R Programming, Data Handling and Cleaning, Basic Statistics, Classical Machine Learning Algorithms, Model Selection and Validation, Advanced Machine Learning Algorithms, Ensemble Learning.
Write your own R scripts and work in R environment.
Import, manipulate, clean up, sanitize and export datasets.
Understand basic statistics and implement using R.
Understand data science life cycle while understanding steps of building, validating, improving and implementing the machine learning models.
Do powerful analysis on data, find insights and present them in visual manner.
Learn classical algorithms like Linear Regression, Logistic Regression, Decision Trees and advance machine learning algorithms like SVM, Artificial Neural Networks, Reinforced Learning, Random Forests and Boosting and clustering algorithms like K-means.
Know how each machine learning algorithm works and which one to choose according to the type of problem.
Build more than one powerful machine learning model and be able to select the best one and improve it further.