IIM Calcutta - IIM Calcutta - Senior Management Programme in Business Analytics
- Offered byEmeritus
IIM Calcutta - Senior Management Programme in Business Analytics at Emeritus Overview
Duration | 9 months |
Total fee | ₹5.95 Lakh |
Mode of learning | Online |
Difficulty level | Advanced |
Credential | Certificate |
IIM Calcutta - Senior Management Programme in Business Analytics at Emeritus Highlights
- Earn a certificate of completion and executive alumni status from IIM Calcutta
- 3 campus immersions at the IIM Calcutta
- *Easy EMI payment option available
- Interact and network with leading industry experts
IIM Calcutta - Senior Management Programme in Business Analytics at Emeritus Course details
- Managers and Senior Managers- looking for a practical understanding of analytics to drive existing or future strategic initiatives, and to tackle business problems using analytics within their organisations to propel their career to the next level.
- Business/Systems/Data Analysts- working in data-centric roles who want to explore the business value in analytics to balance business objectives with analytical outcomes.
- Business Heads, CXO's, and Leaders- who are at the forefront of decision-making in their organisations and recognise the need to leverage analytics for business growth and strategic initiatives, and to be able to provide strategic leadership on analytics projects.
- Senior Consultants- who work with leadership teams to provide direction on how new and existing application of business analytical techniques can lead to innovation and competitive advantage
- Gain proficiency in identifying strategic opportunities to implement business analytics solutions for competitive advantage
- Advance ability to provide vision and direction to the analytics team to adopt specific analytics tools and techniques
- Build capacity in evaluating the need-gap to improve productivity through a data-driven systematic approach
- Lead high-performing analytics projects and teams effectively towards business transformation
- Incorporate industry best practices in organisational analytics strategy: customer data privacy, legal and ethical issues
- The program helps participants learn to make decisions which keep pace with the emerging new platforms, network effects, personalisation and targeting with a focus on proven frameworks and best practices in the industry. Participants will also learn how analytical innovations are leading to disruption in the business world
- Schedule: 3 Hours Every Sunday (9.00 AM to 12.00 PM)
IIM Calcutta - Senior Management Programme in Business Analytics at Emeritus Curriculum
Module 1: Business Value of Data Analytics
Building a data-driven culture in an organisation:
Analytics readiness of an organisation and building a data-driven decision-making culture
Building organisational team for making use of Data Science and Analytics
Appreciating the emerging nature of competition and the role of business analytics
Module 2: Statistics for Data Science
Statistics: The art of summarising data and statistical learning in decision-making
Probability: Applied probability and decision-making under uncertainty
Sampling: Data sampling and the art of inferring about the population from samples
Regression: Regression techniques and the art of capturing relationships among variables of interest
Module 3: Descriptive Analytics
Exploratory Data Analysis: Appreciation of analytical reasoning and empirical findings from data
Data Visualisation: Challenges in Data visualisation and data interpretation
Module 4: Experimentation
Experiment Design, Analysis & Testing: Data capture and preprocessing issues
Causal Inference and analysis: Interpretation of raw data
Interpreting result: Interpretation of statistical summary of data
Module 5: Data Sources
Data Sources: Issues in filtering Raw Data for finding extract worth Modeling
Data Extraction and Cleaning: Outlier analysis, Dimensionality reduction in Data Cleaning
MODULE 6: Predictive Analytics
Forecasting: Business forecasting principles and issues
Classification: Artificial Intelligence and Machine Learning in Decision-making -role of supervised learning
Clustering: Role of unsupervised learning in decision-making
Time series analysis: Time series analysis based decision-making
Supervised Machine Learning: Combining human expertise with data driven intelligence for decision-making
Neural Networks and Deep Learning: Artificial neural network and deep learning in decision-making.
MODULE 7 - Prescriptive Analytics
Simulation: Learning through simulation and games
Decision Analysis: Individual and group decision-making issues
Optimisation Models: Use of discrete optimisation concepts in decision-making
Game theory: Insights from game theoretic situations, network externalities and network effect on economy, information cascade effects in decision-making.