MS Data Science 60 ECTS

Solve a real industry problem through the concepts learnt in exploratory data analysis 

Build a model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue 

Help the sales team of your company identify which leads are worth pursuing through this classification case study 

Apply the machine learning concepts learnt to help an international NGO cluster countries to determine their overall development and plan for lagging … Apply the machine learning concepts learnt to help an international NGO cluster countries to determine their overall development and plan for lagging countries.

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customer… Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them. Learn Dimensionality Reduction and Classification techniques to mitigate customer churn problems.

Build a machine learning model to identify fraudulent credit card transactions 

Help a retail-giant to have a clear idea of how their sales will look like in the future. Use time-series analysis to create a forecasting model to h… Help a retail-giant to have a clear idea of how their sales will look like in the future. Use time-series analysis to create a forecasting model to help predict sales.

In this assignment, you will work on a movies dataset using SQL to extract exciting insights. 

In this assignment, you will apply your Hive and Hadoop learnings on an E-commerce company dataset. 

This is an ETL project which will cover the topics like Apache Sqoop, Apache Spark and Apache Redshift 

This assignment will test the learners understanding of the previous 2 modules on structured problem solving 1 and 2 

With the IPL season commencing, let's go ahead and do an exciting assignment on sports analytics in Tableau. 

Build a regularized regression model to understand the most important variables to predict the house prices in Australia. 

Analyse the dataset of parking tickets 

Practice MapReduce Programming on a Big Dataset. 

In this module, you will solve an industry case study using optimisation techniques 

This module will contain practice assignment & all resources related to a classification based problem statement.