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Data Science & AI - (Academic–Industry Partner: EY India)
Program details
The BBA in Data Science & Artificial Intelligence, offered in academic partnership with EY India, is an industry-integrated undergraduate program designed to develop business professionals skilled in data-driven decision-making, analytics, and AI-enabled strategy.
The program blends core business education with applied data science and artificial intelligence, preparing students to work confidently with data, analytics tools, and AI frameworks in real business contexts. Of the nearly 135 academic credits, 36 credits (10 specialised modules, ~360 hours) are designed and delivered by EY experts, ensuring strong industry relevance and practical exposure.
Students gain hands-on experience in business analytics, predictive modelling, machine learning for managers, data visualisation, and AI strategy, supported by real-world case studies and tool-based learning.
Program Highlights
- Industry-integrated curriculum with EY-designed and EY-delivered specialisation modules
- Strong business foundation combined with data analytics, machine learning, and AI applications
- Hands-on training in tools such as Excel, Python, Power BI, Qlik Sense, and BI platforms
- Focus on business-centric analytics, data storytelling, and decision support
- Exposure to AI strategy, implementation, and responsible AI practices
- Real-world case studies and practical assignments aligned with industry needs
Industry Trends & Career Opportunities
Business decision-making is increasingly shaped by data, analytics, and artificial intelligence, making analytical capability a core managerial skill across industries. Organisations are moving beyond descriptive reporting to predictive and AI-driven insights to improve performance in marketing, finance, operations, and strategy. Technologies such as machine learning, intelligent automation, and Generative AI are accelerating digital transformation, while growing regulatory focus on data governance, ethics, and responsible AI is redefining how data is used in business. This evolving landscape is driving strong demand for professionals who can combine business understanding with analytics and AI expertise, positioning graduates of this program for high relevance in the digital economy.
Graduates are prepared for roles such as Business Analyst, Data Analyst, Business Intelligence (BI) Analyst, Marketing & Customer Analytics Specialist, AI Business or Strategy Associate, Operations & Supply Chain Analytics Analyst, and Risk, Compliance & Responsible AI Analyst. Career opportunities span consulting, IT services, BFSI, retail, e-commerce, healthcare, manufacturing, FMCG, telecom, analytics firms, and large enterprises, offering diverse and scalable career pathways.
Placements
The BBA in Data Science & Artificial Intelligence offers strong placement prospects supported by its industry-integrated curriculum and EY-led specialisation modules. Students graduate with practical exposure to business analytics, data visualisation, predictive modelling, and AI strategy, making them well-prepared for entry-level analytics and strategy roles across sectors.
Graduates are recruited by consulting firms, IT and analytics companies, BFSI organisations, consumer-facing enterprises, and large corporates for roles aligned to business analytics, intelligence, digital strategy, and AI-enabled decision support, with clear pathways for growth into advanced analytics, consulting, and leadership roles.
Fee Structure
Click here for detailed Fee Structure.
Curriculum
Semester 1
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Principles and Practices of Management | 3 | 0 | 0 | 3 |
| Business Economics 1 | 3 | 0 | 0 | 3 |
| Business Mathematics | 3 | 0 | 0 | 3 |
| Business Accounting | 3 | 0 | 0 | 3 |
| Business Communication | 3 | 0 | 0 | 3 |
| Organizational Behavior | 3 | 0 | 0 | 3 |
| Business Environment | 2 | 0 | 0 | 2 |
| Living Conversations | 2 | 0 | 0 | 2 |
| Environment Sustainability & Climate Change (Theory) | 2 | 0 | 0 | 2 |
| TOTAL | 24 |
Semester 2
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Business Economics 2 | 3 | 0 | 0 | 3 |
| Business Statistics | 3 | 0 | 0 | 3 |
| Financial Management | 3 | 0 | 0 | 3 |
| Marketing Management | 3 | 0 | 0 | 3 |
| Technologies of the future | 2 | 0 | 0 | 2 |
| Human Resource Management | 3 | 0 | 0 | 3 |
| Operations Management | 3 | 0 | 0 | 3 |
| Critical Thinking & Writing | 2 | 0 | 0 | 2 |
| Environment Sustainability & Climate Change (living lab) | 0 | 0 | 4 | 2 |
| Community Engagement and Social Internship | 2 | 0 | 0 | 2 |
| TOTAL | 26 |
Semester 3
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Spreadsheet Modelling | 2 | 0 | 2 | 3 |
| Data Environment | 3 | 0 | 0 | 3 |
| Business Ethics and CSR | 2 | 0 | 0 | 2 |
| Global Context of Business | 1 | 0 | 0 | 1 |
| Data Management | 2 | 0 | 2 | 3 |
| Research Methodology & Report Writing | 3 | 0 | 0 | 3 |
| Consumer Behaviour & Market Research | 3 | 0 | 0 | 3 |
| Minor/Exploratory I | 3 | 0 | 0 | 3 |
| Meta 101 | 1 | 0 | 0 | 1 |
| Working with Data | 2 | 0 | 0 | 2 |
| TOTAL | 24 |
Semester 4
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Web Analytics | 2 | 0 | 2 | 3 |
| Advanced Statistics | 3 | 0 | 0 | 3 |
| Specialization Paper I (Specialization 1: Programing for Analytics, Course: Overview of Programing for Analytics 2: Big Data Analytics and Mining, Course: Big Data Analytics) | 3 | 0 | 0 | 3 |
| Industrial Visit | 0 | 0 | 2 | 1 |
| Minor/Exploratory II | 3 | 0 | 0 | 3 |
| Minor/Exploratory III | 3 | 0 | 0 | 3 |
| Environmental, Social and Governance | 3 | 0 | 0 | 3 |
| Business Analytics | 2 | 0 | 2 | 3 |
| Design Thinking | 2 | 0 | 0 | 2 |
| TOTAL | 24 |
Semester 5
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Text Mining | 2 | 0 | 2 | 3 |
| Specialisation Paper II (Speacialization 1: Programing for Analyitcs, Course: Data Visualization 2: Big Data Analytics and Mining, Course: Data Mining) | 3 | 0 | 0 | 3 |
| Business Intelligence | 2 | 0 | 2 | 3 |
| Project Management | 3 | 0 | 0 | 3 |
| Minor/Exploratory IV | 3 | 0 | 0 | 3 |
| Minor/Exploratory V | 3 | 0 | 0 | 3 |
| Dissertation I | 0 | 0 | 0 | 2 |
| Summer Internship | 0 | 0 | 0 | 2 |
| Predictive Modeling | 2 | 0 | 2 | 3 |
| Essentials of Strategic Management | 3 | 0 | 0 | 3 |
| Leadership and Teamwork | 2 | 0 | 0 | 2 |
| TOTAL | 30 |
Semester 6
| Course | L | T | P | Credit |
|---|---|---|---|---|
| Data Preparation | 3 | 0 | 0 | 3 |
| Dissertation II | 0 | 0 | 0 | 4 |
| Minor/Exploratory VI | 3 | 0 | 0 | 3 |
| Start your Start-up | 2 | 0 | 0 | 2 |
| TOTAL | 12 |
Eligibility
- 10+2 in any stream (Commerce / Science / Humanities)
- Basic mathematics at the school level
- No prior programming or analytics experience required
Selection Criteria
- Academic performance in 10+2
- University-level aptitude or entrance assessment (as applicable)
- Personal interview (if required by university norms)