MBA in Business Analytics (KPMG) - Deep Learning for Business Applications

The MBA in Business Analytics, in collaboration with KPMG at UPES, is a focused programme built to develop advanced analytical capability and data-driven decision-making for today’s data-centric business environment. It blends core management education with advanced analytics concepts, tools and industry practices, and uses classroom learning, hands-on lab sessions, live industry projects, internships and expert interactions to build practical exposure to real business challenges. KPMG strengthens industry relevance through mentorship, workshops, case studies and capstone projects aligned with current analytics requirements.

Building on this foundation, the Deep Learning for Business Applications specialisation focuses on advanced techniques that help organisations uncover complex patterns from large and unstructured datasets. It introduces neural networks, deep learning architectures and predictive models for business decision-making, supporting forecasting, risk analysis, customer analytics, recommendation systems and operational optimisation. Together, the programme and specialisation develop strategic thinking, structured problem-solving, and the application of advanced AI techniques to strategic and operational business challenges.

• Students learn deep learning concepts through application-focused learning.
• Learners gain hands-on experience with predictive and classification models.
• The curriculum takes a business-centric approach to advanced AI methodologies.
• Students work with real-world datasets and business problems for practical context.
• The programme emphasises interpretability and managerial decision-making.
• Use cases span finance, marketing, operations and supply chains.
• The learning remains strongly aligned with analytics and consulting career paths.

Deep learning is a key driver of advanced analytics and intelligent automation, and organisations increasingly rely on it to improve accuracy, efficiency and scalability in decision-making. This is reflected in the growing adoption of AI-driven predictive analytics, deeper use in risk management and forecasting, automation of insights generation and anomaly detection, and expansion of AI applications across BFSI, retail, logistics and healthcare—alongside rising demand for professionals who can translate AI insights into business actions. Job roles include:

• Business Analytics Professional
• Data Analyst / Advanced Analytics Analyst
• Decision Science Analyst
• Risk Analytics Consultant
• AI & Analytics Consultant
• Business Intelligence Specialist

The specialisation strengthens placement prospects by preparing students for analytics and consulting roles that require advanced predictive modelling skills. Students benefit from structured placement preparation, industry projects, and exposure to analytics-driven business functions, supported by the programme’s KPMG-linked mentorship and applied learning approach.

Click here for detailed Fee Structure.

Interested students must meet the minimum eligibility criteria for the MBA in Business Analytics with specialisation in Deep Learning for Business Applications, in collaboration with KPMG, as stated below: Minimum 50% marks in Class X, XII and Graduation. Graduation From a recognized University in any stream.

The selection criteria for students who wish to pursue MBA in Business Analytics with specialisation in Generative AI for Business, in collaboration with KPMG, offered by UPES depend on the individual's performance in UPESMET / National Level Exams/ CUET followed by Personal Interview.

Non-Examination Pathways:

Students with a minimum eligible MAT / CMAT 2026 score of 70 percentile will be exempted from the UPES Management Entrance Test (UPESMET) and will be called only for the Group Discussion and Personal Interview, subject to qualification.

A valid score of 50 percentile or above in CAT 2025 / XAT 2026, a GMAT score of 400 or above, or a score of 120 or above in NMAT 2025–26 will also be accepted.

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