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PG PROGRAM IN DATA SCIENCE

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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.


Timings

Weekends

Online

Batch Schedule

Course fee

Mode

15 December 2017

Batch Start date

₹ 1,50,000 + Taxes

On completion of the course get a certificate from Manipal Academy of Higher Education

Comprehensive curriculum:

Course Highlights

Industry-relevant course curriculum, with applications in multiple domains taught by highly experienced Subject Matter Experts from academia, IT and Data Science industry.

Award / Certificate

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:

Eligibility Criteria

Applicants should have the following minimum academic qualifications:


  • B.E/B.Tech/BCA/B Pharm graduates and/or ME/M.Tech/MCA/M-Pharm graduates from a recognised Institute/University.

Or

          Science Graduates (BSc. & MSc.) from a recognised university in Maths/Stats/Operations Research/Physics/Economics/Computer      Science/Information Technology

Or

          Commerce Graduates from a recognised university in Maths/Stats/Economics/Computer Science/Information Technology

  • Min 50% marks or equivalent in the qualifying examinations.

          

The program admits students who are Freshers and working professionals who wants to build career in the field of Data Science.

Course Curriculum / Modules

Module 8 - a : Machine Learning I

                 b : Machine Learning II

Module 6 - Big Data Technologies

Module 5 - Data Visualization

Module 1 - a : Problem Solving for Java Programming

                b : Advanced Excel

Module 4 - Exploratory Data Analysis

Module 7 - Business Communication

Module 2 - a : Programming with Data Science

                 b : Introduction to Python with Data Science

Module 9 - Specialization 1 : HR Analytics

                 Specialization 2: Banking Analytics

                 Specialization 3: Web Analytics with Google

Module 3 - Statistical Technique in Data Science

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.

Understand and use Big Data technologies as enablers to deploy enterprise information management and solve business problems.

Learning Outcomes

Perform data analysis, modelling, predictive analysis, and story-telling through data visualization which is crucial to business decision-making.

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