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About MSC in DATA SCIENCE
The rate at which we are able to create data is rapidly accelerating. This ranges from biomedical data to social media activity and climate monitoring to retail transactions. These enormous quantities of data hold the keys to success across many domains from business and marketing to treating cancer or mitigating climate change.
“According to IBM, globally, we currently produce over 2.5 Quintilian bytes of data a day.”
The pace at which we produce data is rapidly outstripping our ability to analyse and use it. Science and industry are crying out for a new generation of data scientists who combine the statistical skills of data analysis and the computational skills needed to Carry out this analysis on a vast scale.
Aims and outcomes:
The Data Science Masters degree will provide the students with an in-depth understanding of the theory and practice of Data Science and its application in different organisational contexts. The students will also gain practical skills in handling structured and unstructured data, analyzing and visualizing data, data mining, as well as gaining hands-on experience of software tools used and their use in real-world settings.
Students will gain the skills of a “data manager” who understands what the algorithms (e.g., for data mining or handling ‘Big Data’) can do and when to use them for the beneﬁt of the organization.
Get prepared for globally recognized Certifications
150+ centres spread over 20+ countries
State-of-the-art Infrastructure based on latest technologies
Get trained from industry-experts
Based on ITIMS, Social, Mobility, Analytics and Cloud
Dedicated Placement Cell for IIHT students
1. Introduction to Data Science
2. Programming for Data Science with R
3. Set Theory and Mathematical Concepts for DATA Science
4. Fundamentals of Business Statistics
5. Implementing R Tool
6. Programming for DATA Science with SQL
1. Fundamentals of Data Mining
2. Data Warehousing
3. Business Intelligence
4. Statistical and Mathematical Implementing Business statics and its application
5. Managing and Implementing Data mining tools
1. Operation Management
2. Programming for Data Science with Python
3. Deterministic Models and Optimization
4. Business Modeling for Enterprise
5. Implementing Business Research Methods
6. Machine learning
1. Big Data
2. Large Scale Data Processing
3. Data Sourcing
5. Programming and Data Analysis
6. Hadoop DFS
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