Learn essentials of management; planning, organizing, directing and controlling in a real-time simulated environment through case studies. In this course, the learners will hone their decision-making skills by enacting the protagonists’ role in solving challenging managerial situations. The learners will debate and participate in designing the strategies and implementing tactics to build performance-driven, sustainable organizations. The focus would be to learn the skills to build a data-driven culture to manage performance and competitive advantage.

Tools: Power BI, HBR Case studies, and Simulations.

This module will provide hands-on skills with SQL, Python and Tableau required to implement business analytics projects. Through a set of mini-projects, the learners will design and implement a domain-driven system; design and build DataMarts with SQL, extract and process the data with Python and build a dynamic dashboard with Tableau/Qlik Sense on key performance metrics.

Tools: SQL, Python, and Power BI.

This module aims to provide a strong foundation in applying statistical concepts and methods in real-world situations and domains related to analytics. They will learn univariate, bivariate and multivariate statistical techniques, setting and testing hypotheses, sampling, probability and building statistical models. The participants will learn to present their cases with appropriate business relevance to non-statistical / business stakeholders.

Tools: Python, R, and Advanced Excel.

This module is a combination of concepts, tools and practical workshops to familiarize and build expertise in Machine Learning algorithms and model building processes. Learners will get in-depth practical skills in building supervised and unsupervised algorithms through industry-relevant case studies and data sets. CRISP-DM framework is used for all the data science projects and sessions, to ensure that the focus business solutions and not mere model building.

Tools: Python, R, Keras, H₂O

The objective of this module is to make the participants implement and apply state-of-the-art deep learning models in real-world problems. The participants will get in-depth understanding and hands-on exposure to applying deep learning methods to solve a variety of computer vision-based problems. The labs include building a deep neural network for a given problem, hyper-parameter tuning, and optimization to make sure it avoids overfitting, building a time sequence-based neural networks and solving the problems of forecasting, building CNN for image processing tasks, learn how and when to use Autoencoders and familiarize with the latest advances in deep learning.

Tools: Python

Marketing analytics helps the participants to understand and apply the processes and technologies that enable marketers to evaluate the success and value of their marketing initiatives, identify trends and patterns over time, and make data-driven decisions. They will be able to apply marketing mix modelling, market basket analysis, Association rules, Customer Lifetime value calculations and recommendation engines.

Tools: Python, R, Azure, and Power BI.

This course deals with financial analytics concepts and its applications in real-life business environments. Concepts in Fundamental and Technical analysis, Key Financial Statements, Computation of Key Financial Metrics, Types of BFSI Products, and Profit and Loss Drivers etc., will be learnt. The learners will be able to design, build and deploy machine-learning models in BFSI segments. Algorithmic trading, Credit risk scoring, fraud analytics, portfolio management are some of the use cases.

Tools: Python, R, Azure, and Power BI.

Learn the best practices on supply chain analytics from global practitioners. The module provides conceptual and practical skills on the complete spectrum of supply chain and analytics applications on; operational procurement, vendor management, procurement decisions, category management, spend analytics, production systems, logistics sales & operations and customer management. At the end of the module, the learners will be able to design streamlined processes, demand forecasting, network design, predictive maintenance, warehouse zoning and management, performance reports, decision dashboards, moving from descriptive to predictive to prescriptive analytics through real-time industry case studies.

Tools: Python, Advanced Excel, HBR case studies, simulations and role-plays.

The objective of this course is to provide knowledge and skills to the participants to analyze the text and derive useful insights. The participants will be able to read the text data, preprocess, and classify the text. They will have a clear understanding of grouping the text/documents by similarity, detecting the topics in texts, analyze the sentiments, topics and intent with social media posts. NLP based models will be taught with hands-on sessions.

Tools: Python, R

This course will delve into the transformative power of Generative AI, exploring its applications across various industries. Through practical projects, participants will gain hands-on experience with cutting-edge tools and techniques for leveraging AI to generate text, images, audio, and more. The objective is to empower the learner with the knowledge and skills to strategize, implement, and manage Generative AI initiatives within their organizations. Upon completion, participants will be equipped to understand the potential of Generative AI and implement relevant use cases to drive innovation.

Tools: Python, Azure, and AWS.

The first-year Business Analytics program will culminate in designing, preparing and presenting a real-time capstone project on a live business challenge. Each of the participants will be provided with a senior industry mentor for guidance spanning 6 weeks. The final certification is strictly based on the successful completion and submission of the capstone project with a favorable assessment from the panel of industry mentors. The objective is to develop your managerial and consulting capabilities by applying the lessons learnt in the program to real-life business situations.

Tools: Full-stack

Through this course, the participants will learn a variety of structured problem-solving techniques and key management frameworks to solve any business problems. Furthermore, emphasis will be on how to take complex business problems and structurally break down the problem into analytical solutions and present recommendations in the storytelling format to convince stakeholders, combine management consulting skills with statistical and data science skills to solve real-world business problems.

Tools: Simulations, HBR/IVY case studies

Through this course, the participants will learn to connect large Analytics/AI systems from various functions of an enterprise and build a performance-driven KPI setting per function and enterprise as a whole. They will learn to build analytical data mart, dashboards and predictive models across key functions like Finance, Operations, Marketing and Sales, HR, Supply Chain, etc. The participant will be equipped with knowledge, skill and experience to take up the identification of opportunities for analytics in an enterprise and recommend the appropriate solution. Writing and presenting techno-functional RFP’s is an outcome of this module.

Tools: Qlik Sense, SQL, Azure, Python

This is a Microsoft Azure-based module with certification. The learners will be able to design and deploy AI systems with Azure through this course. They will plan and manage an azure cognitive services solution, implement computer vision solutions, NLP solutions, knowledge solutions, and conversational AI solutions. After completing the certification exam they will be designated as Azure AI Engineer Associate

Tools: Azure and Python.

This module deals with designing and implementing a data science solution on Microsoft Azure. The participants will learn to create and manage Azure and Data Bricks workspace, run and monitor models, automated MLs and tune hyper-parameters and Deploy and operationalize machine-learning solutions in the Azure cloud environment. The participants will go through the DP-100 to qualify as Microsoft certified Azure Data Scientist.

Tools: Azure and Python.

The second-year Business Analytics program will culminate in designing, preparing and presenting/publishing a real-time capstone project on a live business challenge. The scope and business applications of the project need to be larger than the first-year project. Designing and implementing, deploying and demonstrating an end-to-end analytics project with a reasonable monetary benefit need to be built. The program office will support with mentoring and report writing. The evaluation is based on viva-voce by an industry panel of experts.

Tools: Full Stack

This module credits can be earned by writing and publishing a research paper on the capstone project done in the earlier module. The participant needs to publish or present the paper in a peer-reviewed journal or reputed international conference. The participants will learn skills in research paper writing and publishing/presenting.