B. Sc. (Data Science & Artificial Intelligence)
Learn data science, artificial intelligence, machine learning, analytics, and programming to solve real-world business challenges effectively.
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BSC Program Structure
Program Features
Highlights:
- The Bachelor of Science (B.Sc.) in Data Science & Artificial Intelligence is an undergraduate program focused on data-driven technologies and intelligent systems.
- The program equips students with strong foundations in Data Science, Artificial Intelligence, Machine Learning, Python Programming, and Data Analytics.
- Students gain hands-on experience with data visualization, predictive modeling, cloud computing, and AI applications.
- The curriculum combines theoretical concepts with practical projects to prepare students for industry and research opportunities.
Outcomes:
- Build strong analytical and problem-solving skills using data-driven approaches.
- Develop expertise in machine learning, artificial intelligence, and statistical analysis.
- Learn to collect, process, visualize, and interpret complex datasets for informed decision-making.
- Gain proficiency in programming languages and AI tools used in modern industries.
- Apply AI and data science techniques to solve real-world business and technological challenges.
- Prepare for careers in Data Science, AI, Machine Learning, Business Analytics, and related technology fields.
Career Options
With the right guidance and practical training, you can build a successful career in the rapidly growing fields of Data Science and Artificial Intelligence. Some of the career opportunities after completing the program are:
Data Scientist
Collect, analyze, and interpret large datasets to generate valuable insights and support business decision-making.- Machine Learning Engineer
Design, develop, and deploy machine learning models that automate tasks and improve business processes. - Artificial Intelligence Engineer
Build intelligent systems using AI technologies such as natural language processing, computer vision, and deep learning. - Data Analyst
Transform raw data into meaningful reports and dashboards to help organizations make informed strategic decisions - AI Research Associate
Work on developing innovative AI solutions, conducting research, and improving intelligent algorithms for real-world applications.
Eligibility & Programs
- 10+2 (Higher Secondary) or equivalent from a recognized board
- Mathematics/Statistics/Computer Science preferred (as per university norms)
- Minimum qualifying marks as prescribed by the university
Apply now to start your admission process and secure your seat in your preferred program today.
Course Structure
Semester - 1
Subjects
- C Programming
- Mathematics
- Computer & Network Fundamentals
- Operating System
- English
- Advanced Excel
- Lokmanya Bal Gangadhar Tilak- Maker of Modern India
- C Programming (PR)
Semester - 2
Subjects
- Python Programming
- Statistics
- Structured System Analysis and Design
- Data Mining
- Communication Skills
- Moral Values
- Indian Knowledge System (IKS)- Generic
- Python Programming (PR)
Semester - 3
Subjects
- Advanced Web Designing
- Database Management System (DBMS)
- Environmental Studies
- Exploratory Data Analysis
- Lokmanya B.G Tilak -The Visionary
- Machine Learning Foundation
- Data Visualisation
- Â Data Visualisation (PR)
- Advanced Web Designing (PR)
Semester - 4
Subjects
- Advanced Database Management System
- Java Programming
- Power Bi
- Unified Modeling Language(UML)
- Bigdata Technologies
- Soft Skills
- Indian Knowledge System-Computer Science- Discipline Specific
- Java Programming (PR)
- Advanced Database Management System (PR)
Semester - 5
Subjects
- Machine Learning – I
- Natural Language Processing
- Internet of Things- IoT
- Introduction to Artificial Intelligence
- Business Communication
- Business Forcasting
- Digital Marketing with Data Analytics
- Management Information System
- Machine Learning (PR)
- Natural Language Processing PR)
Semester - 6
Subjects
- Machine Learning – II
- Deep Learning
- Cloud Technology & Security
- Project
- Internship
- Machine Learning – II (PR)
- Deep Learning (PR)