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MCA in Data Science at Invertis University
Bareilly, Uttar Pradesh
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About the Specialization
What is Data Science at Invertis University Bareilly?
This MCA program at Invertis University, with an elective specialization track in Data Science, focuses on equipping students with advanced computational skills and analytical capabilities essential for modern data-driven roles. It builds a strong foundation in core computer applications while allowing students to delve into specialized areas like Data Science, Machine Learning, and Big Data Analytics, catering to the burgeoning demand in the Indian technology sector for skilled data professionals.
Who Should Apply?
This program is ideal for BCA/B.Sc. IT graduates seeking advanced qualifications, working professionals looking to transition into data analytics, or career changers aiming to leverage computational skills in the data domain. It caters to those with a foundational understanding of programming and mathematics who are eager to explore complex data challenges and contribute to India''''s digital transformation.
Why Choose This Course?
Graduates of this program can expect to pursue rewarding career paths in India as Data Analysts, Data Scientists, Machine Learning Engineers, or Big Data Specialists. Entry-level salaries typically range from INR 4-7 LPA, with experienced professionals earning upwards of INR 10-25 LPA. The program aligns with industry demands, preparing students for roles in IT services, e-commerce, banking, and healthcare sectors across India.
Student Success Practices
Foundation Stage
Master Programming and Data Fundamentals- (Semester 1-2)
Dedicate significant time to thoroughly understand core programming concepts in Python and Java, alongside robust data structures and database management. Actively practice coding on platforms like HackerRank or LeetCode to build problem-solving skills and develop a strong logical foundation, which is crucial for advanced data science topics.
Tools & Resources
Python IDE (e.g., VS Code), Java JDK, MySQL/PostgreSQL, HackerRank, GeeksforGeeks, NPTEL courses on Data Structures
Career Connection
A strong foundation in programming and data structures is the bedrock for any data science role, ensuring efficient algorithm development and database handling, directly impacting technical interview performance and on-the-job effectiveness.
Build Strong Mathematical and Statistical Acumen- (Semester 1-2)
Reinforce concepts from ''''Mathematical Foundations of Computer Science'''' and proactively study introductory statistics. Understanding probability, linear algebra, and calculus is paramount for grasping machine learning algorithms. Utilize online resources or textbooks for additional practice and conceptual clarity beyond classroom lectures.
Tools & Resources
Khan Academy for Calculus/Linear Algebra, MIT OpenCourseWare for Probability/Statistics, NCERT Mathematics textbooks, Reference books on Discrete Mathematics
Career Connection
Robust mathematical understanding enables students to comprehend the theoretical underpinnings of data science models, which is essential for innovation, debugging complex algorithms, and excelling in quantitative roles within analytics firms.
Engage in Peer Learning and Group Projects- (Semester 1-2)
Form study groups to discuss complex topics, share knowledge, and collaborate on small programming assignments or mini-projects. Active participation in group discussions on core computer science subjects not only deepens understanding but also develops teamwork and communication skills, vital for future industry roles.
Tools & Resources
Google Docs/Drive for collaboration, GitHub for code sharing, Discord/WhatsApp for group communication, University library resources
Career Connection
Collaborative skills honed through peer learning are highly valued in corporate environments, preparing students for team-based project execution and fostering a supportive learning ecosystem that can lead to shared career opportunities.
Intermediate Stage
Specialize through Electives and Practical Application- (Semester 3)
Dive deep into the ''''Data Science'''' elective by undertaking hands-on projects, utilizing real-world datasets. Learn popular data science libraries in Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn). Focus on practical implementation of data preprocessing, exploratory data analysis, and basic machine learning models. Participate in hackathons.
Tools & Resources
Kaggle for datasets and competitions, Jupyter Notebooks, Anaconda Distribution, Coursera/edX courses on Data Science, Google Colab
Career Connection
Practical application of data science concepts during electives provides a portfolio of projects, demonstrating applied skills to potential employers and preparing students for entry-level data science and analytics roles.
Seek Early Industry Exposure through Internships- (Semester 3 (4-6 weeks during semester break))
Actively pursue the mandatory industrial training/internship in a company focused on data analytics, software development, or IT services. This provides invaluable real-world experience, helps bridge academic knowledge with industry demands, and offers networking opportunities. Focus on gaining experience in data manipulation, basic modeling, or data visualization.
Tools & Resources
LinkedIn, Internshala, Naukri.com, University Placement Cell, Industry mentorship programs
Career Connection
Internships are critical for securing full-time placements. They provide practical skills, industry contacts, and often lead to pre-placement offers, significantly boosting career prospects in the competitive Indian job market.
Develop Presentation and Technical Communication Skills- (Semester 3)
Utilize the ''''Seminar'''' course to refine public speaking, technical report writing, and presentation delivery. Practice articulating complex technical ideas clearly and concisely. This is crucial for conveying findings from data analysis projects to both technical and non-technical audiences, a key skill for a data scientist.
Tools & Resources
Microsoft PowerPoint/Google Slides, Grammarly, Toastmasters International (local chapters), Online tutorials on technical writing
Career Connection
Effective communication skills are highly sought after by employers, enabling graduates to present data insights, collaborate with cross-functional teams, and influence decision-making within organizations.
Advanced Stage
Master Advanced Data Science Techniques- (Semester 4)
Deepen your expertise by focusing on ''''Machine Learning'''' and ''''Big Data Analytics'''' electives. Implement various ML algorithms, understand model evaluation metrics, and explore distributed computing frameworks like Hadoop/Spark. Participate in advanced data challenges and explore advanced topics like deep learning if time permits.
Tools & Resources
TensorFlow/Keras/PyTorch, Apache Hadoop/Spark, AWS/Azure/GCP free tiers for cloud computing, DataCamp/Udemy courses on advanced ML
Career Connection
Advanced skills in Machine Learning and Big Data make graduates highly competitive for specialized roles in AI, advanced analytics, and big data engineering, commanding higher salaries and greater responsibilities in the Indian tech landscape.
Execute a Capstone Data Science Project- (Semester 4)
Undertake a ''''Major Project'''' that applies the acquired Data Science, Machine Learning, or Big Data Analytics skills to solve a significant real-world problem. Focus on a complete project lifecycle from problem definition, data collection, model building, to deployment. This project will be a centerpiece of your portfolio.
Tools & Resources
Specific industry datasets, Version control (Git/GitHub), Project management tools (Trello/Asana), Mentorship from faculty or industry experts
Career Connection
A strong capstone project demonstrates practical problem-solving abilities and a comprehensive understanding of the specialization, making graduates highly attractive to recruiters and often leading directly to job offers.
Intensive Placement Preparation and Networking- (Semester 4)
Actively engage in comprehensive placement preparation, including mock interviews (technical and HR), aptitude test practice, and resume building. Network with alumni and industry professionals through LinkedIn or university events. Understand company-specific hiring processes for data science roles in India and tailor your application accordingly.
Tools & Resources
Placement cell workshops, Glassdoor for company insights, LinkedIn for networking, Online aptitude test platforms, Mock interview tools
Career Connection
Strategic placement preparation maximizes the chances of securing desirable positions in leading Indian and global companies. Networking can open doors to opportunities not advertised publicly, accelerating career entry and growth.
Program Structure and Curriculum
Eligibility:
- BCA/B.Sc. (Computer Science/IT)/B.Voc. (Software Development/IT) or equivalent degree with minimum 50% marks in aggregate. OR B.Tech./B.E. (CSE/IT) or equivalent with minimum 50% marks in aggregate. OR B.Sc./B.Com./B.A. with Mathematics as one of the subjects at 10+2 level or graduation level with minimum 50% marks in aggregate and obtained at least 50% marks in the entrance examination conducted by Invertis University, Bareilly.
Duration: 2 years (4 semesters)
Credits: 86 Credits
Assessment: Internal: 30% (for theory subjects), 50% (for practical subjects), External: 70% (for theory subjects), 50% (for practical subjects)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MCA-101 | Mathematical Foundations of Computer Science | Core | 4 | Set Theory and Logic, Relations and Functions, Graph Theory, Algebraic Structures, Combinatorics |
| MCA-102 | Data Structures | Core | 4 | Arrays and Pointers, Stacks and Queues, Linked Lists, Trees and Graphs, Sorting and Searching Algorithms |
| MCA-103 | Operating System | Core | 4 | Process Management, CPU Scheduling, Memory Management, File Systems, Deadlocks and Concurrency Control |
| MCA-104 | Object Oriented Programming using Python | Core | 4 | Python Fundamentals, Object-Oriented Concepts, Classes and Objects, Inheritance and Polymorphism, Exception Handling, File I/O |
| MCA-105 | Data Structures Lab | Lab | 1 | Implementation of Stacks, Queue Operations, Linked List Manipulations, Tree Traversal Algorithms, Sorting and Searching Practical |
| MCA-106 | Object Oriented Programming Lab (using Python) | Lab | 1 | Python Programming Basics, OOP Concepts Implementation, File Handling in Python, GUI Programming with Tkinter, Database Connectivity |
| MCA-107 | Professional Communication | Core | 4 | Fundamentals of Communication, Business Correspondence, Presentation Skills, Group Discussion Techniques, Interview Preparation |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MCA-201 | Computer Networks | Core | 4 | Network Models (OSI, TCP/IP), Data Link Layer, Network Layer Protocols, Transport Layer Services, Network Security Basics |
| MCA-202 | Database Management System | Core | 4 | DBMS Architecture, ER Model and Relational Model, SQL Queries and Constraints, Normalization, Transaction Management and Concurrency Control |
| MCA-203 | Design & Analysis of Algorithms | Core | 4 | Algorithmic Strategies, Time and Space Complexity, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms |
| MCA-204 | Web Technology | Core | 4 | HTML5 and CSS3, JavaScript Fundamentals, Server-Side Scripting (PHP), Web Servers and Databases, AJAX and Responsive Design |
| MCA-205 | Database Management System Lab | Lab | 1 | SQL Commands and Functions, PL/SQL Programming, Database Design and Implementation, Trigger and Cursor Implementation, Report Generation Tools |
| MCA-206 | Web Technology Lab | Lab | 1 | HTML and CSS Website Development, JavaScript Dynamic Pages, PHP Scripting, Database Connectivity with MySQL, Web Application Project |
| MCA-207 | Object Oriented Programming using Java | Core | 4 | Java Basics, OOPs in Java, Inheritance, Polymorphism, Exception Handling, Multithreading, AWT and Swings |
| MCA-208 | Object Oriented Programming Lab (using Java) | Lab | 1 | Java Program Development, OOP Principles Implementation, File I/O and Networking in Java, GUI Applications with Java, Database Connectivity (JDBC) |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MCA-301 | Software Engineering | Core | 4 | Software Development Life Cycle, Software Requirements Engineering, Software Design Principles, Software Testing Strategies, Software Project Management |
| MCA-302 | Cloud Computing | Core | 4 | Cloud Computing Concepts, Service Models (IaaS, PaaS, SaaS), Deployment Models, Virtualization, Cloud Security and Management |
| MCA-303 | Advance Java Programming | Core | 4 | Servlets and JSP, JDBC for Database Connectivity, Java Beans, Web Services (RESTful, SOAP), Spring Framework Introduction |
| MCA-304 | Advance Java Programming Lab | Lab | 1 | Web Application Development using Servlets, JSP Page Creation, Database Integration with JDBC, Spring Boot Application Development, RESTful API Implementation |
| MCA-E-305 | Data Science | Elective | 4 | Introduction to Data Science, Data Collection and Preprocessing, Exploratory Data Analysis, Statistical Inference and Hypothesis Testing, Introduction to Machine Learning, Data Visualization Techniques |
| MCA-306 | Industrial Training / Internship (4-6 Weeks) | Project/Internship | 3 | Industry Exposure, Practical Skill Development, Project Implementation, Technical Report Writing, Professional Presentation |
| MCA-307 | Seminar | Core | 0 | Technical Topic Research, Presentation Skills, Public Speaking, Critical Analysis, Question and Answer Sessions |
| MCA-E-MOOC1 | MOOCs-I (Elective) | Elective | 2 | Self-paced learning platform usage, Specialized topic of choice, Online course completion, Certificate acquisition, Independent study |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MCA-401 | Mobile Application Development | Core | 4 | Android/iOS Architecture, UI/UX Design for Mobile, Data Storage in Mobile Apps, Networking and API Integration, Mobile Security Considerations |
| MCA-402 | Mobile Application Development Lab | Lab | 1 | Android App Development Tools, User Interface Implementation, Database Integration in Android, API Consumption in Mobile Apps, Testing and Debugging Mobile Applications |
| MCA-E-403 | Machine Learning | Elective | 4 | Supervised Learning Algorithms, Unsupervised Learning Algorithms, Regression and Classification, Clustering Techniques, Introduction to Neural Networks and Deep Learning |
| MCA-E-404 | Big Data Analytics | Elective | 4 | Introduction to Big Data, Hadoop Ecosystem (HDFS, MapReduce), Apache Spark for Data Processing, NoSQL Databases, Data Warehousing and Data Lake Concepts |
| MCA-405 | Major Project | Project | 8 | Problem Identification and Scope Definition, System Design and Architecture, Implementation and Coding, Testing, Debugging and Quality Assurance, Documentation and Final Presentation |
| MCA-E-MOOC2 | MOOCs-II (Elective) | Elective | 2 | Advanced self-paced learning, Industry-specific certifications, Online project work, Skill enhancement for niche areas, Global knowledge access |
