Official Prospectus 2026

School of Computer Science Engineering & Technology

Building the next generation of innovators, developers, and tech leaders.

Govt. College Dharamshala, Himachal Pradesh - 176215

Prof. Rakesh Pathania

Principal, GC Dharamshala

From the Principal's Desk

I extend a warm welcome to all in Government College Dharamshala, one of the most prestigious colleges of Himachal Pradesh. This college was established in 1926 and is on the verge of completing its successful journey of a hundred years. It is my proud privilege to serve the oldest college of the state as Principal.

It is a matter of happiness and pride that this college is accredited by NAAC with a B++ grade. The college is offering many graduate, post-graduate, and professional self-financing courses to the students. This college has excellent infrastructure, committed staff, and students from far-flung areas. Many committees, clubs, and units are constituted for the benefit and welfare of the students and the smooth functioning of the institution.

Dear students, this is the era of tough competition. You should increase your knowledge day by day. Make the best use of the library in the college as it has thousands of books, newspapers, magazines, and journals. There is no shortcut to success. Hard work is the only key to success and practice makes a man perfect.

Overuse and misuse of mobile phones, T.V., and the internet cause distraction, health hazards, and wastage of precious time. Instead, take part in sports and extra-curricular activities to groom up a healthy and balanced personality. In a true sense, education means acquiring sound knowledge and attaining strong values of life to be refined human beings and responsible citizens.

May God bless you all!

My best wishes to each one associated with Government College Dharamshala.

Prof. Rakesh Pathania

Principal

Government College Dharamshala, District Kangra HP

Academic Excellence

Our Commitments & Methodology

We emphasize contemporary knowledge, professional skill development, and student-driven learning to prepare you for the demanding business and tech world.

Interactive Learning

Focus on interactive lectures, case analysis, role play, business simulations, games, assignments, and quiz competitions.

Computer Based Training

Regular practical training provided by subject experts using the latest software, hardware resources, and multimedia setups.

Expert Lectures

Frequent lectures and interactive sessions by eminent personalities and academicians from renowned institutions and industry.

Project Assignments

Specific project work including live industrial projects and practical assignments to develop true workmanship.

Educational Tours

Annual educational and industrial tours organized to make students aware of the changing scenarios in the industrial sector.

Culture & Lifestyle

A blend of activities nurturing independence, self-discipline, and energy to build your drive for self-initiative and results.

Code of Conduct & General Rules

The decision of the Principal in all matters will be final and binding.
Students must be seated before the start of the lecture. No entry is allowed 5 minutes after the class starts.
Regular attendance in classes and guest lectures is compulsory. Name will be struck-off if a candidate absents continuously for six days.
Use of mobile phones is strictly prohibited in the college premises.
Misbehavior, persistent disobedience, consumption of drugs/liquor, or cheating may invite strict disciplinary action including expulsion.
Each student is expected to observe the college dress code strictly. Boys must have properly trimmed beards; girls must keep hair in proper order.
No student is permitted to undertake any part-time/whole-time job during the course of study.
Food, breweries, and drinks are not permitted in the labs or classrooms.
Students must not leave the campus during teaching hours without prior permission.
Every student must always carry their duly completed identity card.

RAGGING IS A COGNIZABLE OFFENCE

...Any act of Ragging would not go unnoticed and unpunished...

Ragging of all kinds is strictly banned in the college campus. Anyone indulging in ragging is likely to be punished appropriately. Punishments include imprisonment, fine, expulsion from the institution, or suspension from classes/hostel.

Toll Free Helpline

1800 - 180 - 5522

B.Tech in Computer Science & Engineering

To create motivated, innovative, and creative-thinking graduates capable of filling ICT positions across sectors. Our students are trained to conceptualize, design, analyze, and develop applications to meet modern-day requirements.

The School of Computer Science and Engineering at Govt. College Dharamshala offers a four-year B.Tech (CSE) degree spread over eight semesters. This course is affiliated to Himachal Pradesh Technical University (HPTU) Hamirpur and is approved by the All India Council for Technical Education (AICTE), New Delhi.

The department provides industrial visits, training, seminars, and workshops on the latest software technologies. We boast a well-qualified faculty per AICTE norms and a dedicated career guidance and placement cell working efficiently to place students in leading MNCs.

Our Vision

To contribute to the state and India through excellence in scientific and technical education and research, serving as a valuable resource for Industry and Society. We are committed to creating conditions that enable all students to experience an educational journey that is intellectually, socially, and personally transformative.

Our Mission

Provide the best technical education to generate new knowledge in rural areas.
Develop the personality, talent, and employability skills of students.
Increase self-confidence and leadership quality.
Develop a positive attitude, good ethics, and social values.
Foster team spirit to achieve organizational goals.

Overall Programme Objectives

Technical Foundations

Understanding computing at different levels including OOPS, Cloud Computing, IoT circuits, architecture, OS, and algorithms.

Problem Solving

Ability to adapt established models, techniques, and algorithms for efficiently solving new problems and designing computer-based systems.

Professional Growth

Function effectively in teams, communicate effectively, understand ethical responsibilities, and engage in life-long learning.

Research & Entrepreneurship

Undertake small research tasks and projects, with the ability to take an idea and develop it into a business plan for an entrepreneurial venture.

Societal Impact

An understanding of the impact of technological solutions in an economic, societal, and environmental context.

Admission Criteria & Eligibility

Eligibility: The candidate must have passed 10+2 or its equivalent examination from a recognized Board with Physics and Mathematics as compulsory subjects, securing at least 45% marks (40% for reserved categories).

Basis of Admission

First 50% Seats: Based on merit/rank/score obtained in the current JEE (Main).
Remaining 50% Seats: Filled on the basis of merit in the current year HPCET.
Vacant Seats: If seats remain vacant after exhausting JEE (Main) and HPCET merit, they will be filled based on 10+2 examination merit.

Schedule of Fines (in Rs.)

Violation	Fine Amount (Rs.)
Absence fine for a period	05.00
Absence fine for a practical	05.00
Absence fine for Tutorial Classes	10.00
Absence fine for Class Tests	10.00
Absence fine for House Exam	100.00
Fine for delay in returning library book (per day)	02.00
Fine for not wearing Dress Code in college	100.00
Without Identity Card	10.00
Mobile Phone fine in Deptt./Lab/Class Room	Strict Disciplinary Action

Dress code (gray pant, light blue striped shirt, navy blue coat, striped blue tie, formal black shoes/belt) is compulsory for B.Tech (CSE) students except on Thursdays.

Required Documents

Ensure the following documents are attached with your application form and ready for checking before submission.

1. Application Form

Online Application Form (Students may upload on spot in the CSE department)

2. Attested Copies of Certificates

Matriculation (10th)
Plus Two (10+2)
Graduation (If applicable)
Proof of JEE/HPCET score
Counselling letter from HPTU, Hamirpur

3. Original / Photocopy Certificates

Certificate of Caste / Tribe / Antyodaya / IRDP
Income Certificate (If parents' income is < Rs. 5000/month)
Certificate for Physically Handicapped (if applicable)
Bonafide Himachali Certificate
Character Certificate in Original
Affidavit of gap year (if any)

Academic Excellence

Teaching Methodology

We emphasize contemporary knowledge, professional skill development, and student-driven learning to prepare you for the demanding business and tech world.

Interactive Learning

Focus on interactive lectures, case analysis, role play, business simulations, games, assignments, and quiz competitions.

Computer Based Training

Regular practical training provided by subject experts using the latest software, hardware resources, and multimedia setups.

Expert Lectures

Frequent lectures and interactive sessions by eminent personalities and academicians from renowned institutions and industry.

Project Assignments

Specific project work including live industrial projects and practical assignments to develop true workmanship.

Educational Tours

Annual educational and industrial tours organized to make students aware of the changing scenarios in the industrial sector.

Culture & Lifestyle

A blend of activities nurturing independence, self-discipline, and energy to build your drive for self-initiative and results.

B.Tech Curriculum

Course Outline

Comprehensive breakdown of theoretical subjects, practical labs, and major projects required for the B.Tech (CSE) degree.

S.No.	Category	Code	Subject Title	L	T	P	Credits	IA	ESE	Total
Theory Subjects
1	HSMC	HSMC-101	English	2	0	0	2	40	60	100
2	BSC	BSC-101	Physics	3	1	0	4	40	60	100
3	BSC	BSC-102	Mathematics-I	3	1	0	4	40	60	100
4	ESC	ESC-101	Basic Electrical Engineering	3	1	0	4	40	60	100
Practical / Labs
1	HSMC	HSMC-101P	English Lab	0	0	2	1	30	20	50
2	BSC	BSC-101P	Physics Lab	0	0	2	1	30	20	50
3	ESC	ESC-101P	Basic Electrical Engg. Lab	0	0	2	1	30	20	50
4	ESC	ESC-102P	Engineering Workshop	0	0	4	2	50	50	100

S.No.	Category	Code	Subject Title	L	T	P	Credits	IA	ESE	Total
Theory Subjects
1	BSC	BSC-103	Chemistry	3	1	0	4	40	60	100
2	BSC	BSC-104	Mathematics-II	3	1	0	4	40	60	100
3	ESC	ESC-103	Programming for Problem Solving	3	0	0	3	40	60	100
Practical / Labs
1	BSC	BSC-103P	Chemistry Lab	0	0	2	1	30	20	50
2	ESC	ESC-103P	Programming Lab	0	0	4	2	50	50	100
3	ESC	ESC-104P	Engineering Graphics & Design	0	0	4	2	50	50	100

S.No.	Category	Code	Subject Title	L	T	P	Credits	IA	ESE	Total
Theory Subjects
1	BS	MAFC-311	Probability Theory and Statistics	3	1	0	4	40	60	100
2	PC	CSPC-311	Data Structure and Algorithms	3	1	0	4	40	60	100
3	PC	CSPC-312	Python Programming	2	0	0	2	40	60	100
4	PC	CSPC-313	Computer Organization and Architecture	3	1	0	4	40	60	100
5	PC	ECEPC-312	Digital System Design	3	0	0	3	40	60	100
6	HS	IKS-311	Indian Knowledge System	2	0	0	2	40	60	100
7	HS	HS-311	Engineering Economics	2	0	0	2	40	60	100
Practical / Labs
1	PC	CSPC-311P	Data Structure and Algorithms Lab	0	0	2	1	30	20	50
2	PC	CSPC-312P	Python Programming Lab	0	0	2	1	30	20	50
3	PC	ECEPC-312P	Digital System Design Lab	0	0	2	1	30	20	50

S.No.	Category	Code	Subject Title	L	T	P	Credits	IA	ESE	Total
Theory Subjects
1	PC	CSPC-411	Discrete Mathematics	3	0	0	3	40	60	100
2	PC	CSPC-412	Operating System	3	1	0	4	40	60	100
3	PC	CSPC-413	Design and Analysis of Algorithm	3	1	0	4	40	60	100
4	PC	CSPC-414	Artificial Intelligence in Engineering	3	0	0	3	40	60	100
5	PC	CSPC-415	Database Management System	3	1	0	4	40	60	100
6	PC	ECEPC-412	Microcontrollers	3	0	0	3	40	60	100
Practical / Labs
1	PC	CSPC-413P	DAA Lab	0	0	2	1	30	20	50
2	PC	CSPC-414P	AI Lab	0	0	2	1	30	20	50
3	PC	CSPC-415P	DBMS Lab	0	0	2	1	30	20	50
Exit Option
1	INT	CSE-416P	Internship-I (Exit Option)	-	-	-	6	30	20	50

S.No.	Category	Code	Subject Title	L	T	P	Credits	IA	ESE	Total
Theory Subjects
1	PC	CSPC-511	Computer Networks	3	1	0	4	40	60	100
2	PC	CSPC-512	Theory of Computation	3	1	0	4	40	60	100
3	PC	CSPC-513	Intro to Machine Learning	3	1	0	4	40	60	100
4	PC	CSPC-514	Software Engineering	3	0	0	3	40	60	100
5	PC	CSPC-515	Data Warehouse & Mining	3	0	0	3	40	60	100
Practical / Labs
1	PC	CSPC-511P	Computer Networks Lab	0	0	2	1	30	20	50
2	PC	CSPC-513P	Machine Learning Lab	0	0	2	1	30	20	50

S.No.	Category	Code	Subject Title	L	T	P	Credits	IA	ESE	Total
Theory Subjects
1	PC	CSPC-613	Compiler Design	3	1	0	4	40	60	100
2	PC	CSPC-614	Computer Graphics	3	0	0	3	40	60	100
3	PE	CSPE-611	Internet of Things	3	0	0	3	40	60	100
4	PE	CSPE-612	Advanced Computer Network	3	0	0	3	40	60	100
5	HS	SIE-611	Start-Up, Innovation and Entrepreneurship	2	0	2	3	50	50	100
Practical / Labs
1	PC	CSPC-613P	Compiler Design Lab	0	0	2	1	30	20	50
2	PC	CSPC-614P	Computer Graphics Lab	0	0	2	1	30	20	50
3	EE	CSEE-611P	Capstone Project-I	0	0	4	2	60	40	100
B.Sc. Degree Exit Option
1	EE	CSEE-613P	Internship-II (Exit)	-	-	-	6	50	50	100

S.No.	Category	Code	Subject Title	L	T	P	Credits	IA	ESE	Total
Theory Subjects
1	PC	CSPC-711	Cloud Computing*	3	1	0	4	40	60	100
2	PC	CSPC-712	Natural Language Processing**	3	1	0	4	40	60	100
3	OE	CSOE-711x	Open Elective-I	3	0	0	3	40	60	100
4	PE	CSPE-711x	Professional Elective-III	3	0	0	3	40	60	100
5	PE	CSPE-712x	Professional Elective-IV	3	0	0	3	40	60	100
Labs & Projects
1	EE	CSEE-711P	Seminar	0	0	2	1	50	50	100
2	EE	CSEE-712P	Major Project-I	0	0	6	3	60	40	100
3	EE	CSEE-713P	Internship Presentation	0	0	0	2	50	50	100

S.No.	Category	Code	Subject Title	L	T	P	Credits	IA	ESE	Total
1	EE	CSEE-811P	Major Project-II (Prototype & Testing)	0	0	24	12	300	200	500
OR
2	EE	CSEE-812P	Industrial Project/Internship OR Research Project	0	0	24	12	300	200	500

UNIT I: INTRODUCTION & STACKS

Basic Concepts: Data and Information, Introduction to Data Structure, Classification of Data Structure, Operations on Data Structures, Algorithm, Algorithms Complexity (Time and Space).

Stacks: Introduction to Stacks, Array representation of Stacks, Operations on Stacks (Push, Pop, Peek, Full, Empty), Applications of Stacks: Infix to Postfix conversion, Evaluation of Postfix expression, Recursion.

UNIT II: QUEUES & LINKED LISTS

Queues: Introduction to Queues, Array representation of Queues, Operations on Queues, Linear Queue, Circular Queue, Priority Queue.

Linked Lists: Introduction to Linked Lists, Representation of Linked List in Memory, Singly Linked List: Traversing, Insertion, Deletion, Doubly Linked List, Circular Linked List, Applications of Linked Lists.

UNIT III: TREES & GRAPHS

Trees: Basic Terminology, Binary Trees, Representation of Binary Tree in Memory, Tree Traversals (Preorder, Inorder, Postorder), Binary Search Trees: Searching, Insertion, Deletion.

Graphs: Basic Terminology, Representation of Graph (Adjacency Matrix, Adjacency List), Graph Traversals: Breadth First Search (BFS), Depth First Search (DFS).

UNIT IV: SEARCHING & SORTING

Searching: Linear Search, Binary Search.

Sorting: Selection Sort, Bubble Sort, Insertion Sort, Quick Sort, Merge Sort, Heap Sort.

Hashing: Introduction to Hashing, Hash Functions, Collision Resolution Techniques.

Suggested Text Books:

Seymour Lipschutz, "Data Structures", Revised First Edition, Schaum’s Outline Series, McGraw Hill.
R. Gilberg and B. Forouzan, "Data Structures: A Pseudo-code approach with C", Second Edition, Cengage Learning.

Course Learning Outcomes (CLOs)

Perform operations on various discrete structures such as set, function and relation.
Apply basic concepts of asymptotic notation in analysis of algorithm.
Illustrate the basic properties and algorithms of graphs and apply them in modeling and solving real world problems.
Comprehend formal Logical arguments and translate statements from a natural language into its symbolic structures in logic.
Identify and prove various properties of rings, field, and groups.

Unit-I: Sets, Relations and Functions

Operations on Set, Inclusion-Exclusion principle, Representation of Discrete Structures, Fuzzy Set, Multi-set, Bijective function, Inverse and Composition of functions, Floor and Ceiling functions, Growth of functions: Big-O notation, functions, Recursive function, Functions applications.

Unit-II: Relations

Reflexivity, Symmetry, Transitivity, Equivalence, and partial ordered relations, Asymmetric, Irreflexivity relation, Inverse and Complementary relations, partitions and Covering of a set, N-ary Relations and database, Representation relation using matrices and digraph, Closure of relations, Warshall’s algorithms, Lexicographic Ordering, Hasse diagram, Lattices, Boolean algebra, Application of transitive Closure in medicine and engineering. Application: Embedding a partial order.

Unit-III: Graph Theory & Basic Logic

Graph Theory: Representation, Type of Graphs, Paths, and Circuits: Euler Graphs, Hamiltonians Paths & Circuits: Cut Sets, Connectivity and Separability, Planar Graphs, Isomorphisms, Graph Coloring, Covering and Partitioning, Max flow: Ford-Fulkerson algorithm, Application of Graph Theory in real life applications.

Basic Logic: Propositional Logic, Logical connectives, Truth Tables, Normal Forms (Conjunctive and Disjunctive), Validity of well-formed formula, Propositional inference rules (Concepts of modus ponens and modus tollens), Predicate Logic, Universal and existential quantification.

Unit-IV: Proof Techniques and Algebraic Structure

Proof Techniques and Counting: Notions of Implications, equivalence, converse, inverse, contra positive, negation and contradiction, The structure of mathematical proofs, Direct proofs, disproving by counter example, Proof by contradiction, Induction over natural numbers, structural induction, weak and strong induction, The pigeonhole principle, solving homogenous and heterogeneous recurrence relations.

Algebraic Structure: Group, Semi-group, Monoids, Homomorphism, Congruencies, Ring, Field, Homomorphism, Congruencies, Applications of algebra to control structure of a program, the application of Residue Arithmetic to Computers.

Textbooks:

Rosen H.K., Discrete mathematics and its Applications, McGraw Hill (2011) 7th ed.
Tremblay P.J. and Manohar, R., Discrete Mathematical Structures with Applications to Computer Science, Tata McGraw Hill (2008).

Course Objectives (COs)

To understand the role, responsibilities and the algorithms involved for achieving various functionalities of an Operating System.

Unit-I: Introduction and System Structures

Introduction: Types of operating systems, Computer System Operation, Operating-System Services, System Calls, Types of System Calls.

Process Management: Process Concept, Process Scheduling, Operations on Processes, Inter-process Communication.

Multi-threaded programming: Multi-core Programming, Multithreading Models.

Unit-II: Process Scheduling & Deadlock

Process Scheduling: Basic Concepts, Scheduling Criteria, Scheduling Algorithms, Multiple-Processor Scheduling.

Concurrency: The Critical-Section Problem, Synchronization Hardware, Semaphores, Classic Problems of Synchronization, Monitors.

Deadlock: System Model, Deadlock Characterization, Methods for Handling Deadlocks, Deadlock Prevention, Deadlock Avoidance, Deadlock Detection, Recovery from Deadlock.

Unit-III: Memory & File Management

Memory Management: Basic Hardware, Address Binding, Logical and Physical Address, Dynamic linking and loading, Shared Libraries, Swapping, Contiguous Memory Allocation, Segmentation, Paging, Structure of the Page Table, Virtual Memory Management: Demand Paging, Page Replacement, Allocation of Frames, Thrashing.

File Systems: File Concept, Access Methods, Directory and Disk Structure, File-System Mounting, File Sharing, Protection, File-System Structure, File-System Implementation, Directory Implementation, Allocation Methods, Free-Space Management.

Unit-IV: Disk Management & Security

Disk Management: Mass Storage Structure, Disk Structure, Disk Attachment, Disk Scheduling, Disk Management, Swap-space Management, RAID Structure.

Protection and Security: Goals of Protection, Domain of protection, Access rights, Unix/Linux Case study.

Course Learning Outcomes (CLOs)

Explain the basic of an operating system viz. system programs, system calls, user mode and kernel mode.
Select particular CPU scheduling algorithms for specific situation and analyses the environment leading to deadlock and its rectification.
Explicate memory management techniques viz. caching, paging, segmentation, virtual memory, and thrashing.
Understand the concepts related to file systems, disk scheduling and security, protection.
Comprehend the concepts related to concurrency.

Textbooks:

Silberschatz A., Galvin B.P. and Gagne G., Operating System Concepts, John Wiley & Sons Inc (2013) 9th ed.
Stallings W., Operating Systems Internals and Design Principles, Prentice Hall (2018) 9th ed.

Course Objectives

To impart knowledge about the asymptotic notations to analyze the performance of algorithms.
To introduce the fundamental concepts of various problem-solving techniques such as divide and conquer, greedy algorithms, etc.
To enable the students to understand the concepts of P, NP, NP-hard and NP-complete problems.

Unit-I: Introduction & Divide and Conquer

Algorithm Introduction; Algorithm Design paradigms- motivation, concept of algorithmic efficiency, run time analysis of algorithm, Asymptotic Notations. Divide and Conquer Approach: Structure of divide-and-conquer algorithms; sets and disjoint sets: Union and Find algorithms; quick sort, Finding the maximum and minimum, Quick Sort, Merge sort, Heap and heap sort.

Unit-II: Greedy & Graph Algorithms

Greedy Algorithms: Optimal storage on tapes, Knapsack problem, Job sequencing with deadlines, Minimum Spanning trees: Prim’s algorithm and Kruskal’s algorithm, Huffman codes.

Graph Algorithms: Representation of graphs, BFS, DFS, Topological sort, strongly connected components; single source shortest paths: Bellman-Ford algorithm, Dijkstra’s algorithm; All pairs shortest path: The Warshall’s algorithm.

Unit-III: Dynamic Programming & Backtracking

Dynamic Programming: Overview, difference between dynamic programming and divide and conquer, Matrix chain multiplication, Traveling salesman Problem, longest Common sequence, 0/1 knapsack. Backtracking: 8-Queen Problem, Sum of subsets, graph colouring, Hamiltonian cycles.

Unit-IV: Branch and Bound & Complexity

Branch and Bound: LC searching Bounding, FIFO branch and bound, LC branch and bound application: 0/1 Knapsack problem, Traveling Salesman Problem. Computational Complexity: Complexity measures, Polynomial vs. non-polynomial time complexity; NP-hard and NP-complete classes, examples.

Reference / Text Books:

T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, "Introduction to Algorithms", MIT Press.
Ellis Horowitz, Sartaj Sahni, and Sanguthevar Rajasekaran, "Fundamentals of Computer Algorithms", Galgotia Publications.

Course Outcomes (COs)

Remember the fundamentals, history, and applications of AI in mechanical engineering.
Understand various AI approaches, including cybernetic, symbolic, sub-symbolic, and statistical methods, in mechanical engineering.
Apply data preprocessing techniques like cleaning, feature selection, and normalization in machine learning.
Analyze the ethical and social implications of AI, including job impacts and regulatory issues.
Evaluate machine learning algorithms, neural networks, and fuzzy logic systems for mechanical engineering applications.

Unit-I: Fundamentals of AI & Social Implications

Fundamentals of AI: Introduction to AI, History of AI, General applications of AI, Need of AI in Engineering, Problem solving, Process of problem solving, breadth first search, depth first search, heuristics search techniques, best first search, Introduction to intelligent systems, Various approaches to AI: Cybernetics and brain simulation, Symbolic, Sub-symbolic, Statistical.

Ethical and Social Implications of AI: Ethical considerations in AI development and deployment, Impact of AI on jobs and society, Regulatory and policy issues.

Unit-II: Fundamentals of Machine Learning (ML)

Introduction: Introduction to Machine Learning, datasets, Forms of Learning: Supervised and Unsupervised Learning, reinforcement learning, processes involved in Machine Learning, Applications of ML in Engineering.

Data Preprocessing and Approaches: Data preprocessing, cleaning and normalization; Approaches in Machine Learning (ML): Data preprocessing, Data cleaning, Feature selection and extraction, Data normalization and scaling.

Unit-III: Artificial Neural Networks (ANNs)

Introduction to Artificial Neural Networks (ANNs): Definition and history of ANNs, Types of ANNs architectures, Basic architecture of ANNs, Activation functions, Singled-Layered and Multi-Layered Perceptron, Backpropagation algorithms, Applications of ANNs in Engineering.

Unit-IV: Fuzzy Logic and Genetic Algorithms

Fuzzy Logic: Introduction to Fuzzy Logic: Basic concepts, history, and fuzzy set theory; Processes in a fuzzy logic system, Applications of Fuzzy Logic in Engineering.

Genetic Algorithm (GA): Basics of GA, Main operations of GA, Flowchart of GA, Working principle of GA in step by step, Applications in Engineering.

Text Books:

Deisenroth, Faisal, Ong, Mathematics for Machine Learning, Cambridge University Press, 2020.
B Joshi, Machine Learning and Artificial Intelligence, Springer, 2020.
Parag Kulkarni and Prachi Joshi, Artificial Intelligence – Building Intelligent Systems, PHI learning Pvt. Ltd., ISBN – 978-81-203-5046-5, 2015.

Course Objectives

To Understand the basic concepts and the applications of database systems.
To Master the basics of SQL and construct queries using SQL.
To understand the relational database design principles.
To become familiar with the basic issues of transaction processing and concurrency control.
To become familiar with database storage structures and access techniques.

Unit-I: Introduction & Data Modeling

Database Management System: Introduction, Applications, Purpose of Database Systems, View of Data – Data Abstraction – Instances and Schemas – data Models – the ER Model – Relational Model – Other Models – Database Languages – DDL – DML – database Access for applications Programs – database Users and Administrator – Transaction Management – data base Architecture – Storage Manager – the Query Processor Data base design and ER diagrams – ER Model - Entities, Attributes and Entity sets – Relationships and Relationship sets – ER Design Issues – Concept Design – Conceptual Design for University Enterprise. Introduction to the Relational Model – Structure – Database Schema, Keys – Schema Diagrams.

Unit-II: Relational Languages & SQL

Relational Query Languages, Relational Operations. Relational Algebra – Selection and projection set operations – renaming – Joins – Division – Examples of Algebra overviews – Relational calculus – Tuple relational Calculus – Domain relational calculus. Overview of the SQL Query Language – Basic Structure of SQL Queries, Set Operations, Aggregate Functions – GROUPBY – HAVING, Nested Sub queries, Views, Triggers.

Unit-III: Normalization

Normalization – Introduction, Non loss decomposition and functional dependencies, First, Second, and third normal forms – dependency preservation, Boyce Codd normal form. Higher Normal Forms - Introduction, Multi-valued dependencies and Fourth normal form, Join dependencies and Fifth normal form.

Unit-IV: Transaction Management & NoSQL

Transaction Concept- Transaction State- Implementation of Atomicity and Durability – Concurrent Executions – Serializability- Recoverability – Implementation of Isolation – Testing for serializability- Lock -Based Protocols – Timestamp Based Protocols- Validation- Based Protocols – Multiple Granularity. Recovery and Atomicity – Log – Based Recovery – Recovery with Concurrent Transactions, Introduction to NOSQL.

Course Learning Outcomes (CLOs)

Explain the features of database management systems and Relational database.
Create and populate a RDBMS for a real-life application, with constraints and keys, using SQL and retrieve any type of information from a data base by formulating complex queries in SQL.
Analyze the existing design of a database schema and apply concepts of normalization to design an optimal database and build indexing mechanisms for efficient retrieval of information from a database.

Textbooks:

Data base Management Systems, Raghurama Krishnan, Johannes Gehrke, TATA McGraw Hill 3rd Edition.
A Silberschatz, H Korth, S Sudarshan, “Database System and Concepts”, fifth Edition McGraw-Hill.
Data base System Concepts, Silberschatz, Korth, McGraw hill, Sixth Edition.

Mentors & Guides

Our Esteemed Faculty

Experienced academicians and subject matter experts dedicated to shaping the theoretical foundation and technical skills of our B.Tech students.

Applied Sciences & Humanities

Eminent Guest Faculty & Industry Experts

Bridging the gap between academia and the corporate world through constant interaction with industry leaders and renowned professors.

Dr. Dhirendra Sharma

Prof. UIIT Shimla

Dr. Sandeep Kumar Sood

Assoc. Professor, NIT Kurukshetra

Dr. Kumar S. Pandey

Professor, Dept of CSE, NIT Hamirpur

Dr. Sanjoy Das

Professor & Head, CS, IGNTU Imphal

Dr. Kamlesh Dutta

HOD, Dept of CSE, NIT Hamirpur

Dr. Vinod Sharma

Professor & Head, Univ. of Jammu

Dr. Mukesh Pandey

Professor & Dean, RGPV Bhopal

Dr. Dharmendra S. Rajput

Professor & Head, CSE, VIT

Dr. Puneet Sood

Dy. Director (Tech. Ed.), Govt of HP

Prof. Manoj Dhiman

Assistant Professor, CUHP

Prof. Vivek Kumar

Asst. Prof, Maths, Govt. College D/shala

Prof. Ramam Sharma

Asst. Prof, RG Govt. Engg College, Kangra

Er. Ravi Verma

Senior Developer, APTRON PVT. LTD.

Er. Rohit Soni

BDM, CS Soft Solutions, Mohali

Er. Sanjay Bhargva

CEO, Ignite Solutions, Dharamshala

Er. Varun Rattan Singh

CEO, Development Logics, Dharamshala

Er. Prabhu

CEO, Gai Technologies, Dharamshala

School of Computer Science Engineering & Technology

Prof. Rakesh Pathania

From the Principal's Desk

Prof. Rakesh Pathania

Our Commitments & Methodology

Interactive Learning

Computer Based Training

Expert Lectures

Project Assignments

Educational Tours

Culture & Lifestyle

Code of Conduct & General Rules

RAGGING IS A COGNIZABLE OFFENCE

1800 - 180 - 5522

B.Tech in Computer Science & Engineering

Our Vision

Our Mission

Overall Programme Objectives

Technical Foundations

Problem Solving

Professional Growth

Research & Entrepreneurship

Societal Impact

Admission Criteria & Eligibility

Basis of Admission

Schedule of Fines (in Rs.)

Required Documents

1. Application Form

2. Attested Copies of Certificates

3. Original / Photocopy Certificates

Teaching Methodology

Interactive Learning

Computer Based Training

Expert Lectures

Project Assignments

Educational Tours

Culture & Lifestyle

Course Outline

Our Esteemed Faculty

Sh. Rajnish Dewan

Dr. Pawan Thakur

Applied Sciences & Humanities

Dr. Ashish Ranjan

Dr. Shweta Gupta

Dr. Poonam Rana

Er. Divya Verma

Ms. Sunita Dhiman

Er. Harsh Guleria

Ms. Suman Bhardwaj

Dr. Aditya Sharma

Dr. Jyoti Bhardwaj

Eminent Guest Faculty & Industry Experts

Dr. Dhirendra Sharma

Dr. Sandeep Kumar Sood

Dr. Kumar S. Pandey

Dr. Sanjoy Das

Dr. Kamlesh Dutta

Dr. Vinod Sharma

Dr. Mukesh Pandey

Dr. Dharmendra S. Rajput

Dr. Puneet Sood

Prof. Manoj Dhiman

Prof. Vivek Kumar

Prof. Ramam Sharma

Er. Ravi Verma

Er. Rohit Soni

Er. Sanjay Bhargva

Er. Varun Rattan Singh

Er. Prabhu