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B-TECH in Computer Science And Engineering at National Institute of Technology Patna
Patna, Bihar
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About the Specialization
What is Computer Science and Engineering at National Institute of Technology Patna Patna?
This Computer Science and Engineering program at National Institute of Technology Patna focuses on equipping students with a robust foundation in computing principles and their applications. It is designed to meet the growing demand for skilled professionals in India''''s rapidly expanding technology sector, covering core areas from algorithms to artificial intelligence, with an emphasis on practical problem-solving and innovation.
Who Should Apply?
This program is ideal for high school graduates with strong analytical and mathematical aptitudes seeking entry into the diverse field of technology. It also caters to students passionate about software development, data science, cybersecurity, and AI, aiming for impactful careers in India''''s leading IT companies and startups, or pursuing higher studies in advanced computing.
Why Choose This Course?
Graduates of this program can expect to secure roles as software engineers, data scientists, AI/ML engineers, cybersecurity analysts, and full-stack developers within India''''s tech giants and burgeoning startups. Entry-level salaries typically range from INR 6-12 LPA, with significant growth trajectories. The curriculum also aligns with industry certifications, enhancing professional recognition and global career prospects.
Student Success Practices
Foundation Stage
Master Programming Fundamentals with Online Platforms- (Semester 1-2)
Consistently practice problem-solving on platforms like HackerRank, LeetCode (easy level), and GeeksforGeeks to solidify C/C++ programming skills. Focus on data types, control structures, and basic algorithms to build a strong coding base.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, NPTEL courses on Programming
Career Connection
Strong coding fundamentals are crucial for technical interviews and competitive programming, opening doors to top IT firms in India.
Develop Strong Mathematical & Logical Aptitude- (Semester 1-2)
Pay close attention to Mathematics I & II, Discrete Mathematical Structures, and Engineering Physics. Actively participate in logical reasoning puzzles and math clubs. These form the bedrock for advanced Computer Science topics and problem-solving.
Tools & Resources
NCERT Mathematics, online puzzle sites, peer study groups, NPTEL for advanced topics
Career Connection
Essential for algorithm design, data science, machine learning, and analytical roles in product-based companies and research.
Engage in Departmental Orientation & Peer Learning- (Semester 1-2)
Actively participate in departmental orientation programs, technical clubs (e.g., programming clubs, AI clubs), and form study groups with peers. Seek guidance from seniors for course selection and early project ideas to integrate into the academic environment.
Tools & Resources
College technical clubs, departmental mentors, senior students
Career Connection
Builds a valuable network, provides insights into departmental culture, and fosters collaborative problem-solving skills vital for team projects and future career growth.
Intermediate Stage
Build a Strong Data Structures & Algorithms Foundation- (Semester 3-4)
Dedicate significant time to mastering Data Structures and Algorithms (DSA). Practice implementing various data structures and algorithms, and solve problems on competitive programming platforms like InterviewBit or Codeforces consistently.
Tools & Resources
LeetCode (medium/hard), GeeksforGeeks, InterviewBit, Codeforces, C++ or Java for implementation
Career Connection
DSA is the most critical skill for cracking technical interviews at product-based companies and tech startups in India, and forms the basis for efficient software development.
Undertake Mini-Projects & Explore Core CS Domains- (Semester 4-5)
Apply theoretical knowledge from courses like Operating Systems, DBMS, and Computer Networks by building small-scale projects. Explore online courses or certifications in areas of interest, such as web development or cybersecurity, to gain practical exposure.
Tools & Resources
GitHub, online tutorials (e.g., freeCodeCamp, Udemy), departmental project labs, faculty guidance
Career Connection
Practical project experience is highly valued by recruiters, demonstrating application skills, domain knowledge, and a proactive approach to learning and problem-solving.
Network with Alumni & Seek Early Internship Opportunities- (Semester 4-5)
Connect with NIT Patna CSE alumni on LinkedIn for mentorship and career advice. Start looking for summer internship opportunities (even unpaid) after 2nd or 3rd year to gain early industry exposure and understand professional work environments.
Tools & Resources
LinkedIn, college career services, alumni network platforms
Career Connection
Internships provide invaluable real-world experience, often convert into pre-placement offers, and significantly build a professional network beneficial for future job searches.
Advanced Stage
Specialize and Deep Dive into Emerging Technologies- (Semester 6-7)
Choose departmental electives wisely based on career interests (e.g., AI/ML, Cyber Security, Cloud Computing). Pursue advanced online courses, participate in hackathons, and contribute to open-source projects in your chosen domain to build expertise.
Tools & Resources
Coursera, edX, NPTEL advanced courses, Kaggle for data science, GitHub for open-source
Career Connection
Specialization makes you a more competitive candidate for niche roles and higher-paying jobs in specific tech fields, aligning your skills with industry demand.
Focus on Major Projects & Research (Capstone)- (Semester 7-8)
Dedicate significant effort to the Major Project (Semester 7 & 8). Aim for innovative solutions, potential publications if feasible, and a strong final presentation. Consider entrepreneurial avenues by converting a successful project into a startup idea.
Tools & Resources
Research papers, faculty mentors, university labs, innovation centers
Career Connection
A strong capstone project is a key differentiator in placements, showcasing advanced problem-solving, engineering skills, and often attracts direct industry attention for job offers or further research opportunities.
Intensive Placement Preparation & Soft Skills Development- (Semester 7-8)
Begin rigorous placement preparation, including mock interviews, aptitude tests, and resume building workshops. Enhance essential soft skills like communication, teamwork, and leadership through college workshops and extracurricular activities to be well-rounded.
Tools & Resources
College placement cell, career counseling, online aptitude test platforms, group discussion practice sessions
Career Connection
Comprehensive preparation ensures readiness for campus recruitment drives, maximizing chances of securing desirable job offers from top companies in the Indian and global tech landscape.
Program Structure and Curriculum
Eligibility:
- No eligibility criteria specified
Duration: 8 semesters / 4 years
Credits: 160 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PH101 | ENGINEERING PHYSICS | Core | 4 | Classical and Quantum Mechanics, Electromagnetic Theory, Optics, Solid State Physics, Lasers and Fiber Optics |
| MA101 | MATHEMATICS – I | Core | 4 | Differential Calculus, Integral Calculus, Multivariable Calculus, Vector Calculus, Ordinary Differential Equations |
| CH101 | ENGINEERING CHEMISTRY | Core | 4 | Chemical Bonding, Thermodynamics, Electrochemistry, Reaction Kinetics, Spectroscopy |
| CS101 | PROGRAMMING FOR PROBLEM SOLVING | Core | 3 | Introduction to Programming, Control Structures, Functions, Arrays, Pointers, Structures |
| ME101 | ENGINEERING GRAPHICS | Core | 3 | Orthographic Projections, Isometric Projections, Sectional Views, AutoCAD Basics, Development of Surfaces |
| PH102 | ENGINEERING PHYSICS LAB | Lab | 1 | Experiments on Optics, Electricity and Magnetism, Quantum Phenomena, Semiconductor Devices |
| CH102 | ENGINEERING CHEMISTRY LAB | Lab | 1 | Volumetric Analysis, Instrumental Methods, Water Analysis, Organic Synthesis, Polymer Characterization |
| CS102 | PROGRAMMING FOR PROBLEM SOLVING LAB | Lab | 1 | Problem solving using C language, Implementation of algorithms, Debugging techniques, Data handling |
| ME102 | WORKSHOP PRACTICE | Lab | 2 | Carpentry, Welding, Fitting, Sheet Metal, Machining |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| EE101 | BASIC ELECTRICAL ENGINEERING | Core | 4 | DC Circuits, AC Circuits, Transformers, Motors, Power Systems |
| EC101 | BASIC ELECTRONICS ENGINEERING | Core | 4 | Diodes, Transistors, Amplifiers, Oscillators, Digital Logic Gates |
| MA102 | MATHEMATICS – II | Core | 4 | Differential Equations, Laplace Transforms, Fourier Series, Partial Differential Equations, Complex Analysis |
| HS101 | COMMUNICATION SKILLS | Core | 2 | Oral Communication, Written Communication, Presentation Skills, Group Discussion, Interview Techniques |
| BT101 | BIOLOGY FOR ENGINEERS | Core | 2 | Cell Biology, Genetics, Microbiology, Bioenergetics, Biomaterials |
| ES101 | ENVIRONMENTAL SCIENCE | Core | 2 | Ecosystems, Biodiversity, Pollution, Renewable Energy, Environmental Management |
| EE102 | BASIC ELECTRICAL ENGINEERING LAB | Lab | 1 | DC circuit experiments, AC circuit experiments, Motor characteristics, Transformer tests |
| EC102 | BASIC ELECTRONICS ENGINEERING LAB | Lab | 1 | Diode characteristics, Transistor circuits, Logic gate verification, Op-Amp applications |
| HS102 | LANGUAGE LAB | Lab | 1 | Pronunciation, Listening Comprehension, Public Speaking, Role Plays, Software-based language learning |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA201 | MATHEMATICS – III | Core | 4 | Probability Theory, Random Variables, Probability Distributions, Statistical Inference, Regression Analysis |
| CS201 | DATA STRUCTURES | Core | 3 | Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, Hashing |
| CS202 | DISCRETE MATHEMATICAL STRUCTURES | Core | 4 | Set Theory, Logic, Relations and Functions, Graph Theory, Algebraic Structures |
| CS203 | DIGITAL ELECTRONICS & LOGIC DESIGN | Core | 3 | Boolean Algebra, Logic Gates, Combinational Circuits, Sequential Circuits, Memories |
| CS204 | OBJECT ORIENTED PROGRAMMING | Core | 3 | Classes and Objects, Inheritance, Polymorphism, Abstraction, Encapsulation, Exception Handling |
| CS205 | DATA STRUCTURES LAB | Lab | 1 | Implementation of Data Structures, Algorithm analysis, Sorting and Searching |
| CS206 | DIGITAL ELECTRONICS & LOGIC DESIGN LAB | Lab | 1 | Logic gate implementation, Combinational circuit design, Sequential circuit design |
| CS207 | OBJECT ORIENTED PROGRAMMING LAB | Lab | 1 | C++ or Java programming, Object-oriented principles, GUI programming |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS208 | DESIGN AND ANALYSIS OF ALGORITHMS | Core | 4 | Asymptotic Notation, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms |
| CS209 | COMPUTER ORGANIZATION AND ARCHITECTURE | Core | 4 | CPU Structure, Memory Hierarchy, I/O Organization, Pipelining, Instruction Set Architectures |
| CS210 | OPERATING SYSTEMS | Core | 3 | Process Management, Memory Management, File Systems, I/O Systems, Deadlocks |
| CS211 | DATABASE MANAGEMENT SYSTEMS | Core | 3 | Relational Model, SQL, ER Diagrams, Normalization, Transaction Management, Concurrency Control |
| CS212 | SOFTWARE ENGINEERING | Core | 3 | Software Development Life Cycle, Requirements Engineering, Design Principles, Testing, Maintenance |
| CS213 | OPERATING SYSTEMS LAB | Lab | 1 | Linux commands, Shell scripting, Process management, Memory allocation, Synchronization |
| CS214 | DATABASE MANAGEMENT SYSTEMS LAB | Lab | 1 | SQL queries, Database design, PL/SQL, NoSQL databases |
| HS201 | PRINCIPLES OF ECONOMICS | Core | 2 | Microeconomics, Macroeconomics, Market Structures, National Income, Fiscal and Monetary Policy |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS301 | THEORY OF COMPUTATION | Core | 4 | Finite Automata, Regular Expressions, Context-Free Grammars, Pushdown Automata, Turing Machines, Decidability |
| CS302 | COMPUTER NETWORKS | Core | 3 | Network Topologies, OSI Model, TCP/IP Protocol Suite, Routing, Congestion Control, Network Security |
| CS303 | ARTIFICIAL INTELLIGENCE | Core | 3 | Problem Solving Agents, Search Algorithms, Knowledge Representation, Machine Learning Basics, Expert Systems |
| CS304 | COMPILER DESIGN | Core | 3 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization |
| CS305 | COMPUTER NETWORKS LAB | Lab | 1 | Network configuration, Socket programming, Protocol implementation, Network simulation tools |
| CS306 | ARTIFICIAL INTELLIGENCE LAB | Lab | 1 | AI programming languages (Prolog/Python), Search algorithms, Game playing agents |
| CS307 | HIGH PERFORMANCE COMPUTING (DE-I Example) | Elective | 3 | Parallel Computing, Distributed Systems, Cloud Computing, GPU Computing, Performance Metrics |
| OE-I | OPEN ELECTIVE – I | Elective | 3 |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS311 | MACHINE LEARNING | Core | 3 | Supervised Learning, Unsupervised Learning, Deep Learning Basics, Reinforcement Learning, Model Evaluation |
| CS312 | DISTRIBUTED SYSTEMS | Core | 3 | Distributed Architecture, Remote Procedure Calls, Distributed File Systems, Consistency, Fault Tolerance |
| CS313 | MACHINE LEARNING LAB | Lab | 1 | Python for ML, Scikit-learn, TensorFlow/PyTorch basics, Data preprocessing, Model training |
| CS314 | MINI PROJECT | Project | 2 | Project planning, System design, Implementation, Testing, Documentation |
| CS316 | BIG DATA ANALYTICS (DE-II Example) | Elective | 3 | Hadoop Ecosystem, MapReduce, Spark, Data Storage, Data Processing |
| CS320 | CYBER SECURITY (DE-III Example) | Elective | 3 | Cryptography, Network Security, Web Security, Malwares, Security Policies |
| OE-II | OPEN ELECTIVE – II | Elective | 3 |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS401 | MAJOR PROJECT – I | Project | 3 | Problem identification, Literature review, Methodology design, Prototype development, Interim report |
| CS402 | DEEP LEARNING (DE-IV Example) | Elective | 3 | Neural Networks, Convolutional Networks, Recurrent Networks, Generative Models, Deep Learning Frameworks |
| CS403 | CLOUD COMPUTING (DE-V Example) | Elective | 3 | Cloud Architecture, Virtualization, AWS/Azure/GCP, Cloud Security, Microservices |
| OE-III | OPEN ELECTIVE – III | Elective | 3 | |
| HS401 | MANAGEMENT PRINCIPLES & CONCEPTS | Core | 3 | Principles of Management, Planning, Organizing, Staffing, Directing, Controlling |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS408 | MAJOR PROJECT – II | Project | 6 | Advanced development, Testing and deployment, Performance evaluation, Final documentation, Presentation |
| CS411 | DIGITAL FORENSICS (DE-VI Example) | Elective | 3 | Digital Evidence, Forensic Tools, Network Forensics, Mobile Forensics, Legal Aspects |
| OE-IV | OPEN ELECTIVE – IV | Elective | 3 |
