Automation in Excel(Excel VBA and Macro)

Advanced Analytics in R for Beginners

Number of Hours : 30 Hours

R possesses an extensive catalog of statistical and graphical methods. It includes machine learning algorithm, linear regression, time series, statistical inference to name a few. Data analysis with R is done in a series of steps; programming, transforming, discovering, modeling and communicate the results.

Prerequisites:

Basic Programming Skills

Courses Objectives:

After the course, you will be able to:

    • Implement creative visualizations in ggplot2
    • Implement Classification Techniques
    • Implement Unsupervised Learning Techniques
    • Understand and Implement Text Analytics, Deep learning and Time Series Analytics
    • Bar Charts, Line Charts, Box Plot charts, Scatter plot and Histogram
    • Changing layers, scales, coordinates, and themes
    • Random Forest
    • Naive Bayes
    • Support Vector Machine: Classification
    • Implementing K-means Clustering in R
    • Implementing C-means Clustering in R
    • Implementing Hierarchical Clustering in R
    • Implementing Bag of Words approach in R
    • Implementing Sentiment Analysis on Twitter Data using R
    • Visualizing and formatting Time Series data
    • Plotting decomposed Time Series data plot
    • Applying ARIMA and ETS model for Time Series Forecasting
    • Forecasting for given Time period
    • Biological Neural Networks
    • Understand Artificial Neural Networks
    • Building an Artificial Neural Network