, web content, and link analytics including PageRank and graph analysis. (K6)
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| 19 | Cloud Computing | 24MC3TE1 | Third Semester | Theory | 5 | - CO1: Explain scalable computing concepts, distributed/cloud system models, and evaluate performance, security, and energy efficiency aspects. (K2)
- CO2: Apply virtualization techniques for CPU, memory, I/O devices, and resource management in virtual clusters and data centers. (K3)
- CO3: Analyze cloud service models, architectural design of compute and storage clouds, and assess cloud security and trust management strategies. (K4)
- CO4: Evaluate cloud programming paradigms and implement applications on platforms such as AWS, Azure, Hadoop, and Google File System. (K5)
- CO5: Design and develop scheduling policies and resource management strategies for cloud environments with deadlines and performance constraints. (K6)
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| 20 | Full Stack Development | 24MC3T02 | Third Semester | Theory | 5 | - CO1: Explain and apply the core concepts of JavaScript, including variables, data types, arrays, strings, functions, objects, and control structures. (K3)
- CO2: Demonstrate DOM manipulation and event handling by dynamically updating web content and building interactive front-end components. (K4)
- CO3: Develop enhanced forms with validation and implement basic React components using props, children, and composition within the MERN stack.(K5)
- CO4: Design stateful React applications with efficient component communication, and integrate REST/GraphQL APIs for full-stack interaction. (K5)
- CO5: Create and optimize full-stack web applications by implementing MongoDB CRUD operations and configuring modularization with Webpack for production-ready deployment. (K6)
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| 21 | Human Resource Management | 24MC3T04 | Third Semester | Theory | 5 | - CO1: Explain the significance, functions, ethical aspects, policies, and global challenges of HRM while aligning HR strategies with organizational strategies. (K2)
- CO2: Apply HR planning, recruitment, training, and development techniques to ensure effective workforce acquisition and retention. (K3)
- CO3: Analyze wage structures, incentive systems, and welfare measures to design equitable compensation and employee well-being mechanisms. (K4)
- CO4: Evaluate performance appraisal methods, career development practices, and compensation systems in both national and international contexts. (K5)
- CO5: Design mechanisms for managing industrial relations, collective bargaining, grievance handling, workplace safety, and stress management. (K6)
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| 22 | Machine Learning using Python | 24MC3T01 | Third Semester | Theory | 5 | - CO1: Recall and explain the fundamental concepts, basic terminology, and types of Machine Learning, while setting up Python libraries for ML applications.
- CO2: Apply supervised machine learning algorithms (k-NN, linear models, Naive Bayes, decision trees, SVM, ensembles) to solve classification and regression problems. (K3)
- CO3: Analyze unsupervised learning techniques, perform clustering and dimensionality reduction, and evaluate model performance on real-world datasets (K4)
- CO4: Evaluate and design effective feature representation, preprocessing methods, and pipeline construction for optimizing machine learning workflows. (K5)
- CO5: Create machine learning solutions for text data processing, sentiment analysis, and recommender systems using appropriate feature engineering and visualization techniques.(K6)
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| 23 | Big Data Technologies Lab | 24MC3L03 | Third Semester | Lab | 5 | - CO1: Demonstrate Hadoop installation and manage files in HDFS using
command-line utilities. (K3)
- CO2: Develop and execute MapReduce programs for data processing and analysis. (K4)
- CO3: Apply CRUD and aggregation operations in NoSQL databases using MongoDB.(K3)
- CO4: Design and execute data analysis tasks using Pig Latin scripts and Hive queries. (K5)
- CO5: Utilize Spark, CDH, and HUE tools for large-scale data analysis and
reporting. (K6)
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| 24 | Employability Skills | 24MC3L04 | Third Semester | Lab | 5 | - CO1: Apply basic numerical concepts such as numbers, ratios, percentages, and profit & loss to solve aptitude problems. (K3)
- CO2: Solve arithmetical problems related to work, time, distance, and real-life applications with accuracy.(K3)
- CO3: Analyze and apply logical and quantitative reasoning techniques such as interest, probability, and permutations to complex problems.(K3)
- CO4: Evaluate and solve problems involving mensuration, including geometry, surface areas, and volumes. (K5)
- CO5: Interpret and analyze data presented in tabular and graphical forms to draw meaningful conclusions. (K5)
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| 25 | Full Stack Development Lab | 24MC3L01 | Third Semester | Lab | 5 | - CO1: Apply JavaScript fundamentals (variables, arrays, strings, functions) for basic programming tasks.(K3)
- CO2: Demonstrate object-oriented concepts and implement interactive web pages using DOM and event handling. (K4)
- CO3: Develop functional components in React with state and hooks for dynamic UI interaction. (K5)
- CO4: Build RESTful APIs using Express with request handling and middleware.(K5)
- CO5: Create a full-stack MERN application integrating MongoDB, Express, and React for data-driven solutions. (K6)
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| 26 | Machine Learning with Python Lab | 24MC3L02 | Third Semester | Lab | 5 | - CO1: Apply concept learning algorithms (FIND-S, Candidate-Elimination) to derive hypotheses from training data. (K3)
- CO2: Analyze classification problems using decision tree and instance-based learning algorithms. (K4)
- CO3: Implement and evaluate machine learning models using artificial neural networks and Bayesian learning techniques. (K5)
- CO4: Develop probabilistic models for text/document classification and evaluate them using performance metrics.(K5)
- CO5: Create clustering and regression models to analyze and compare data patterns using unsupervised and non-parametric methods. (K6)
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| 27 | DEEP LEARNING | 24MC4TE4 | Fourth Semester | Theory | 5 | - CO1: Describe the historical development of Deep Learning and explain the
working of perceptrons, MLPs, and backpropagation.
- CO2: Apply different activation functions, optimization algorithms, and
regularization methods to design and train effective neural network models.
- CO3: Analyze convolutional neural networks and compare various deep CNN
architectures (LeNet, AlexNet, VGG) with respect to their performance and
applications.
- CO4: Evaluate the performance of different recurrent architectures such as RNNs,
LSTMs, GRUs, and Seq2Seq models for sequential data problems.
- CO5: Design and implement deep learning solutions for real-world applications in
computer vision, NLP, speech recognition, and video analytics.
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| 28 | FUNDAMENTALS OF DATASCIENCE | 24MC4TE9 | Fourth Semester | Theory | 5 | - CO1: Explain the fundamentals of Data Science and demonstrate the use of NumPy for array-based computation and data manipulation.
- CO2: Apply pandas’ data structures and functionalities for data cleaning, transformation, and statistical summarization.
- CO3: Analyze different data formats and storage mechanisms to efficiently load, process, and persist structured and unstructured data.
- CO4: Evaluate and perform advanced data wrangling techniques to integrate, restructure, and refine datasets for analysis.
- CO5: Create effective visualizations using matplotlib and pandas to interpret and communicate data-driven insights.
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