These courses can be used by students, researchers, and analysts. Further suggestions and collaborations are welcome.

Principles of Data Science

Data science comprises the study of the nature of data in order to discover structural relationships contained in the data, and hence about what the data represents. Data can be considered as those aspects of information around us that can be captured and preserved in memory. Various techniques are employed on existing data to discover its structure.


Experiments & Causal Inference

A particular cause can produce two simultaneous effects which are strongly correlated. Those effects can predict each other very well, but we know that none of them is the cause for the other. This course offers methods to establish the existence of such causal relationship using data. Concepts are explained using examples and implementations.


Time Series Analytics

Time series appears in all fields of study. This course provides concepts and implementations of time series methods. For better illustration of concepts, we will rely on examples from the domain of financial markets. We will understand why time series requires a different set of methods, and cover traditional time series models and new models based on machine learning.


Network Analytics

Networks are everywhere -- in nature, in society, in markets. This course will provide you the concepts and tools to work with network data, identify situations where network modelling is appropriate, and choose the best methods available. You can extend your study to specific fields of applications, depending on your interests.


Data Driven Business Decisions

This course is about using and communicating data science better, in the process of making business decisions. The course covers various examples of the nature of decision making in management, and hands-on experience on general business analytics cases, along with inputs from latest research. Pros and cons of data-driven decision support systems are also available.


Computational Social Science

Social issues have always existed. The era of big data has provided several data sources and computational power to extract insights on social issues. This course is designed for those who are interested in gaining a deeper understanding of traditional and contemporary social issues using various cutting-edge methods from data science like social networks and text analysis.



Here you can find data sets, learning paths, and other recommended materials. These will be made available in near future.