Data Analytics with R Certification Training

Training will help you gain expertise in R Programming, Data Manipulation, Exploratory Data Analysis, Data Visualization, Data Mining, Regression, Sentiment Analysis and using R Studio for real life case studies on Retail, Social Media. 

Data Analytics with R Certification Training
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Edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. 

After the completion of the Edureka Data Analytics with R course, you should be able to:

  • Understand concepts around Business Intelligence and Business Analytics
  • Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others
  • Apply various supervised machine learning techniques
  • Perform Analysis of Variance (ANOVA)
  • Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc
  • Use various packages in R to create fancy plots
  • Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights

The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists.

Программа курса:

  • Introduction to Data Analytics
  • Introduction to R Programming
  • Data Manipulation in R
  • Data Import Techniques in R
  • Exploratory Data Analysis
  • Data Visualization in R
  • Data Mining: Clustering Techniques
  • Data Mining: Association Rule Mining & Collaborative filtering
  • Linear and Logistic Regression
  • Anova and Sentiment Analysis
  • Data Mining: Decision Trees and Random Forest
  • Project Work