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PGP in Data Analytics

A PGP in Data Analytics enables you to collect, clean, and analyze data that can be used to improve business decisions.

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Accreditation / Approval

UPES Online

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Duration

6 Months

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Fee

INR 1,25,000/-

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EMI

Avail easy EMI options

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Start Date

January, April, July, October

 

Post Graduate Program in Data Analytics

Every business, small, medium, or large, generates and collects data. This data can be marketing research, logistics, accounts, customer feedback, user behaviour, and so on. Such a rise in data generation has made the need for a data analyst more prominent.

Completing a Post Graduate Program in Data Analytics helps you scrutinize raw data to draw meaningful insights. You can use the data and the derived insights to plan numerous activities like how to lower transportation costs, improve customer experience, and price new materials, to name a few.

Key highlights
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Top-class faculty 

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60+ hours of live classes

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Hands-on training with 70% practical content

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Career essential soft skill program

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100% career assistance with 300+ corporate partners globally

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7 industry projects from different domains

 

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Career prospects
  • Data Analyst
  • Business Analyst
  • Financial Analyst
  • Business Intelligence Analyst
  • Infrastructure Architect
  • Business Intelligence Developer
  • Marketing Analyst
  • Quantitative Analyst
  • Data Visualization Specialist
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Skills covered
  • Basic Statistics
  • Advanced Statistics
  • Descriptive Analytics
  • Predictive Analytics
  • Using R and R studio for analysing data
  • Data Analysis in SQL
  • Data Visualization in Tableau
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Eligibility
  • Any graduate or student pursuing a technical or non-technical degree.
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Selection process
  • Submit an application with information about yourself and why you want to pursue a PG Program in Data Analytics.
  • An Admission Panel will review the application and shortlist candidates.
  • Receive admission confirmation to start the Data Analytics Program within 1 - 2 weeks

Syllabus

Introduction to Data Analytics

  • Data Analytics - An Overview

Basics of R, Data Handling and Statistics

  • Fundamentals of R
  • Data Visualization in R
  • Data Preparation and Cleaning using R
  • Understanding the data using univariate statistics in R
  • Hypothesis testing and ANOVA in R to guide decision making

Predictive Analytics in R

  • Correlation and Linear regression
  • Logistic regression
  • Techniques of customer segmentation
  • Time series forecasting techniques
  • Decision trees & Random Forests
  • Boosting Machines
  • Cross Validation & Parameter Tuning
  • Final Case Study

Basics of Python (Videos Only)

Data Analysis in SQL (Videos Only)

  • Introduction to SQL
  • SQL Data Types & Operators
  • Useful Operations in SQL
  • Aggregating Data in SQL
  • Writing Sub-Queries in SQL
  • Common function in SQL
  • Analytic Functions in SQL
  • Writing DML Statements
  • Writing DDL Statements
  • Using Constraints in SQL
  • SQL Joins
  • Views in SQL

Data Visualization in Tableau (Videos Only)

  • Introduction to Business Intelligence & Visualization
  • Introduction to Tableau
  • Dive into Tableau
  • Connecting Data Sources
  • Tableau Generated Fields
  • Data Manipulation in Tableau
  • Working with Dates in Tableau
  • Data Customization with Calculations
  • Adding Dynamism to a View with Parameters
  • Geographical Analysis & Maps
  • Creating Visualizations
  • Adding Statistics to Data
  • Formatting & Annotation
  • Dashboards & Stories

Our Facilitators

Organisations where our Alumni work

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