MBA in Business Analytics

Programme Overview

The curriculum of the online MBA in Business Analytics features two parallel tracks - Business Management and Analytics. The curriculum includes thirteen courses on business management, eight courses on statistics and analytics techniques, five electives, and Experiential projects.

Each course will include some pre-recorded instructor videos, reading material, and practice questions. This will be accompanied with weekly assessments, hands-on assignments, and project work (often in groups) to ensure you will achieve all course-learning objectives. You will have the opportunity to interact with faculty in at least three live sessions per course, where you may seek feedback and clarification. The programme recognises 12 credits for the following certifications in the Term 2 and Term 3 electives: -

• Google Data Analytics Professional Certificate

• IBM Data Analyst Professional Certificate

• IBM Data Science Professional Certificate

• Fractal Data Science Professional Certificate

In addition to these 4 Credit based Industry certifications, enrolled learners will receive a Career Stack License wherein they complete these certifications during their degree, as well. Additionally, enrolled learners will have access to 45 other industry certifications listed here, which can be pursued without credit recognition.

Curriculum

The curriculum of the online MBA in Business Analytics is organised along two verticals—business management and analytics, and an engaging mix of both core and elective courses.

The curriculum now includes two cutting-edge courses designed by globally recognized faculty:

• Generative AI for Business Strategy & Innovation: Learn to create AI-powered business insights, dashboards, and narratives that tell the story behind the data without writing code.

• AI Tools for Decision-Making and Productivity: Harness the power of AI tools to enhance decision-making, automate tasks, and significantly boost personal and team productivity.

Generative AI for Business Strategy & Innovation

Generative AI for Business Strategy & Innovation equips learners to use open-source AI and analytics tools to create decision-ready narratives, build interactive insights, and implement responsible AI workflows that accelerate strategic decision-making and innovation.

This course  explores how leaders can use generative AI and open-source analytics tools to create faster, clearer, and more actionable business insights. Learners move from traditional BI to AI-augmented analytics through hands-on work in Python-based environments (Jupyter/Colab) and open NLP tooling.

The course emphasizes automated data storytelling, conversational exploration (“chat with your data”), and AI-assisted reporting that delivers executive-ready narratives and dashboards.

Students apply open generative models for summarization, sentiment analysis, entity extraction, and insight generation across structured and unstructured business datasets.

Advanced modules introduce strategic analytics (causal reasoning, counterfactuals, synthetic controls), probabilistic forecasting with modern time-series model approaches, multimodal analytics, and diagnostic workflows for anomaly detection and root-cause explanation.

The course closes with governance and implementation: measuring ROI, change management, and building responsible insight pipelines with verification, audit trails, and human-in-the-loop oversight—so graduates can lead AI-enabled decision systems across the enterprise.

Build the ability to:

• Explain what’s happening in the business—and what to do next using AI-generated narratives and reporting flows

• Explore data conversationally (“chat with your CSV”) to accelerate insight discovery

• Move from descriptive to strategic analytics with causal thinking, counterfactuals, and scenario modeling

• Forecast with confidence, using probabilistic predictions and executive-friendly explanations

• Operationalize responsible AI analytics, including governance, hallucination mitigation, and bias checks

By the end of the course, learners will be able to:

• Turn raw business data into boardroom-ready narratives (clear “what/so what/now what” reporting).

• Build interactive dashboards and insight experiences using open-source tool .

• Use conversational analytics workflows to explore datasets efficiently and communicate findings clearly.

• Apply open generative AI for summarization and business reporting (briefs, insight notes, decision memos).

• Extract strategic signals from text data (sentiment, themes, entities) from reviews, feedback, and documents.

• Create scenario and “what-if” analyses using causal reasoning concepts and counterfactual thinking.

• Develop probabilistic forecasts with explanations (confidence intervals + narrative rationale).

• Implement responsible GenAI governance: reduce hallucinations, detect bias, and design verification workflows.

AI Tools for Decision-Making and Productivity

AI Tools for Decision-Making and Productivity prepares students to become AI-enabled business leaders who can design intelligent workflows, extract actionable insights from data, and responsibly deploy generative AI to create competitive advantage.

AI Tools for Decision-Making and Productivity is a hands-on course that prepares MBA learners to use modern generative AI tools—especially large language models (LLMs) and intelligent workflows—to operate and decide more efficiently.

Learners will begin with a practical understanding of what GenAI can (and can’t) do in business, then build skills in prompt engineering to reliably generate high-quality outputs for communication, reporting, and marketing.

The course moves from individual productivity to team and organizational impact: using AI-enabled workspaces for documentation and project management, applying AI analytics tools for rapid insight generation from structured and unstructured data, and designing automated workflows using no-code integration platforms (e.g., Zapier/Make).

Learners will also explore agentic AI systems and conclude with essential governance topics—privacy, bias, hallucinations, and acceptable-use practices—so they can deploy AI responsibly in real organizations. The course culminates in a capstone-style workflow and dashboard that demonstrates measurable productivity and decision-making value.

Organizations are rapidly integrating tools like ChatGPT, Gemini, Copilot, and AI-powered workflow systems — but most professionals lack structured training on how to use them strategically, responsibly, and at scale.

Build the ability to:

• Translate AI capabilities into real business outcomes

• Automate repetitive workflows and decision processes

• Extract insights from complex structured and unstructured data

• Build AI-enabled systems — without writing code

• Lead AI adoption responsibly within organizations

By the end of the course, learners will be able to:

• Interpret and communicate business data using narratives and dashboards created with open-source AI tools.

• Apply open generative AI models for text summarization, business reporting, and conversational analytics.

• Transform, analyze, and visualize structured business datasets to support data-driven decision making.

• Design AI-powered business workflows for reporting and insight delivery without code generation.

Exclusive access to 4000+ courses

Eligible learners who enrol for this programme will gain access to these additional benefits*:

• Advance their career with credentials from 100+ leading global universities

• Transform their learning experience with access to 4000+ courses and 1000+ guided projects

• Keep upskilling and secure access to 30,000+ hours of teaching by renowned, global professors

• Gain access to courses that are loved by thousands of global learners

*Subject to change as per the Coursera Partner Consortium Program Terms and Conditions.