Futures Studies

This course on time series is for students enrolled for MSc (Data Science) offered by the Department of Futures Studies.

This course is on the range of requirements, functionality, design tradeoffs, memory hierarchy and cost-performance tradeoffs related to par allel/distributed systems, cluster computing, grid computing, supercomputing, cloud computing that modern parallel/distributed systems have to address.

FUS-E-639 Introduction to data analysis for third semester MTech(TM) students 

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Students will review statistical sampling, T-tests, Analysis of Variance, Linear Regression and other skills. Rather than calculations, the course focuses on interpretation, analysis and communication of the results and ethics of statistical analysis.

This course introduces the core principles and techniques required in the design and implementation of database systems. It also provides students with theoretical knowledge and practical skills in the use of databases and database management systems in information technology applications.

This course introduces fundamental mathematical concepts relevant to computer science and provides a basis for studies in data science and statistical machine learning.

This course emphasizes database concepts, developments, use and management in three main sections: database concepts, practice, and emerging trends. Relational database systems are the main focus, but other types, including object- oriented databases, are also studied.

In this course, you will learn the fundamentals of Python programming with a focus on data analytics, and work with popular statistical computing libraries — like numPy, Pandas, sciPy, and Scikit-learn — that allow you to begin analyzing data to answer key questions.

The purpose of this course is to introduce data science  concepts and help you learn and apply its knowledge.