elearning
  • Provides an approach for the study of concepts related to gathering insights from data which would enable in data driven decision making

ONLINE PROGRAM
DATA ANALYTICS

95000 32138

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Duration | 10 days (10*6 hrs/day (60 hrs)

ELIGIBILITY:

  • Final Year students/ Pre-Final Year Students of B.E

  • Graduate Engineers (Who have graduated within one year and looking to upskill)

  • Science Graduates with Mathematics/Statistics background

  • Programming knowledge in python & R is required

HIGHLIGHTS

  • The training is offered with a number of case studies illustrating the various techniques used in Data Analytics.

  • Hands on exercises of the techniques on standard tools like R and Python are included as a part of the course.

  • Course will be delivered through Online mode.

  • Lecture sessions would have a duration of 90  minutes with a maximum of two lectures per day.

CONTENTS

  • Basics of {Python /R Programming for the course)

  • Installation of Software (Python /R and other tools

  • Introduction to Data Analytics

  • Data Types, Variables, Measurement

  • Data Analytics-Descriptive, Predictive, Diagnostics, Prescriptive

  • Introduction to Data Analytics

  • Data Types, Variables, Measurement

  • Data Analytics-Descriptive, Predictive, Diagnostics, Prescriptive

  • Probability and Statistics for Data Analytics

  • Probability concepts

  • Inferential Statistics concepts

  • Hypothesis Testing with Practical scenarios

  • Predictive Analytics

  • Linear Regression

  • Classification-Logistic Regression

  • Quiz  other interactions

OUTCOMES

By The End Of Course The Learner Will:

  • Will be able to  analyse data  using standard tools, identify missing elements, Data wrangling and transformation

  • Will be able to prepare plots, charts  for Data Visualization using standard libraries in R and Python

  • Will able to apply statistical techniques  for analysis to aid decision making

  • Exposed to basic concepts in Predictive Analytics

  • Has gained experience in the use of R /Python and other tools