Basics of Data Science, Types, Variables, Charts
Introduction to Programming with Tool R
Work pro-efficiently with R, advanced skills & techniques
A boost in your career opportunities
Workshop Participant Certificate
Data Science Introduction: Data Statistics – Data Visualization - Machine Learning Algorithm - Supervised – Unsupervised learning Algorithm.
R Introduction: What is R? And Why R?: Different “flavors” of R-Installing - R Studio Desktop - Understanding R Studio-Installing Packages and Libraries in R Studio - Setting Your Work Directory
Implementation Data Variables: Data Types - Operators – Keywords – Exceptions-Functions
R Data Structures Vectors and Lists: Strings and Matrices - Arrays and Factors - Data Frames – Packages.
R Interfaces: R- CSV files Read and Write and analyze the data - R- Excel files Read and Write and analyze the data
Data Visualization: Bar Graph and Line Graph - Area Chart and Pie Chart - Scatter Diagram and Histogram - High-Low Graph - Box Plot and Dual Axis Graph
Correlation Analysis Using R: Formulation of Regression Model - Bivariate Regression using R - Multiple Regression using R - Mapping Bivariate Regression with Real Time Example Linear Regression
Descriptive Statistics: Central Tendency - Mean and Weighted Mean and Geometric Mean - Median, Mode, Percentiles and Quartiles - Dispersion - Variance, Standard Deviation, and Range
Logistic Regression using R: Estimated Equation for Logistic Regression
Factor Analysis using R: Factor Analysis Model-Factor Analysis Method-Principal Component Analysis-Rotation Method -Mapping Factor Analysis with Real Time Example
Cluster Analysis using R: Cluster Analysis Introduction - Statistics associated with Cluster Analysis - Conducting Cluster Analysis - Classification of Clustering Procedure - Hierarchical Clustering - Non-Hierarchical Clustering
Association Rule using R: Association Rule Introduction - Apriori Algorithm - Multiple Association Rules - Market Basket Analysis (MBA) - Application of Apriori Algorithm and Market Basket Analysis
Note: It is strongly recommended that you bring your own LAPTOP for the workshop so that you can easily practice further at Home/Company/College.
Data Modeler and Data Analyst
Mr. Dinesh Babu has gained enough acumen and expertise over 6+ years as a Data Modeler and Data Analyst. He has rehearsed and gained proficiency in requirement gathering and data modeling including design and technical knowledge. His experience spreads wide in the fields of OLTP, Data Warehousing, OLAP and ETL Environment. He is thrilled and swift enough to get adapted to new technologies and actualize them in his field of practice.
Information is the oil of the 21st century, and analytics is the combustion engine.
So Enroll Right Away to Fuel Yourself with Big Data Knowledge with R, which is the Foundation of all the Megatrends that are Happening.
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