Data science and Spatial Analytics

The current trends of Artificial Intelligence techniques, inclusively Machine learning and deep learning aspects, are uniformly revamping a range of fields from finance and banking to healthcare and earth observations. Over the decades, the volume, variability, and variety of earth observing data have tremendously increased and have generated footprints in almost every terrain of society. The flavors of technological advancement for availing high-resolution spatial data and high computational architectures have become the driving forces for the proliferation of Geo-intelligence and business intelligence. The deep learning capabilities like Neural Networks are very potent to capture the complex non-linear, inter co-related patterns in spatial data with near-human precision and accuracy. This is the art of applying data science for observing spatial data through process of hypothesizing, hypothesis testing, model building and discovering hidden patterns.

Objective:

The objective of M.Sc. (Data science & spatial analytics) is to create the data science professionals by drawing upon data engineering principles augmented by time and space, statistical modeling, mathematical practices and geo-visualization of data environment to solve the data intensive, large –scale, location- based business requirement of industry 4.0

Course Duration:

2 year full time course (4 Semesters)

Semester I Semester II

Generic Core Courses

  • Mathematics for Spatial Sciences
  • Applied Statistics
  • Fundamentals of Data Science
  • Python Programming
  • Introduction to Geospatial Technology
  • Programming for Spatial Sciences 
  • Business Communication
  • Cyber Security
  • Integrated Disaster Management 

Generic Core Courses

  • Spatial Big Data and Storage Analytics
  • Data Mining and Algorithms
  • Machine learning
  • Advance Python Programming for Spatial Analytics 
  • Image Analytics
  • Spatial Data Base Management
  • Flexi-Credit Course
Semester III Semester IV

Generic Core Courses

  • Spatial Modeling
  • Summer Project
  • Web Analytics
  • Artificial Intelligence
  • Flexi-Credit Course
  • Predictive Analytics and Development 

Generic Elective Courses Group

  • Deep learning
  • System Dynamics Simulation
  • IOT Spatial Analytics
  • Spatial User Interface design and Implementation

Generic Core Courses

  • Industry project

Career Prospects

“Learning from data is virtually universally useful. Master it and you’ll be welcomed nearly everywhere”- John Elder, Elder Research

Location based service industry including:

  • Transportation (Uber,Ola)
  • Telecom
  • Retail
  • Utilities/ Manufacturing
  • Healthcare/ pharma E-commerce
  • Banking/ Insurance
  • Automotive