PG PROGRAM IN DATA SCIENCE
Take your first step towards becoming a Data Scientist
- 120+ Hours of LIVE Web Classes
- 350+ Hours of High Quality e-learning
- Tools covered: R, Tableau, Hadoop, Pig, Hive, HBase, Spark, etc.
Batch Start date
15 December 2017
₹ 1,50,000 + Taxes
Industry-relevant course curriculum, with applications in multiple domains taught by highly experienced Subject Matter Experts from academia, IT and Data Science industry.
120+ Hours of LIVE web classroom sessions on weekends, complemented with assignments and case studies during after-class hours. Along with 350+ Hours of Online classes.
Instructor led learning:
On completion of the course get a certificate from Manipal Academy of Higher Education
Award / Certificate
The program admits students who are Freshers and working professionals who wants to build career in the field of Data Science.
Applicants should have the following minimum academic qualifications:
Science Graduates (BSc. & MSc.) from a recognised university in Maths/Stats/Operations Research/Physics/Economics/Computer Science/Information Technology
Commerce Graduates from a recognised university in Maths/Stats/Economics/Computer Science/Information Technology
Course Curriculum / Modules
Module 1 - a : Problem Solving for Java Programming
b : Advanced Excel
Module 2 - a : Programming with Data Science
b : Introduction to Python with Data Science
Module 3 - Statistical Technique in Data Science
Module 4 - Exploratory Data Analysis
Module 6 - Big Data Technologies
Module 7 - Business Communication
Module 8 - a : Machine Learning I
b : Machine Learning II
Module 9 - Specialization 1 : HR Analytics
Specialization 2: Banking Analytics
Specialization 3: Web Analytics with Google
Module 5 - Data Visualization
Perform data analysis, modelling, predictive analysis, and story-telling through data visualization which is crucial to business decision-making.
Understand and use Big Data technologies as enablers to deploy enterprise information management and solve business problems.
Apply the methods, tools and techniques by leveraging technologies such as R, Excel, SQL, NoSQL, Hadoop, Pig, Hive, Apache Spark and other open source and proprietary products as well.
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