Introduction to Data Analytics

Course outline:

Every company, business, corporate, start-up is always looking at the next frontier to breach or trouble-shooting an urgent scenario. However, how to do that? What is that next frontier? What does it take to reach to that level? How to come out with the best solution to the given scenario?
The answer lies in the field of Data Analytics & Predictive Modelling.


Key Takeaways:

  • Gain exposure to key disciplines and skills needed to fulfill the role of a business analyst
  • Real-world applications of Data Analytics and Predictive Modelling
  • Understands and master Data Sanitization techniques
  • Learn to perform testing and segmentation
  • Build predictive models using linear, logistic regression
  • Forecast using time series analysis
  • Perform text mining and sentiment analysis on social media data


Introduction to Analytics & Data Analysis tools

  • What is data analytics?
  • Importance of analytics.
  • Introduction to various analysis techniques
  • Applications of data analysis in various industries
  • Introduction to R
  • Basics of programming in R
  • Data handling in R
  • BI reporting in R
  • Performing statistical analysis on R
  • Analyzing the data with simple descriptive statistics
  • Variance and standard deviation


Data Validation & Cleaning

  • Introduction to validating and cleaning data
  • Examining data errors when reading raw data files
  • Validating data with the CONTENTS, PRINT, FREQ, MEANS and UNIVARIATE procedures.
  • Cleaning invalid data: Missing value identification and treatment.
  • Outlier identification and treatment


Correlation and simple regression

  • Studying variable association using correlation
  • Building linear regression Models
  • Building nonlinear regression models


Cluster Analysis

  • Customer segmentation using cluster analysis


Decision Trees

  • Customer segmentation using decision trees


Time series forecasting

  • Time series analysis & forecasting using ARIMA


Credit Risk Model Building

  • Introduction to predictive modeling
  • Steps in credit risk model building
  • Variable selection techniques
  • Model validation


Data visualizations & dashboard making on Tableau

  • Introduction to Tableau
  • Data import & manipulation in tableau
  • Creating visualizations in tableau
  • Dashboards & analysis on tableau


Note: If you miss a scheduled one on one class, then don’t worry, you can reschedule it at your convenient time & the missed class won’t be counted. You may defer a class any number of time. Also, you get life time access to materials which gets constantly updated.


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