Year 1 -  First Semester 

& Second  Semester 

Year 2 -  First Semester 

& Second  Semester 

MSc Data Science Subjects

MSc Data Science syllabus must be looked at before choosing the course. The detailed syllabus is mentioned below:

MSc Data Science First Year Subjects

Mathematical Foundations For Data Science: It covers, in particular, the basics of signal and image processing, imaging sciences and machine learning

Probability And Distribution Theory: A probability distribution gives the possible outcomes of random events. It is also defined as the set of possible outcomes of a random experiment based on the underlying sampling space.

Design and Analysis of Algorithms: Algorithm analysis is a part of computational complexity theory, which provides theoretical estimation for the required resources of an algorithm to solve a specific computational problem. 

Introduction to Geospatial Technology: Geospatial Technology includes Geographic Information Systems, Remote Sensing, and Global Positioning Systems. It enables us to acquire data and use it for analysis, modeling, simulations, and visualization.

Advanced Python Programming for Spatial Analytics: This is a Python module that implements various iterator building blocks that together form an "iterator algebra" that allows you to efficiently build tools in the Python language.

Data Analytics Courses

Big Data Courses

MSc Data Science Second Year Subjects

Spatial Modeling: Spatial modeling is an important tool for performing geospatial analysis to understand the world and guide decision-making. In GIS, a spatial model is a formal language for expressing the mechanics of geographic processes and designing analytical workflows.

Genomics: Genomics is an interdisciplinary branch of biology focused on genome structure, function, evolution, mapping, and editing.

Research Publication: Publications make scientific information publicly available and enable the rest of the academic audience to assess the quality of research.

Natural Language Processing: Natural language processing is a subfield of linguistics, computer science, and artificial intelligence that deals with the interaction between computers and human language.

Exploratory Data Analysis: Exploratory data analysis refers to the essential process of conducting an initial investigation of data to discover patterns, detect anomalies, test hypotheses, and validate assumptions using summary statistics and graphs.