Industry Partners

• Deloitte Touche Tohmatsu India LLP

• Zell Education Private Limited

Aggregate of 50% marks at the Intermediate/Higher-Secondary (10+2) level from any recognized board in India with Mathematics/ Statistics as subject. 

• To provide a strong foundation in finance, economics, technology, and data analytics.
• To train students in the application of emerging technologies such as Artificial Intelligence, Blockchain, and Machine Learning in financial services.
• To develop analytical and decision-making skills using real-world data.
• To foster entrepreneurial thinking and innovation in the FinTech domain.
• To prepare students for careers across banking, financial services, consulting, analytics, and technology sectors.

• Financial Data Analyst / Business Analyst
• FinTech Product Manager / Digital Banking Specialist
• Data Scientist (Finance Domain)
• Risk Analyst / Credit Analyst
• Blockchain Developer / RegTech Specialist
• Investment Analyst / Quantitative Researcher
• Business Intelligence Professional
• Research Associate / Academic

• Industry-Academia Collaboration: Offered by KIIT Deemed to be University in collaboration with Deloitte Touche Tohmatsu India LLP and Zell Education Private Limited, ensuring strong industry relevance and practical orientation.
• Interdisciplinary Curriculum: Seamless integration of Finance, Economics, Technology, and Business Analytics aligned with global FinTech trends.
• Emerging Technology Focus: Exposure to cutting-edge domains such as Artificial Intelligence, Machine Learning, Blockchain, Big Data, Cloud Computing, and Digital Banking.
• Hands-on Analytics Training: Practical learning using industry-standard tools including Python, R, Power BI, Excel, and Tableau.
• Experiential Learning Model: Case studies, simulations, live industry projects, internships, and a final capstone project embedded in the curriculum.
• Industry Exposure & Mentorship: Expert lectures, workshops, and interactions with industry professionals facilitated through the Deloitte collaboration.
• Career-Oriented Design: Curriculum mapped to roles in FinTech, banking, consulting, analytics, risk management, and digital finance.
• Research & Higher Education Pathways: Strong analytical and conceptual foundation suitable for higher studies and research in Finance, Analytics, Economics, and Data Science.
• Ethics & Leadership Emphasis: Focus on ethical decision-making, governance, and responsible leadership in technology-driven financial systems.
• NEP 2020 Aligned: Skill-based, multidisciplinary, and flexible learning structure in line with the National Education Policy 2020.

The Bachelor of Science [B.Sc. (Hons)] in Economics with Data Analytics programme offered by the Department of Economics, School of Economics & Commerce, KIIT Deemed to be University, is a four-year undergraduate programme designed in accordance with the National Education Policy (NEP) 2020 and the UGC Curriculum and Credit Framework (CCF-UG). The programme aims to develop analytically proficient, technologically competent, and ethically responsible graduates with a strong foundation in economics, quantitative methods, and data analytics, enabling them to address contemporary economic and business challenges through evidence-based decision-making.

The rapid growth of the digital economy, artificial intelligence, big data, and financial technologies has transformed the discipline of economics. Modern economists are expected to possess not only sound theoretical knowledge but also the computational and analytical skills required to analyse complex datasets, forecast economic trends, evaluate public policies, and support strategic decision-making. In this context, the programme adopts an interdisciplinary approach by integrating economics with statistics, mathematics, computer science, and data analytics.

The curriculum combines the core principles of economics with contemporary analytical tools and technologies. In addition to foundational courses in Microeconomics, Macroeconomics, Mathematical Economics, Econometrics, Development Economics, Public Economics, International Economics, Financial Economics, and Environmental Economics, students receive rigorous training in C Programming, Data Structures, Programming with R, Python for Data Analysis, Database Management using SQL, Statistical Computing, Bayesian Data Analysis, Machine Learning, Artificial Intelligence and Business Intelligence Tools, Data Analysis using STATA, Applied Data Mining, Time Series Analysis, Big Data Analytics, Applied Panel Data Analytics, Spatial (GIS) Economic Analysis, Computational Modelling, FinTech Analytics, Risk and Portfolio Analytics, and Economic Data Visualisation using Power BI and Tableau. This multidisciplinary curriculum equips students with the knowledge and practical skills required to analyse economic and financial data using advanced statistical, econometric, and computational techniques.

The programme is guided by the educational philosophy of NEP 2020, promoting holistic development through the four pillars of education—learning to know, learning to do, learning to live together, and learning to be. It seeks to cultivate critical thinking, computational reasoning, ethical values, communication skills, innovation, and lifelong learning while fostering an interdisciplinary understanding of economics and its applications in a technology-driven world.

The pedagogy combines classroom instruction with programming laboratories, econometric modelling, statistical computing, case studies, data visualisation, research projects, internships, seminars, and industry interaction. Students gain practical exposure to widely used analytical platforms, including Python, R, SQL, STATA, SPSS, Power BI, Tableau, Microsoft Excel, and cloud-based computing environments, ensuring strong technical competence and industry readiness.

The programme prepares graduates for careers as Economic Analysts, Data Analysts, Business Analysts, Financial Analysts, Policy Analysts, Business Intelligence Analysts, Risk Analysts, FinTech Analysts, Economic Consultants, and Data Scientists, as well as for higher studies and research in Economics, Econometrics, Data Science, Business Analytics, Finance, Public Policy, and related interdisciplinary fields. By integrating economic theory with modern analytical techniques, the programme equips graduates to School of Economics & Commerce, KIIT Deemed to be University | B.Sc. (Economics with Data Analytics) Programme | Academic Year 2026– 27 contribute effectively to evidence-based policymaking, digital transformation, and sustainable economic development in an increasingly data-driven global economy.

The salient features of the B.Sc. (Economics with Data Analytics) course curriculum are:

• The programme is designed as an interdisciplinary and future-ready data-driven curriculum that integrates Economics with Data Analytics, Statistics, Econometrics, Programming, Artificial Intelligence, Machine Learning, Financial Systems, and Business Intelligence, enabling students to develop quantitative, computational, and analytical competencies for the digital economy.
• The programme is organised into several categories of courses, each carrying specific credit requirements for the different degree types:
• A 3-year UG programme requires a minimum of 120 credits; a 4-year UG (Honours) programme requires 160 credits.
• Major (Core) courses require a minimum of 60 credits for the 3-year programme and 80 credits for the 4-year programme.
• Minor Stream courses require a minimum of 24 credits for the 3-year programme and 32 credits for the 4-year programme.
• General Education Requirement (GER) includes: Multidisciplinary/Open Elective (9 credits), Ability Enhancement Courses (8 credits), Skill Enhancement Courses (9 credits), Value Added Courses (8 credits), Summer Internship & Seminar (8 credits), and Research Project/Dissertation (12 credits for Honours with Research).

Note on Course Codes: Major Core Courses (011–099); Major Discipline Specific Elective Courses (111–299); Minor and Minor Elective Courses (311–499); GER – Ability Enhancement Courses (511–599); GER – Skill Enhancement Courses incl. Internship (611–699); GER – Value Added Courses (711–799); GER – Multidisciplinary/Open Elective Courses (811–899); Lab Courses (911–999).

Multiple Entry and Exit Options (NEP 2020)

• The undergraduate programme extends over four academic years (eight semesters) with multiple entry and exit options, as follows:
•  UG Certificate*: Awarded to students who exit after Year 1 with a minimum of 40 earned credits and completion of one vocational course (4 credits) during the summer vacation. Re-entry is permitted within 3 years, with degree completion within 7 years.
• UG Diploma*: Awarded to students who exit after Year 2 with a minimum of 80 earned credits and completion of one vocational course (4 credits) during the summer vacation. Re-entry is permitted within 3 years, with degree completion within 7 years.
• 3-Year UG Degree: Awarded on successful completion of three years, subject to fulfilment of the required credit obligations.
• 4-Year UG Degree (Honours): Awarded on completion of the four-year programme, subject to fulfilment of the full credit requirement.
• 4-Year UG Degree (Honours with Research): Available to students with a CGPA ≥ 7.5 in the first six semesters who undertake a research project/dissertation (12 credits) in the final year under faculty guidance.