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B-SC in Computer Science at GITAM (Gandhi Institute of Technology and Management)
Visakhapatnam, Andhra Pradesh
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About the Specialization
What is Computer Science at GITAM (Gandhi Institute of Technology and Management) Visakhapatnam?
This B.Sc Computer Science program at GITAM, Visakhapatnam, focuses on building a strong foundation in core computer science principles, alongside emerging areas like data analytics, machine learning, and web technologies. The curriculum is designed to meet the demands of India''''s rapidly growing IT sector, emphasizing practical skills and theoretical knowledge for a well-rounded computing professional.
Who Should Apply?
This program is ideal for recent 10+2 graduates with a strong aptitude for mathematics, logical reasoning, and an interest in technology. It caters to individuals aspiring to entry-level roles in software development, data analysis, or IT support, as well as those looking to pursue higher studies in computer science. Candidates from diverse academic backgrounds with a foundational understanding of computing concepts are encouraged to apply.
Why Choose This Course?
Graduates of this program can expect to secure roles such as Junior Software Developer, Data Analyst, Web Developer, or IT Support Specialist in Indian companies. Entry-level salaries typically range from 3-6 LPA, with significant growth potential in specialized fields. The program also prepares students for further academic pursuits like M.Sc or MCA, aligning with industry demand for skilled computing professionals across various sectors.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Dedicate significant time to understanding programming logic and syntax in languages like Python and Java. Regularly practice coding problems to solidify concepts and build problem-solving skills.
Tools & Resources
HackerRank, CodeChef, GeeksforGeeks, Official Language Documentation
Career Connection
A strong grasp of fundamentals is crucial for cracking technical interviews and excelling in any software development role.
Build Strong Mathematical Foundations- (Semester 1-2)
Focus on discrete mathematics and calculus concepts, which are foundational for advanced computer science topics like algorithms, data structures, and artificial intelligence. Practice problem-solving rigorously.
Tools & Resources
Khan Academy, NPTEL Courses, Textbooks and Exercise Sets
Career Connection
Strong mathematical skills are vital for roles in data science, machine learning, and algorithmic development.
Engage in Peer Learning and Collaborative Projects- (Semester 1-2)
Form study groups, discuss complex topics, and work together on small programming assignments. Collaborative learning enhances understanding and prepares for team-based industry projects.
Tools & Resources
GitHub (for version control), Google Docs (for collaboration), Departmental labs and study rooms
Career Connection
Teamwork and collaboration are highly valued soft skills in the IT industry, essential for project success.
Intermediate Stage
Undertake Practical Projects- (Semester 3-5)
Apply theoretical knowledge by developing mini-projects in areas like web development, database management, or simple AI applications. Focus on end-to-end implementation and problem-solving.
Tools & Resources
GitHub, VS Code, XAMPP/WAMP Server, Python/Java frameworks
Career Connection
Practical projects demonstrate application skills to potential employers and build a strong portfolio.
Seek and Complete Internships- (Semester 3-5 (during summer breaks))
Actively search for and complete internships, even short-term ones, to gain real-world industry exposure. Focus on learning industry best practices and expanding your professional network.
Tools & Resources
Internshala, LinkedIn, College Placement Cell, Naukri.com
Career Connection
Internships are critical for building experience, enhancing employability, and often lead to pre-placement offers.
Participate in Hackathons and Coding Competitions- (Semester 3-5)
Engage in hackathons and coding competitions to challenge your skills, work under pressure, and explore innovative solutions. This builds competitive spirit and problem-solving agility.
Tools & Resources
Major League Hacking (MLH), HackerEarth, College technical clubs, Online competitive programming platforms
Career Connection
Winning or participating actively in such events adds significant value to your resume and showcases initiative.
Advanced Stage
Specialize and Deepen Expertise- (Semester 6)
Identify a domain of interest (e.g., Data Science, AI, Cyber Security, Web Development) based on electives and project work. Pursue advanced learning through online courses, certifications, and specialized projects.
Tools & Resources
Coursera, Udemy, edX, NPTEL advanced courses, Industry certifications
Career Connection
Specialized knowledge makes you a valuable asset for targeted roles and higher-paying positions in specific tech domains.
Intensive Placement Preparation- (Semester 6)
Begin rigorous preparation for campus placements, focusing on aptitude tests, technical interview questions, and soft skills. Practice mock interviews and resume building with career services.
Tools & Resources
Company-specific interview guides, Mock interview platforms, Resume builders, Aptitude test preparation books/sites
Career Connection
Thorough preparation directly impacts placement success and the quality of job offers received.
Develop a Major Capstone Project- (Semester 5-6)
Collaborate on a significant final year project that solves a real-world problem or demonstrates innovative application of learned concepts. Document the process thoroughly and present findings effectively.
Tools & Resources
Project management tools (Jira, Trello), Advanced development environments, Research papers and journals, Faculty mentors
Career Connection
A strong capstone project is a powerful differentiator in placements and an excellent talking point during interviews, showcasing comprehensive skill application.
Program Structure and Curriculum
Eligibility:
- Intermediate or 10+2 with a minimum of 50% aggregate marks in any discipline from a recognised Central / State Board or equivalent with Mathematics / Computer Science / Statistics / Business Mathematics as one of the subjects.
Duration: 3 years (6 semesters)
Credits: 124 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSC 101 | Foundation Course in English | Foundation | 3 | Listening Skills, Speaking Skills, Reading Skills, Writing Skills, Grammar and Vocabulary |
| BSC 102 | Environmental Studies | Foundation | 3 | Multidisciplinary Nature of Environmental Studies, Ecosystems, Biodiversity and its Conservation, Environmental Pollution, Social Issues and the Environment |
| BSC 103 | Foundation Course in Mathematics | Foundation | 4 | Differential Calculus, Integral Calculus, Ordinary Differential Equations, Partial Differential Equations, Vector Calculus |
| BSC CS 101 | Programming in Python | Core | 4 | Introduction to Python, Data Types and Operators, Control Flow Statements, Functions and Modules, Object-Oriented Programming in Python |
| BSC CS 102 | Computer Organization | Core | 4 | Digital Logic Circuits, Data Representation, Central Processing Unit, Memory System, Input/Output Organization |
| BSC CS 103 | Programming in Python Lab | Lab | 3 | Basic Python Syntax, Conditional and Loop Structures, Function Implementation, File Handling, List, Tuple, Dictionary Operations |
| VAC 1 | Value Added Course - I | Value Added Course | 1 | Professional Ethics, Basic Soft Skills, Digital Literacy, Personal Effectiveness, Time Management |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSC 104 | Foundation Course in Communication Skills | Foundation | 3 | Types of Communication, Verbal and Non-verbal Communication, Interpersonal Skills, Presentation Skills, Writing for Professional Contexts |
| BSC CS 104 | Discrete Mathematical Structures | Core | 4 | Mathematical Logic, Set Theory and Relations, Functions, Graph Theory, Combinatorics |
| BSC CS 105 | Data Structures | Core | 4 | Introduction to Data Structures, Arrays and Linked Lists, Stacks and Queues, Trees, Graphs and Sorting Algorithms |
| BSC CS 106 | Operating Systems | Core | 4 | Introduction to Operating Systems, Process Management, CPU Scheduling, Memory Management, File Systems |
| BSC CS 107 | Object-Oriented Programming with Java | Core | 4 | OOP Concepts, Classes, Objects, and Methods, Inheritance and Polymorphism, Exception Handling, Multithreading and Collections |
| BSC CS 108 | Data Structures and Java Lab | Lab | 2 | Implementation of Data Structures, Java Programming Exercises, OOP Concepts Application, Debugging and Testing, GUI Programming Basics |
| VAC 2 | Value Added Course - II | Value Added Course | 1 | Critical Thinking, Creative Problem Solving, Introduction to Entrepreneurship, Workplace Readiness, Teamwork and Collaboration |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSC CS 201 | Database Management Systems | Core | 4 | DBMS Architecture, Entity-Relationship Model, Relational Model and Algebra, Structured Query Language (SQL), Normalization and Transaction Management |
| BSC CS 202 | Computer Networks | Core | 4 | Network Models (OSI/TCP-IP), Data Link Layer, Network Layer, Transport Layer, Application Layer Protocols |
| BSC CS 203 | Theory of Computation | Core | 4 | Finite Automata, Regular Expressions and Languages, Context-Free Grammars, Turing Machines, Decidability and Undecidability |
| BSC CS 204 | Web Technologies | Core | 4 | HTML and CSS, JavaScript Fundamentals, Client-Side Scripting, Web Servers and Databases, XML and AJAX |
| BSC CS 205 | Database Management Systems Lab | Lab | 3 | SQL Query Writing, Database Design, ER Diagrams Implementation, PL/SQL Programming, Transaction Control |
| SEC 1 | Skill Enhancement Course - I (e.g., Statistical Tools for Data Analysis) | Skill Enhancement | 2 | Descriptive Statistics, Probability Distributions, Hypothesis Testing, Regression Analysis, Data Visualization Techniques |
| GE 1 | Generic Elective - I (e.g., Introduction to Cloud Computing) | Elective | 2 | Cloud Computing Basics, Service Models (IaaS, PaaS, SaaS), Deployment Models, Virtualization, Cloud Security Fundamentals |
| VAC 3 | Value Added Course - III | Value Added Course | 1 | Emotional Intelligence, Stress Management, Conflict Resolution, Cultural Sensitivity, Ethical Hacking Awareness |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSC CS 206 | Design and Analysis of Algorithms | Core | 4 | Algorithm Analysis, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms |
| BSC CS 207 | Artificial Intelligence | Core | 4 | Introduction to AI, Problem Solving Agents, Search Algorithms, Knowledge Representation, Machine Learning Basics |
| BSC CS 208 | Software Engineering | Core | 4 | Software Life Cycle Models, Requirements Engineering, Software Design Principles, Software Testing Techniques, Software Project Management |
| BSC CS 209 | Web Technologies Lab | Lab | 3 | HTML and CSS Implementation, JavaScript DOM Manipulation, AJAX Integration, Frontend Framework Basics, Web Page Responsiveness |
| BSC CS 210 | Elective - I (e.g., Cloud Computing) | Elective | 4 | Cloud Architecture, Cloud Service Models (IaaS, PaaS, SaaS), Cloud Deployment Models, Virtualization Technologies, Cloud Security Best Practices |
| SEC 2 | Skill Enhancement Course - II (e.g., R Programming) | Skill Enhancement | 2 | R Basics and Data Types, Data Structures in R, Data Manipulation with dplyr, Graphics with ggplot2, Statistical Modeling in R |
| GE 2 | Generic Elective - II (e.g., Data Visualization) | Elective | 2 | Principles of Data Visualization, Types of Charts and Graphs, Data Storytelling, Dashboard Design, Visualization Tools (e.g., Tableau, PowerBI) |
| VAC 4 | Value Added Course - IV | Value Added Course | 1 | Critical Thinking and Reasoning, Ethical Decision-Making, Global Citizenship, Sustainable Development Goals, Societal Impact of Technology |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSC CS 301 | Data Analytics | Core | 4 | Introduction to Data Analytics, Data Preprocessing, Exploratory Data Analysis, Predictive Modeling, Data Visualization for Analytics |
| BSC CS 302 | Machine Learning | Core | 4 | Supervised Learning, Unsupervised Learning, Regression Models, Classification Algorithms, Introduction to Deep Learning |
| BSC CS 303 | Elective - II (e.g., Cyber Security) | Elective | 4 | Network Security Fundamentals, Cryptography, Web Application Security, Cyber Laws and Ethics, Ethical Hacking Concepts |
| BSC CS 304 | Elective - III (e.g., Mobile Application Development) | Elective | 4 | Android Studio Environment, UI/UX Design for Mobile, Activities and Intents, Data Storage and Retrieval, API Integration |
| BSC CS 305 | Project Work - I (Minor Project) | Project | 3 | Project Planning and Scoping, Literature Review, System Design and Architecture, Initial Implementation, Report Writing and Presentation |
| BSC CS 306 | Data Analytics & Machine Learning Lab | Lab | 3 | Python Libraries for Data Science (NumPy, Pandas), Machine Learning Model Implementation (Scikit-learn), Data Preprocessing Techniques, Model Evaluation Metrics, Visualization with Matplotlib/Seaborn |
| GE 3 | Generic Elective - III (e.g., Deep Learning) | Elective | 2 | Neural Network Architectures, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Backpropagation Algorithm, Transfer Learning |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BSC CS 307 | Elective - IV (e.g., Data Science with R) | Elective | 4 | R Programming for Data Science, Data Import and Cleaning, Statistical Modeling in R, Machine Learning with R, Report Generation with R Markdown |
| BSC CS 308 | Elective - V (e.g., Blockchain Technologies) | Elective | 4 | Cryptographic Foundations, Distributed Ledger Technologies, Consensus Mechanisms, Smart Contracts, Blockchain Applications and Use Cases |
| BSC CS 309 | Summer Internship | Summer Internship | 2 | Industry Exposure, Real-world Project Experience, Professional Skill Development, Technical Report Writing, Presentation Skills |
| BSC CS 310 | Project Work - II (Major Project) | Project | 8 | Advanced Project Management, System Development Life Cycle, Research Methodology, Innovation and Development, Deployment and Testing |
| GE 4 | Generic Elective - IV (e.g., Natural Language Processing) | Elective | 2 | Text Preprocessing and Tokenization, Word Embeddings (Word2Vec, GloVe), Sentiment Analysis, Chatbots and Virtual Assistants, Language Models |
