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B-TECH in Computer Science Business Systems Csbs at Koneru Lakshmaiah Education Foundation (Deemed to be University)
Guntur, Andhra Pradesh
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About the Specialization
What is Computer Science & Business Systems (CSBS) at Koneru Lakshmaiah Education Foundation (Deemed to be University) Guntur?
This Computer Science & Business Systems (CSBS) program at Koneru Lakshmaiah, Guntur, focuses on integrating core computer science principles with essential business management concepts. It is designed to create techno-business professionals equipped to address the evolving demands of Indian and global industries, bridging the gap between technical expertise and strategic business understanding. The program''''s interdisciplinary nature prepares graduates for roles requiring both analytical thinking and commercial acumen.
Who Should Apply?
This program is ideal for fresh graduates with a strong aptitude for mathematics and problem-solving, seeking entry into high-growth sectors like IT consulting, data analytics, and business intelligence in India. It also suits working professionals aiming to upskill for techno-managerial roles or career changers transitioning to technology-driven business domains who require a blend of technical and business knowledge to thrive in the competitive Indian job market.
Why Choose This Course?
Graduates of this program can expect diverse India-specific career paths, including Business Analyst, Data Scientist, IT Consultant, Software Developer, and Project Manager, within Indian MNCs and startups. Entry-level salaries typically range from INR 4-8 LPA, with experienced professionals earning upwards of INR 15-20 LPA. The curriculum aligns with certifications in project management, cloud computing, and data analytics, fostering strong growth trajectories in leading Indian companies.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Consistently practice programming concepts (C, Data Structures) on platforms like HackerRank and GeeksforGeeks. Focus on understanding algorithms and data structure implementations, not just memorizing syntax. Engage in weekly coding challenges to build a strong foundation.
Tools & Resources
HackerRank, GeeksforGeeks, LeetCode (easy problems), KLU internal coding clubs
Career Connection
Strong foundational coding skills are crucial for technical interviews and problem-solving in any software development or data science role, enhancing eligibility for entry-level positions.
Active Participation in Core Courses- (Semester 1-2)
Pay close attention to core subjects like Linear Algebra, Probability & Statistics, and Basic Electrical & Electronics. Form study groups, clarify doubts with faculty, and solve extra problems. These courses build the analytical and quantitative base essential for advanced CSBS topics.
Tools & Resources
Textbooks, NPTEL courses for supplementary learning, Peer study groups, Faculty office hours
Career Connection
A solid grasp of mathematics and scientific principles underpins effective data analysis, algorithm design, and system understanding, critical for roles in AI/ML and business analytics.
Develop Communication & Soft Skills- (Semester 1-2)
Utilize English for Communication labs to enhance public speaking, presentation, and written communication skills. Participate in debates, extempore sessions, and student club activities to build confidence and teamwork, which are highly valued in corporate settings.
Tools & Resources
KLU Language Lab, Toastmasters International (if available), Departmental student clubs, Online resources for soft skills development
Career Connection
Effective communication is vital for interacting with business stakeholders, presenting project findings, and excelling in group discussions and personal interviews during placements, especially for business-facing roles.
Intermediate Stage
Apply OOP and DBMS Skills to Real-world Problems- (Semester 3-4)
Beyond lab assignments, build small projects using Java (OOP) and SQL (DBMS). Examples include a simple inventory management system, an online quiz application, or a customer relationship management tool. Focus on database design, efficient querying, and robust object-oriented implementation.
Tools & Resources
Java IDEs (Eclipse/IntelliJ), MySQL/PostgreSQL, GitHub for version control, Online project tutorials
Career Connection
Practical application of OOP and DBMS is a core requirement for most software development, database administration, and backend engineering roles in the Indian IT industry.
Engage in Industry-relevant Internships/Workshops- (Semester 4-5)
Seek out short-term internships or participate in industry-sponsored workshops in areas like Web Technologies, AI, or IoT. These provide crucial industry exposure and help in understanding the application of academic concepts in a corporate setting. Network with professionals.
Tools & Resources
KLU Career Development Center, LinkedIn, Company career portals, Industry events/tech conferences
Career Connection
Internships are vital for gaining practical experience, building a professional network, and often lead to pre-placement offers (PPOs) in Indian companies, significantly boosting placement prospects.
Specialize through Electives and Certifications- (Semester 5)
Choose professional electives strategically based on career interests (e.g., AI, Cyber Security, Cloud). Supplement with relevant online certifications from platforms like Coursera, Udemy, or NPTEL in areas like Machine Learning, Cloud Computing (AWS/Azure), or Data Analytics.
Tools & Resources
Coursera, Udemy, NPTEL, edX, Industry certification bodies (e.g., AWS Certified Cloud Practitioner)
Career Connection
Specialization through electives and certifications makes graduates more competitive for niche roles in high-demand fields like AI/ML engineering, cloud architecture, or cybersecurity, leading to better opportunities and higher salaries.
Advanced Stage
Undertake a Comprehensive Major Project- (Semester 7-8)
For the Major Project (Part A & B), identify a complex business or technical problem and develop a robust solution. Focus on teamwork, project management methodologies (Agile), rigorous testing, and clear documentation. This simulates real-world project delivery.
Tools & Resources
Project management tools (Jira, Trello), Collaboration platforms (Slack), Advanced programming languages/frameworks, GitHub
Career Connection
A strong major project showcases practical skills, problem-solving abilities, and domain expertise to potential employers, making it a key differentiator in placement interviews and portfolios.
Intensive Placement Preparation & Networking- (Semester 6-8)
Actively participate in KLU''''s placement drives, mock interviews, and resume building workshops. Network extensively with alumni and industry professionals through LinkedIn and career fairs. Practice aptitude, reasoning, and technical questions rigorously.
Tools & Resources
KLU Placement Cell, LinkedIn, Online aptitude test platforms, Company-specific interview prep materials
Career Connection
Dedicated placement preparation directly translates into successful job offers from top-tier companies. Networking can open doors to opportunities not publicly advertised, enhancing career prospects significantly.
Explore Entrepreneurship and Innovation- (Semester 8)
Leverage courses like Entrepreneurship to develop a viable business idea. Participate in college startup incubators or pitch competitions. Focus on understanding market needs, building a minimum viable product, and developing a solid business plan.
Tools & Resources
KLU Incubation Center, Startup mentorship programs, Business plan templates, Pitch deck resources
Career Connection
This path is for students aspiring to launch their ventures, fostering an innovative mindset valuable even in corporate roles. It demonstrates initiative, strategic thinking, and leadership, highly valued by employers.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 examination with Physics and Mathematics as compulsory subjects along with one of the Chemistry/Biotechnology/Biology/Technical Vocational subject/Computer Science/Information Technology/Informatics Practices/Agriculture/Engineering Graphics/Business Studies. Obtained at least 45% marks (40% marks in case of candidates belonging to reserved category) in the above subjects taken together.
Duration: 4 years / 8 semesters
Credits: 168 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BS1101 | Linear Algebra and Differential Equations | Core | 4 | Matrices and System of Linear Equations, Eigenvalues and Eigenvectors, First Order Differential Equations, Higher Order Linear Differential Equations, Laplace Transforms |
| 23BS1102 | Physics of Materials | Core | 3 | Quantum Mechanics and Free Electron Theory, Crystal Structure and Semiconductor Physics, Magnetic and Dielectric Materials, Lasers and Fiber Optics, Nanomaterials |
| 23BS1201 | Physics of Materials Lab | Lab | 1 | Error Analysis and Experimentation, Optical Phenomena Experiments, Electrical Conductivity Measurements, Semiconductor Device Characteristics, Magnetic Field Measurements |
| 23CS1001 | Programming for Problem Solving | Core | 3 | Introduction to Programming and C Language, Control Structures and Loops, Functions and Pointers, Arrays and Strings, Structures, Unions and File Handling |
| 23CS1002 | Programming for Problem Solving Lab | Lab | 1 | Basic C Programs (Arithmetic, Conditional), Control Flow Implementations (Loops, Switch), Function and Pointer Usage, Array and String Manipulations, File Operations and Structures |
| 23EN1101 | English for Communication | Core | 3 | Grammar and Vocabulary Building, Paragraph Writing and Essay Writing, Reading Comprehension Strategies, Technical Writing Skills, Oral Communication and Presentations |
| 23EN1102 | English for Communication Lab | Lab | 1 | Phonetics and Pronunciation Practice, Listening and Speaking Activities, Role-playing and Group Discussions, Presentation Skills Development, Interview Skills and Body Language |
| 23ES1001 | Engineering Graphics | Core | 2 | Introduction to Engineering Drawing, Orthographic Projections, Projections of Solids, Sections of Solids and Development of Surfaces, Isometric Projections |
| 23GE1001 | Professional Ethics & Human Values | Core | 2 | Values and Ethics in Profession, Engineering Ethics, Safety, Responsibilities and Rights, Global Issues in Ethics, Code of Conduct and Corporate Governance |
| 23ME1001 | Manufacturing Practices | Core | 2 | Workshop Safety and Tools, Carpentry Shop Operations, Fitting Shop Operations, Welding Shop Processes, Foundry and Forging Practices |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BS2101 | Probability and Statistics | Core | 4 | Basic Probability and Random Variables, Probability Distributions (Discrete & Continuous), Sampling Distributions and Estimation, Hypothesis Testing (Large & Small Samples), Correlation and Regression |
| 23BS2102 | Chemistry for Engineers | Core | 3 | Electrochemistry and Batteries, Corrosion and its Control, Water Technology and Treatment, Polymer Chemistry and Engineering Materials, Spectroscopy and Nanomaterials |
| 23BS2201 | Chemistry for Engineers Lab | Lab | 1 | Volumetric Analysis and Titrations, pH Metry and Potentiometry, Synthesis of Polymers, Analysis of Water Samples, Spectrophotometric Experiments |
| 23CS2001 | Data Structures | Core | 3 | Introduction to Data Structures and Arrays, Linked Lists (Singly, Doubly, Circular), Stacks and Queues, Trees (Binary, BST, AVL), Graphs and Hashing |
| 23CS2002 | Data Structures Lab | Lab | 1 | Implementation of Arrays and Linked Lists, Stack and Queue Operations, Tree Traversal Algorithms, Graph Algorithms (BFS, DFS), Sorting and Searching Techniques |
| 23EC2001 | Basic Electrical and Electronics Engineering | Core | 3 | DC Circuits and Network Theorems, AC Circuits and Single Phase Systems, Semiconductor Diodes and Applications, Bipolar Junction Transistors (BJTs), Operational Amplifiers |
| 23EC2002 | Basic Electrical and Electronics Engineering Lab | Lab | 1 | Verification of Circuit Laws, Diode Characteristics and Rectifiers, Transistor Amplifier Circuits, Operational Amplifier Applications, Basic Electronic Components Identification |
| 23ME2001 | Engineering Mechanics | Core | 3 | Forces and Equilibrium, Friction and its Applications, Centroids and Moment of Inertia, Kinematics of Particles, Kinetics of Particles |
| 23EM2001 | Environmental Science | Core | 2 | Ecosystems and Biodiversity, Environmental Pollution (Air, Water, Soil), Natural Resources and Conservation, Climate Change and Sustainable Development, Environmental Policies and Ethics |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BS3101 | Discrete Mathematics | Core | 4 | Set Theory and Logic, Relations and Functions, Combinatorics and Probability, Graph Theory and Trees, Algebraic Structures and Lattices |
| 23CS3001 | Object-Oriented Programming with Java | Core | 3 | Introduction to OOP and Java Basics, Classes, Objects, Methods, and Constructors, Inheritance, Polymorphism, and Abstraction, Packages, Interfaces, and Exception Handling, Multithreading and Collections |
| 23CS3002 | Object-Oriented Programming Lab | Lab | 1 | Java Basics and Class Implementation, Inheritance and Polymorphism Examples, Exception Handling and Multithreading, GUI Programming (AWT/Swing), File I/O and JDBC Connectivity |
| 23CS3003 | Database Management Systems | Core | 3 | Introduction to DBMS and Data Models, Relational Model and SQL Fundamentals, ER Diagrams and Relational Algebra, Normalization and Dependency Theory, Transaction Management and Concurrency Control |
| 23CS3004 | Database Management Systems Lab | Lab | 1 | SQL DDL and DML Commands, Advanced SQL Queries and Joins, PL/SQL Programming, Database Design and Normalization, Introduction to NoSQL Databases |
| 23CS3005 | Computer Architecture and Organization | Core | 3 | Basic Computer Organization, CPU Design and Instruction Sets, Memory Organization and Hierarchy, I/O Organization and Interfacing, Pipelining and Parallel Processing |
| 23CS3006 | Operating Systems | Core | 3 | Introduction to Operating Systems, Process Management and CPU Scheduling, Process Synchronization and Deadlocks, Memory Management Techniques, File Systems and I/O Management |
| 23CS3007 | Operating Systems Lab | Lab | 1 | Linux Commands and Shell Scripting, Process Creation and Management, CPU Scheduling Algorithms, Deadlock Detection and Prevention, Memory Allocation Algorithms |
| 23GE3001 | Constitution of India | Core | 2 | Historical Background and Preamble, Fundamental Rights and Duties, Directive Principles of State Policy, Union and State Governments, Indian Judiciary and Emergency Provisions |
| 23MC3001 | NSS / NCC / Yoga | Mandatory | 2 | Community Service and Social Responsibility, Discipline and Leadership Training, Physical Fitness and Well-being, Yoga Practices and Mindfulness, Environmental Awareness Campaigns |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BS4101 | Optimization Techniques | Core | 4 | Linear Programming and Simplex Method, Transportation and Assignment Problems, Integer Programming and Goal Programming, Dynamic Programming, Queuing Theory and Decision Analysis |
| 23CS4001 | Design and Analysis of Algorithms | Core | 3 | Algorithm Analysis and Asymptotic Notations, Divide and Conquer Techniques, Greedy Algorithms and Dynamic Programming, Graph Algorithms (BFS, DFS, Spanning Trees), NP-Hard and NP-Complete Problems |
| 23CS4002 | Design and Analysis of Algorithms Lab | Lab | 1 | Implementation of Sorting and Searching, Graph Traversal and Shortest Path Algorithms, Dynamic Programming Solutions, Greedy Algorithm Implementations, Time and Space Complexity Analysis |
| 23CS4003 | Software Engineering | Core | 3 | Software Development Life Cycle Models, Requirements Engineering and Analysis, Software Design Principles and Patterns, Software Testing Techniques and Strategies, Software Project Management and Maintenance |
| 23CS4004 | Formal Languages and Automata Theory | Core | 3 | Finite Automata and Regular Expressions, Context-Free Grammars and Pushdown Automata, Chomsky Hierarchy of Languages, Turing Machines and Computability, Undecidability |
| 23CS4005 | Computer Networks | Core | 3 | Introduction to Data Communication and Networks, OSI and TCP/IP Models, Data Link Layer Protocols, Network Layer Protocols (IP, Routing), Transport Layer (TCP, UDP) and Application Layer Protocols |
| 23CS4006 | Computer Networks Lab | Lab | 1 | Network Configuration and Troubleshooting, Socket Programming (TCP/UDP), Packet Analysis using Wireshark, Routing Protocol Configuration, Network Security Tools |
| 23CS4007 | Web Technologies | Core | 3 | HTML5 and CSS3 Fundamentals, JavaScript for Client-Side Scripting, Web Servers and Web Hosting, Introduction to XML and JSON, AJAX and Introduction to Frameworks |
| 23CS4008 | Web Technologies Lab | Lab | 1 | Creating Responsive Web Pages with HTML/CSS, Dynamic Web Pages with JavaScript, Frontend Frameworks (e.g., Bootstrap), Backend Scripting (e.g., PHP/Node.js), Database Integration for Web Applications |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23CS5001 | Artificial Intelligence | Core | 3 | Introduction to AI and Intelligent Agents, Problem Solving through Search (Heuristic/Uninformed), Knowledge Representation and Reasoning, Machine Learning Basics, Natural Language Processing Fundamentals |
| 23CS5002 | Artificial Intelligence Lab | Lab | 1 | AI Programming (e.g., Prolog/Python), Implementation of Search Algorithms, Knowledge Representation Systems, Rule-Based Systems and Expert Systems, Basic NLP Tasks |
| 23CS5003 | Compiler Design | Core | 3 | Introduction to Compilers and Lexical Analysis, Syntax Analysis (Parsing Techniques), Semantic Analysis and Intermediate Code Generation, Run-Time Environments, Code Optimization and Code Generation |
| 23CS5004 | Cryptography and Network Security | Core | 3 | Security Concepts and Attack Types, Symmetric Key Cryptography (DES, AES), Asymmetric Key Cryptography (RSA, ECC), Hash Functions and Digital Signatures, Network Security (Firewalls, IDS, VPN) |
| 23CS5005 | Cryptography and Network Security Lab | Lab | 1 | Implementation of Classical Ciphers, Symmetric and Asymmetric Key Encryption, Digital Signature Schemes, Network Scanning and Vulnerability Assessment, Firewall Rules Configuration |
| 23CS5006 | Internet of Things | Core | 3 | Introduction to IoT and its Architecture, IoT Devices and Sensors, IoT Communication Protocols (MQTT, CoAP), Cloud Platforms for IoT, IoT Security and Applications |
| 23CS5007 | Internet of Things Lab | Lab | 1 | Interfacing Sensors and Actuators, Data Acquisition from IoT Devices, IoT Platform Integration (e.g., Arduino/ESP32), Cloud Connectivity for IoT Data, Building Simple IoT Applications |
| 23BM5001 | Business Economics | Core | 3 | Introduction to Business Economics, Demand and Supply Analysis, Market Structures and Pricing Strategies, Macroeconomic Concepts (GDP, Inflation), Business Cycles and Economic Policies |
| 23CS5098 | Minor Project | Project | 4 | Project Planning and Requirement Analysis, System Design and Implementation, Testing and Debugging, Documentation and Report Writing, Presentation and Viva-Voce |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BM6001 | Fundamentals of Management | Core | 3 | Introduction to Management and Organizations, Planning and Decision Making, Organizing and Staffing, Directing and Leading, Controlling and Ethics in Management |
| 23CS6001 | Machine Learning | Core | 3 | Introduction to Machine Learning, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering, PCA), Deep Learning Fundamentals, Model Evaluation and Feature Engineering |
| 23CS6002 | Machine Learning Lab | Lab | 1 | Python for Machine Learning (Scikit-learn), Implementing Regression and Classification Models, Clustering Algorithms (K-Means, Hierarchical), Introduction to Deep Learning Frameworks (TensorFlow/Keras), Data Preprocessing and Visualization |
| 23CS6003 | Cloud Computing | Core | 3 | Introduction to Cloud Computing, Cloud Service Models (IaaS, PaaS, SaaS), Cloud Deployment Models, Virtualization Technologies, Cloud Security and Management |
| 23CS6004 | Cloud Computing Lab | Lab | 1 | Working with Cloud Providers (AWS/Azure/GCP), Virtual Machine Management, Cloud Storage Services, Serverless Computing (Lambda/Functions), Networking in Cloud Environments |
| 23CS6005 | Big Data Analytics | Core | 3 | Introduction to Big Data and its Challenges, Hadoop Ecosystem (HDFS, MapReduce), Apache Spark for Data Processing, Data Warehousing and Data Lake Concepts, Big Data Visualization and Applications |
| 23CS6006 | Big Data Analytics Lab | Lab | 1 | Hadoop Command Line Interface, MapReduce Programming, Spark RDD and DataFrame Operations, Data Ingestion and Processing, Distributed Data Processing Tasks |
| 23CS6099 | Internship / Industrial Training | Core | 7 | Industry Exposure and Professional Practices, Application of Academic Knowledge to Real-world Problems, Skill Development and Project Implementation, Report Writing and Presentation, Professional Networking |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23HS7001 | Intellectual Property Rights | Core | 2 | Introduction to IPR and its Types, Patents and Patent Filing Process, Copyrights and Related Rights, Trademarks and Geographical Indications, IPR in the Digital Age and Indian Context |
| 23OE | Open Elective – I | Elective | 3 | To be chosen from a list of open electives provided by the institution. Key topics depend on the chosen elective. |
| 23PE | Professional Elective – I | Elective | 3 | To be chosen from a list of professional electives provided by the institution for CSBS specialization. Key topics depend on the chosen elective. |
| 23PE | Professional Elective – II | Elective | 3 | To be chosen from a list of professional electives provided by the institution for CSBS specialization. Key topics depend on the chosen elective. |
| 23CS7001 | Agile Software Development | Core | 3 | Introduction to Agile Manifesto and Principles, Scrum Framework and Roles, Kanban and Lean Software Development, Extreme Programming (XP) Practices, DevOps and Continuous Integration/Delivery |
| 23CS7099 | Major Project – Part A | Project | 6 | Project Proposal and Problem Identification, Literature Survey and State-of-Art Analysis, System Design and Architecture, Methodology and Implementation Plan, Initial Development and Progress Reporting |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23HS8001 | Entrepreneurship | Core | 2 | Introduction to Entrepreneurship and Startup Ecosystem, Idea Generation and Opportunity Analysis, Business Plan Development, Startup Funding and Marketing Strategies, Legal and Ethical Aspects of Entrepreneurship |
| 23OE | Open Elective – II | Elective | 3 | To be chosen from a list of open electives provided by the institution. Key topics depend on the chosen elective. |
| 23PE | Professional Elective – III | Elective | 3 | To be chosen from a list of professional electives provided by the institution for CSBS specialization. Key topics depend on the chosen elective. |
| 23PE | Professional Elective – IV | Elective | 3 | To be chosen from a list of professional electives provided by the institution for CSBS specialization. Key topics depend on the chosen elective. |
| 23CS8099 | Major Project – Part B | Project | 5 | Advanced Implementation and Module Integration, Rigorous Testing and Performance Evaluation, Final Documentation and Report Preparation, Project Presentation and Demonstration, Viva-Voce and Future Scope |
