Applied Business Analytics

• Data and Measurement Basics

• Introduction to Data Dichotomies

• Data Dichotomies

• Introduction to Data Types

• Debrief for the Scales of Measurement Activity

• Data Preprocessing for Analytics Using the Data-Preproc App

• What are Large Language Models (LLMs)?

• The Power of Generative AI in Data Analysis

• Practical Applications of Generative AI in Business

• Definitional Preliminaries

• Anatomy of a [Simple] Prompt

• Prompting Text Summarisation

• Prompting Reasoning

• RTFC Framework for Prompt Design

• Zero-Shot Prompting: Types & Examples

• One-Shot Prompting: Types & Examples

• Image-Analytics with Generative AI Assist

• Graph-Analysis with Generative AI

• Introduction to Statistics and Hypothesis Testing

• Quick Introduction to Probability

• Introduction to Normal Distribution

• Practical Example of Use of Normal Distribution

• Sample Vs Population

• Statistical Inference

• Unknown Population Standard Deviation

• Two Types of Errors

• Hypothesis Testing

• One Sided Test

• Summary

• Predictive Analytics: Decision Trees

• What is Decision Tree?

• Decision Trees Example for Prediction

• Decision Trees: Demo​

• Depth of the Tree

• Prediction Using Decision Tree

• Decision Trees for Metric or Numerical Outcome

• Regression Analysis

• ML Approaches in Business Analytics

• Regression: Motivating Example

• Input Data and Summary Stats

• Select Dependent (Y) and Independent (X) Variables​

• Regression Demo: Interpretation

• Regression Demo: Evaluating the Model

• Zero Code Learning Demo

• Regression Variant

• Interaction Effects​

• Regression Analysis: Summary

• Classification Analysis

• Logistic Regression Overview

• Why Not Use Regression

• Logistic Regression Example: Predicting Heart Disease

• Interpreting beta

• Classification/Confusion Matrix

• Multiple Classes

• Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC)

• Multiple Classes​​

• Prelims: The WHAT of Factorising Data

• Factor-An: Toothpaste Dataset

• Factor Analysis of a Real Dataset: mtcars

• Factor Analysis on OTT Genres

• Generative AI Assist for the Toothpaste Example

• Cluster Analysis Overview

• Grouping Objects

• Clustering Algorithms

• Clustering and Principal Component Analysis (PCA)

• Clustering Visualisation

• Positioning Statements

• Elements of a Positioning Statement

• Example: Positioning Statement for Southwest Perceptual Maps and JSMs

• Guide to Read JSM Plots

• Generative AI Assist on Pmaps and JSMs

• Cities: Perception and Preference Analysis

• The WHY and HOW of Text-An

• Text-Analysing a Review Corpus ​

• Interpreting App Output with Generative AI Assist​

• Keyword-Based Corpus Filtering​

• The Need for a Keyword Filtering App​

• Elementary Sentiment Mining​ ​​​

• Four Tidytext Sentiment Dictionaries

• Text Analysis with PDF and Generative AI Assistance

• Network Properties

• Social Network Analysis (SNA) Examples

• SNA with Real Data

• SNA Demo: Network-Prep and Basic-Network App

• Social Networks in Affiliation Space

• Text Network and Recommendation Analysis Application

• Introduction

• Understanding Causal Inference

• Gold Standards to Establish Causality (Experiments)

• Causal Inference

• Analysing Experimental Data and Drawing Inferences

• Analysing A/B Tests: Electricity Pricing

• Experimentation Using ML: Ad Targeting Example

• Capstone assignment

After completing this online business analytics programme, you should be able to execute an applied analytics workflow end to end: define and structure business problems for analysis, collect and preprocess data into analysis-ready form, apply core statistical and machine-learning techniques, evaluate model outputs using standard performance and validation logic, and communicate results through business-oriented visual analytics and dashboards (e.g., Tableau-style workflows). You should also be able to learn GenAI and Agentic AI applications for specific analytics tasks such as summarisation, reasoning support, and accelerating insight generation, and then translate findings into quantified recommendations, forecasts, segment strategies, or experiment/causal-inference conclusions. In practical terms, you leave with the capability to independently run applied business analytics workstreams and contribute effectively to decisions and analytics-led managerial roles.

Yes. In the ISB Online Applied Business Analytics programme, there are dedicated modules on leveraging Generative AI for business analytics, including LLMs and prompt design for analysis tasks. In addition, the programme includes live masterclasses on Agentic AI, AI-powered predictive analytics, and AI-augmented business intelligence, so you understand how modern analytics teams are using AI in practice.

You will work with hands-on datasets and real business scenarios drawn from multiple industries. The cases are designed to reflect common analytics use-cases such as customer segmentation, demand and sales forecasting, fraud and risk detection, text analytics on customer feedback, and valuation or performance benchmarking. This ensures the learning stays application-driven and closely aligned with how analytics is used in real organisations.

Yes. The programme ends with a capstone project where you combine the techniques you will learn to solve a structured business problem. It’s your portfolio-style proof of capability in applied business analytics.

The programme does not require prior coding knowledge; you can run analyses and interpret outputs without writing scripts. This makes it accessible for non-technical professionals while still building a clear understanding of the logic and business application of machine-learning models.

This programme is designed for professionals who want applied business analytics skills to improve decisions at work. It’s especially useful if you want to:

• use data to sharpen strategy, marketing, finance, operations or product choices,

• work with and manage data science/analytics teams, or

• move into top roles in analytics.

In short, if your job needs you to solve business problems with data, this business analytics certification fits.

The programme is designed to provide flexible learning given the time constraints of working professionals and contains high-quality pre-recorded videos with the globally renowned faculty from ISB. The programme contains pre-recorded videos by globally renowned ISB faculty, live masterclasses on top trending topics, case studies, datasets, quizzes, assignments, discussion boards, and live doubt-solving sessions. The ISB Applied Business Analytics course runs for 14 weeks. Most learners spend around 4–6+ hours per week, which includes watching recorded faculty lessons, doing quizzes/assignments, attending live doubt-clearing sessions and live masterclass sessions.

There are live webinars with programme leaders called Emeritus office hours, every week for doubt-solving and any discussion regarding the curriculum. There will live masterclasses by industry's top analytics experts. There are no live sessions with ISB faculty.

What are the requirements to earn the ISB Online Applied Business Analytics certificate?

Participants must receive 70% to pass and obtain the certificate of completion and be a part of the ISB Online Network. Each programme includes an estimated learner effort per week, so you can gauge what will be required before you enrol. This is referenced at the top of the programme landing page under the Duration section, as well as in the programme brochure, which you can obtain by submitting the short form at the top of this web page. All programmes are designed to fit into your working life. You must complete the required activities to pass and obtain the certificate of completion. Some programmes include a final project submission or other assignments to obtain passing status. This information will be noted in the programme brochure. Please contact us at 9738013875 or mail at support.india@emeritus.org if you need further clarification on any specific programme requirements.

You will have access to the online learning platform and all the videos and programme materials for 12 months following the programme start date. Access to the learning platform is restricted to registered participants per the terms of agreement.

This programme comes with ISB Online Network access, which allows you to network with other ISB Alumni and a host of other benefits. However, this is not the same as the ISB Online Alumni status accorded for full time campus programmes.

ISB Online Applied Business Analytics is a strong choice for working professionals because it delivers a rigorous online business analytics certification from ISB Online that is tightly focused on real-world application. In 14 weeks, you build end-to-end capability in applied business analytics, data analytics, predictive and prescriptive analytics, and machine learning for business, supported by hands-on datasets, industry cases, Tableau-based visual analytics, and a capstone that mirrors real workplace problem-solving. The learning is supported by live industry masterclasses which includes GenAI and Agentic AI applications, that show how AI agents and LLMs are used to accelerate analysis and decision-making in organisations. The result is a credible ISB Online certificate plus practical, job-relevant skills for roles in analytics.

Participants will need the latest version of their preferred browser to access the learning platform. In addition, Microsoft Office and a PDF viewer are required to access documents, spreadsheets, presentations, PDF files, and transcripts.

Yes, the learning platform is accessed via the internet, and video content is not available for download. However, you can download files of video transcripts, assignment templates, readings, etc. For maximum flexibility, you can access programme content from a desktop, laptop, tablet, or mobile device. Video lectures must be streamed via the internet, and any livestream webinars and office hours will require an internet connection. However, these sessions are always recorded, so you may view them later.

Yes, the flexible payment option allows a participant to pay the programme fee in instalments. This option is made available on the payment page and should be selected before submitting the payment. For more questions on flexible payment options reach out to our programme advisor on +919738013875.

1. If a participant faces severe challenges in dedicating time to study the programme or has personal medical issues, a participant may request to defer the enrolment to another cohort of the same programme.

2. The participant must request to change to a future batch within 30 days after the programme commencement.

3. A participant may request a one-time deferral to the next available cohort of the same program. Such deferral is contingent upon and subject to:

   • Programme and batch availability at the discretion of the Institute and Emeritus

   • Approval of a valid deferral request with the supported document.

   • Payment of all pending programme fees as per the original programme scheduled date or Payment of the applicable non-refundable deferral fee as set forth under point (v).

4. The participant must write the deferral request to support.india@emeritus.org, specifying the reason for deferral with supporting documents.

5. The deferral request with reasons and supporting documents shall be passed on to the Institute, who reserve the absolute right to approve or deny such requests, at its discretion.

6. Participants may be offered a deferment under the condition that they pay the full fees as per the original payment plan. Once the payment is completed, the deferment will be processed. However, if a participant wishes to defer the payment plan as well, they will be required to pay the fee, collectively referred to as the "non-refundable deferral fee" of Rs 10,000 + taxes for certificate courses and Rs 20,000 + taxes for senior executive programmes, along with the programme fee differential amount between the two cohorts.

7. For the payment plan deferment option, the participant will have 5 (five) business days to pay the deferral fee from the date of deferral approval by the Institute, after which the deferral approval will expire, and the participant will continue in the current cohort. For clarity, until the full payment is received, the participant will remain in the current cohort.

8. Upon payment of the non-refundable deferral fee mentioned under point (v), Emeritus will process the deferral request, and the participant's access to the current cohort will be disabled. Accordingly, the participant must start the programme in the new cohort from the beginning.

9. The deferral request can only be considered when the current cohort the participant is enrolled in is ongoing. A deferral request shall not be entertained if the currently assigned cohort is completed or after the programme end date.

10. It is the participant's decision to defer the programme to another cohort. It is important to note that

    if the programme is discontinued after deferment for any reason, the programme fee will not be refunded to the participant