The course will be held in the classroom, in June. Details on the organization and content of the course will follow shortly. More information will be provided on Moodle in due course.

It is important to differentiate between anecdotal evidence and evidence that can be tested and proved. Understanding and analyzing data is essential for the latter. All of us in day-to-day routine use numbers in our calculations. Problems in business contain a great degree of quantitative element in the form of facts and figures. It is essential for professionals to carry out data analysis and interpretation for effective decisions. In this context, they need to prepare quantitative arguments to justify their decisions. Decision making using machine learning techniques is the answer for accomplishing this purpose. The course aims to develop your analytical skills - both the ability to conceptualize a problem as well as solve them broadly, it aims to make you understand and appreciate the most widely used tools of machine learning  which form the basis for rational and sound  decisions

• Focus on problem recognition and test hypothesis/model in the context of managerial decision-making.
• Develop skills in analysis and interpretation of data
• Handle challenging problems using appropriate analysis tools

-   Introduction to analytics using machine learning

-   Introduction to R Studio and QGIS

-   Unsupervised learning

-   Supervised learning: Continuous response and classification

-   Boosting and bagging

-   Model comparisons