Overview
The Bachelor of Science (BSc) with a specialization in Data Science is a 3 years innovative program designed for students passionate about data, analytics, and intelligent decision-making. With the exponential growth of data across industries, skilled data science professionals are in high demand. This programme provides a strong foundation in mathematics, statistics, and computer science, along with specialized training in data analysis, machine learning, and data visualization to transform complex data into meaningful insights and drive data-driven innovation.
What You’ll Learn
This specialized BSc program delves into topics such as
- Data Science
- Statistics
- Mathematics
- Natural Language Processing
- Machine learning
- Deep learning and Big data analytics
Empowering students to apply data-driven solutions in areas including healthcare analytics, financial modeling, social media analysis, business intelligence, and scientific research.
Practical Skills
With a focus on practical learning and real-world applications, graduates of the BSc in Data Science program emerge as skilled professionals capable of analyzing complex datasets, building predictive models, deriving actionable insights, and driving data-driven decision-making in an increasingly digital and data-centric world.
Career Pathways
- Data Analyst
- Business Intelligence (BI) Analyst
- Reporting Analyst
- Market Research Analyst
- Machine Learning Engineer
- AI Developer / AI Engineer
- Deep Learning Specialist
- NLP (Natural Language Processing) Engineer
- Data Visualization Specialist
- Predictive Analytics Specialist
- Research Analyst (Data Science/AI)
- IoT Data Analyst
- Data Engineer
- Big Data Developer
- Database Administrator
- Cloud Data Engineer
Programme Education Objectives
| PEOs | Programme Educational Objectives |
|---|---|
| PEO1 | To instill an in-depth understanding of the key technologies in Data Science. |
| PEO2 | To provide an understanding of data and train students to design integrated solutions to problems by applying principles of Data Science. |
| PEO3 | To impart strong core training both theoretically and practically to create adept data scientist. |
| PEO4 | To provide an exposure to real world problems in order to adapt easily to the industry demands. |
| PEO5 | To encourage students to practice continuous learning in order to achieve professional and personal excellence. |
Programme Outcomes (POs)
| POs | Programme Outcomes |
|---|---|
| PO1 | Proficiently handle and manipulate data by applying mathematics, statistics and computing techniques to clean, transform, and preprocess data for analysis. |
| PO2 | Apply statistical, mathematical and computing knowledge as well as employ cutting edge tools and technologies to analyze, drive insights and forecast from large datasets. |
| PO3 | Demonstrate effective communication and leadership abilities while collaborating within interdisciplinary teams, utilizing domain expertise to address real-world challenges through data-driven methodologies grounded in legal and ethical standards. |
| PO4 | Pursue quality research in Data Science by applying Quantitative modeling and Data analysis techniques to solve real-world problems, communicate findings, and effectively present results. |
| PO5 | Continuously engage in lifelong learning to adapt to evolving technologies, striving for professional excellence, and fostering success as entrepreneurs or professionals who make meaningful contributions to society. |
Programme Structure
| Semester I | Semester II | Semester III | Semester IV | Semester V | Semester VI |
|---|---|---|---|---|---|
| Language I – Kannada: Saahitya Sangama – I, Hindi: Gadya Sampada, Additional English: Translations selected from South India | Language I – Kannada: Saahitya Sangama –II, Hindi: Gadya Sampada, Additional English: Translations selected from South India | Language I – Kannada: Saahitya Sinchana –I, Hindi: Kavya Pankaj, Additional English: Translations selected from Central and West India | Kannada: Saahitya Sinchana - II / Hindi: Khand Kavya-Nahush / Additional English: Translations selected from North India | Software Project Management | Big Data Analytics |
| Language II – Generic English: Readings from Literature and Language Skills | Language II – Generic English: Readings from Literature and Language Skills | Language II – Generic English: Perceptions of Literature and Language Skills | Generic English: Insights from Literature and Language Skills | Deep Learning | Natural Language Processing |
| Descriptive Statistics | Mathematical foundations in Data Science-I | Mathematical foundations in Data Science-II | Probability and Inferential Statistics | Design and Analysis of Algorithms) | NoSQL Lab |
| Essentials of Data Science | Database Management System | Operating System and Unix Programming | Machine Learning | Deep Learning Lab | Natural Language Processing Lab |
| Python Programming | Data Structures | Artificial Intelligence | R programming | Software Project management Lab | Project Lab |
| Data Analysis and Visualization Lab | Database Management System Lab | Unix Lab | Machine Learning Lab | SEC: Aptitude and Reasoning | SEC: Professional Business Communication |
| Python Programming Lab | Data Structures Lab | Artificial Intelligence Lab | R Programming Lab | - | - |
| Constitution of India | Environmental Studies | Elective I | Elective II | - | - |
| - | - | - | Constitution Moral Values | - | - |
Value Added Courses (VACs)
| S.No. | Name of the VAC |
|---|---|
| 1 | Advanced Deep Learning |
| 2 | Mobile Application Development |
| 3 | 2D Animation |
| 4 | Hands on cloud computing on AWS |
| 5 | Cyber Security |
| 6 | Data Analysis using Spreadsheet |
| 7 | Ethical hacking |
| 8 | Web Application development-Back end |
Eligibility Criteria
Candidates who have completed two-years pre-university programme of Karnataka State or its equivalent of any state or country or a candidate who has passed JODC/three-year diploma in engineering (Government of Karnataka) are eligible for admission into this programme.
- Pass in 10 + 2 are eligible for BSc (Data Science) admission.
