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B-TECH-COMPUTER-SCIENCE-ENGINEERING-HINDI in General at Ajay Kumar Garg Engineering College
Ghaziabad, Uttar Pradesh
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About the Specialization
What is General at Ajay Kumar Garg Engineering College Ghaziabad?
This B.Tech Computer Science & Engineering program at Ajay Kumar Garg Engineering College focuses on providing a robust foundation in core computer science principles, including algorithms, data structures, programming languages, operating systems, database management, and networking. It incorporates advanced areas like Artificial Intelligence, Machine Learning, Data Science, and Cloud Computing, aligning with India''''s rapidly expanding digital economy and tech innovation drive. The program aims to produce skilled professionals ready for the evolving IT landscape.
Who Should Apply?
This program is ideal for high school graduates with a strong aptitude in Physics, Chemistry, and Mathematics who are passionate about technology and problem-solving. It caters to aspiring software developers, data scientists, cybersecurity experts, and AI/ML engineers. Students seeking a comprehensive engineering education with practical application and exposure to cutting-edge technologies relevant to the Indian tech industry will find this program highly suitable.
Why Choose This Course?
Graduates of this program can expect diverse career paths such as Software Development Engineer, Data Analyst, Cloud Engineer, AI/ML Specialist, and Network Administrator in leading Indian and multinational companies. Entry-level salaries typically range from INR 4-8 lakhs per annum, with significant growth potential up to INR 15-25+ lakhs for experienced professionals. The curriculum is designed to align with industry certifications and fosters the skills needed for high-growth roles in India''''s booming IT and digital sectors.
Student Success Practices
Foundation Stage
Master Core Programming & Logic- (Semester 1-2)
Dedicate significant time to understanding fundamental programming concepts (C, Python) and data structures. Practice daily on online coding platforms to build strong logical reasoning and problem-solving skills.
Tools & Resources
HackerRank, GeeksforGeeks, CodeChef, NPTEL Introduction to Programming
Career Connection
A strong base in programming and logic is crucial for cracking technical interviews and excelling in initial software development roles.
Build Strong Academic Fundamentals- (Semester 1-2)
Focus on excelling in Engineering Mathematics and Physics. These subjects provide the analytical and logical foundation necessary for advanced computer science topics like algorithms and system design.
Tools & Resources
NCERT textbooks (revisit basics), Khan Academy, MIT OpenCourseware, Peer study groups
Career Connection
Sound mathematical and scientific foundations are essential for understanding complex algorithms, machine learning, and quantitative roles in tech companies.
Participate in Early Tech Engagement- (Semester 1-2)
Join college technical clubs (e.g., Computer Society of India student chapter, coding clubs). Participate in intra-college hackathons and workshops to gain early exposure to technology trends and teamwork.
Tools & Resources
College tech clubs, Local hackathon events, Introductory tech workshops
Career Connection
Early engagement builds a network, exposes you to practical applications, and makes your profile stand out for internships.
Intermediate Stage
Engage in Hands-on Project Development- (Semester 3-5)
Apply theoretical knowledge by building mini-projects in areas like web development, app development, or basic AI. Maintain a GitHub portfolio to showcase your practical skills.
Tools & Resources
GitHub, VS Code, Django/Flask for web development, Kaggle (for data projects)
Career Connection
Practical projects demonstrate your ability to apply concepts, a key requirement for internships and entry-level positions in product development.
Seek Industry-Relevant Skill Specialization- (Semester 3-5)
Identify emerging areas like Data Science, Machine Learning, or Cybersecurity and pursue online courses or certifications. This adds specialized value beyond the core curriculum.
Tools & Resources
Coursera, Udemy, edX, NPTEL advanced courses, Google/AWS certifications
Career Connection
Specialized skills are highly sought after in the Indian job market, opening doors to niche roles and better salary packages.
Network and Seek Mentorship- (Semester 3-5)
Connect with alumni, industry professionals, and faculty mentors. Attend webinars, seminars, and industry events. Mentorship can provide invaluable guidance for career planning.
Tools & Resources
LinkedIn, College alumni network, Industry meetups and conferences
Career Connection
Networking often leads to internship opportunities, job referrals, and insights into industry trends, crucial for career advancement.
Advanced Stage
Intensive Placement Preparation- (Semester 6-8)
Focus rigorously on interview preparation covering Data Structures & Algorithms, System Design, and Behavioral aspects. Practice mock interviews and aptitude tests regularly.
Tools & Resources
LeetCode (medium/hard), GeeksforGeeks Interview Prep, Glassdoor for company-specific questions, Mock interview platforms
Career Connection
Systematic preparation is key to securing placements in top-tier IT companies and startups, which have competitive hiring processes.
Undertake Impactful Capstone Projects- (Semester 6-8)
Work on a significant final year project, ideally addressing a real-world problem or involving research. Collaborate with peers or faculty, focusing on innovation and practical utility.
Tools & Resources
Research papers, Industry problem statements, Advanced frameworks (e.g., TensorFlow, PyTorch, React)
Career Connection
A strong capstone project demonstrates your ability to conceive, design, and execute a complex solution, making you highly valuable to employers.
Cultivate Professional Communication & Ethics- (Semester 6-8)
Develop strong technical writing, presentation, and interpersonal communication skills. Understand ethical considerations in technology development and deployment.
Tools & Resources
Technical writing guides, Toastmasters (if available), Professional ethics workshops
Career Connection
Effective communication and ethical conduct are vital for leadership roles, team collaboration, and navigating the professional landscape responsibly.
Program Structure and Curriculum
Eligibility:
- 10+2 (Intermediate) with Physics, Chemistry, and Mathematics (PCM) as compulsory subjects, with a minimum of 45% aggregate marks (40% for SC/ST candidates) and a valid JEE Main score, as per AKTU and UP Government norms.
Duration: 8 semesters / 4 years
Credits: 158 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| KAS101T | Engineering Physics | Core | 4 | Wave Optics, Quantum Mechanics, Fiber Optics & Laser, Electrodynamics & Magnetic Properties, Superconductivity & Nanomaterials |
| KAS103T | Engineering Mathematics-I | Core | 4 | Matrices, Differential Calculus-I, Differential Calculus-II, Multivariable Calculus, Vector Calculus |
| KCS101T | Programming for Problem Solving | Core | 3 | Introduction to Programming & C, Control Flow Statements, Arrays and Strings, Functions, Pointers, Structures, Unions, Files |
| KAS104T | Basic Electrical Engineering | Core | 4 | DC Circuits & Network Theorems, AC Fundamentals, Single Phase & Three Phase AC Circuits, Magnetic Circuits & Transformers, Electrical Machines |
| KAS151P | Engineering Physics Lab | Lab | 1 | Optical Instruments, Semiconductor Devices, Magnetic Field Measurement, Spectroscopy, Wave Characteristics |
| KCS151P | Programming for Problem Solving Lab | Lab | 1 | C Programming Fundamentals, Conditional Statements & Loops, Arrays and Functions, Pointers & Structures, File Handling |
| KAS154P | Basic Electrical Engineering Lab | Lab | 1 | Circuit Laws Verification, AC Circuit Analysis, Transformer Characteristics, DC Machine Testing, Power Measurement |
| KWS151P | Workshop Practice / Computer Aided Design & Drafting Lab | Lab | 1 | Fitting Shop, Carpentry Shop, Welding Shop, Sheet Metal Shop, Drafting Software |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| KAS202T | Engineering Chemistry | Core | 4 | Water Analysis & Treatment, Fuels & Combustion, Corrosion & its Control, Polymers & Composites, Instrumental Methods of Analysis |
| KAS203T | Engineering Mathematics-II | Core | 4 | Ordinary Differential Equations, Laplace Transforms, Fourier Series & Partial Differential Equations, Complex Numbers, Complex Integration |
| KCS201T | Data Structure | Core | 3 | Introduction to Data Structures, Arrays and Linked Lists, Stacks and Queues, Trees and Graphs, Sorting and Searching |
| KEE201T | Basic Electronics Engineering | Core | 4 | Semiconductor Diodes & Applications, BJT & FET, Operational Amplifiers, Digital Electronics, Transducers & Communication Systems |
| KAS205T | Engineering Graphics & Design | Core | 3 | Introduction to Engineering Graphics, Orthographic Projections, Isometric Projections, Sectional Views, AutoCAD Basics |
| KAS252P | Engineering Chemistry Lab | Lab | 1 | Water Hardness Determination, Titration Techniques, Viscosity Measurement, Fuel Analysis, Spectrophotometry |
| KCS251P | Data Structure Lab | Lab | 1 | Array & Linked List Operations, Stack & Queue Implementations, Tree & Graph Traversals, Sorting Algorithms, Searching Algorithms |
| KEE251P | Basic Electronics Engineering Lab | Lab | 1 | Diode Characteristics, Transistor Amplifier Design, OP-AMP Applications, Logic Gates & Digital Circuits, Oscillators |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| KCS301 | Discrete Structures & Theory of Logic | Core | 4 | Set Theory & Logic, Relations, Functions & Partial Orders, Algebraic Structures, Graph Theory, Combinatorics & Recurrence Relations |
| KCS302 | Computer Organization & Architecture | Core | 4 | Computer Basics & CPU, Memory Organization, I/O Organization, Control Unit Design, Pipelining & Parallel Processing |
| KCS303 | Object Oriented Programming | Core | 3 | OOP Concepts (Encapsulation, Inheritance), Polymorphism & Abstraction, Constructors & Destructors, Exception Handling & Templates, File I/O & STL |
| KCS304 | Operating Systems | Core | 4 | Introduction to OS, Process Management, CPU Scheduling, Memory Management, File Systems & I/O Systems |
| KCS351 | Object Oriented Programming Lab | Lab | 1 | Class & Object Implementation, Inheritance & Polymorphism, Operator Overloading, Exception Handling, File Handling |
| KCS352 | Operating Systems Lab | Lab | 1 | Shell Scripting, Process & Thread Management, CPU Scheduling Algorithms, Deadlock Avoidance, Memory Management Algorithms |
| KCS353 | Python Programming Lab | Lab | 1 | Python Basics & Data Types, Control Flow & Functions, Lists, Tuples, Dictionaries, Object-Oriented Programming in Python, File Handling & Modules |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| KCS401 | Theory of Automata and Formal Languages | Core | 4 | Finite Automata, Regular Expressions & Languages, Context-Free Grammars, Pushdown Automata, Turing Machines & Computability |
| KCS402 | Design and Analysis of Algorithms | Core | 4 | Algorithm Analysis, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms |
| KCS403 | Database Management Systems | Core | 3 | Introduction to DBMS, Relational Model & SQL, Database Design (ER, Normalization), Transaction Management, Concurrency Control & Recovery |
| KCS404 | Computer Networks | Core | 4 | Network Models (OSI, TCP/IP), Physical Layer & Data Link Layer, Network Layer, Transport Layer, Application Layer |
| KCS451 | Database Management Systems Lab | Lab | 1 | SQL Queries (DDL, DML, DCL), Stored Procedures & Functions, Triggers & Views, Database Connectivity, Transaction Management |
| KCS452 | Computer Networks Lab | Lab | 1 | Network Commands & Tools, Socket Programming, Routing Protocols Implementation, Network Configuration, Packet Analysis |
| KCS453 | Web Technology Lab | Lab | 1 | HTML, CSS, JavaScript, DOM Manipulation, AJAX & JSON, Server-Side Scripting (e.g., PHP/Node.js), Database Integration with Web Applications |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| KCS501 | Artificial Intelligence | Core | 4 | Introduction to AI, Problem Solving by Searching, Knowledge Representation & Reasoning, Machine Learning Basics, Natural Language Processing |
| KCS502 | Compiler Design | Core | 3 | Compiler Phases, Lexical Analysis, Syntax Analysis, Intermediate Code Generation, Code Optimization & Generation |
| KCS503 | Software Engineering | Core | 3 | Software Development Life Cycle, Software Requirements Engineering, Software Design, Software Testing, Software Project Management |
| KOE0XX | Open Elective - I | Elective | 3 | General topics from other engineering branches or interdisciplinary fields. |
| KCSXXX | Departmental Elective - I | Elective | 3 | Advanced topics in Computer Science chosen from a list provided by the department. |
| KCS551 | Artificial Intelligence Lab | Lab | 1 | Search Algorithms Implementation, Knowledge Representation, Logic Programming (Prolog), Fuzzy Logic Concepts, Mini AI Projects |
| KCS552 | Software Engineering Lab | Lab | 1 | Requirement Elicitation & Analysis, UML Diagrams, Test Case Generation, Version Control Systems, Software Project Planning |
| KCS553 | Mini Project / Major Project Part-I | Project | 2 | Problem Identification, Literature Survey, Design & Implementation, Testing & Documentation, Project Presentation |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| KCS601 | Machine Learning | Core | 4 | Introduction to ML, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Deep Learning Basics, Model Evaluation & Tuning |
| KCS602 | Computer Graphics | Core | 3 | Graphics Primitives, 2D & 3D Transformations, Clipping & Viewing, Illumination Models & Shading, Visible Surface Detection |
| KCS603 | Cloud Computing | Core | 3 | Cloud Computing Concepts, Service Models (IaaS, PaaS, SaaS), Deployment Models (Public, Private, Hybrid), Virtualization, Cloud Security & Data Management |
| KOE0XX | Open Elective - II | Elective | 3 | General topics from other engineering branches or interdisciplinary fields. |
| KCSXXX | Departmental Elective - II | Elective | 3 | Advanced topics in Computer Science chosen from a list provided by the department. |
| KCS651 | Machine Learning Lab | Lab | 1 | Data Preprocessing, Regression & Classification Algorithms, Clustering Algorithms, Neural Network Implementation, Model Evaluation Metrics |
| KCS652 | Computer Graphics Lab | Lab | 1 | Drawing Primitives, 2D & 3D Transformations, Clipping Algorithms, Shading & Lighting, Interactive Graphics |
| KCS653 | Industrial Training / Internship | Practical | 2 | Industry Work Experience, Project Implementation, Professional Skill Development, Report Writing, Presentation |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| KCS701 | Data Science | Core | 4 | Introduction to Data Science, Statistical Methods for Data Science, Data Preprocessing & Exploration, Predictive Modeling, Big Data Technologies |
| KCS702 | Cryptography & Network Security | Core | 3 | Security Attacks & Mechanisms, Symmetric & Asymmetric Ciphers, Hash Functions & Digital Signatures, Network Security Applications, Firewalls & VPNs |
| KOE0XX | Open Elective - III | Elective | 3 | General topics from other engineering branches or interdisciplinary fields. |
| KCSXXX | Departmental Elective - III | Elective | 3 | Advanced topics in Computer Science chosen from a list provided by the department. |
| KCSXXX | Departmental Elective - IV | Elective | 3 | Advanced topics in Computer Science chosen from a list provided by the department. |
| KCS751 | Data Science Lab | Lab | 1 | Data Cleaning & Transformation, Exploratory Data Analysis, Statistical Modeling, Machine Learning Algorithms in Python/R, Data Visualization |
| KCS752 | Project (Part-I) / Industrial Project | Project | 4 | Problem Definition & Scope, System Design & Architecture, Module Development, Interim Report & Presentation, Team Collaboration |
| KCS753 | Seminar | Practical | 1 | Research on Emerging Technologies, Technical Presentation Skills, Literature Review, Question & Answer Sessions, Report Generation |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| KCS801 | Internet of Things | Core | 3 | IoT Architecture & Protocols, Sensors & Actuators, IoT Communication Technologies, IoT Platforms & Cloud Integration, IoT Security & Applications |
| KCSXXX | Departmental Elective - V | Elective | 3 | Advanced topics in Computer Science chosen from a list provided by the department. |
| KCSXXX | Departmental Elective - VI | Elective | 3 | Advanced topics in Computer Science chosen from a list provided by the department. |
| KOE0XX | Open Elective - IV | Elective | 3 | General topics from other engineering branches or interdisciplinary fields. |
| KCS851 | Major Project | Project | 6 | Comprehensive System Development, Advanced Technology Application, Detailed Project Report, Live Demo & Presentation, Innovation & Research Contribution |
