R Programming for Complete Data Science and Machine Learning

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Price: 19.99$

The whole journey of the course is all about R Programming first, then Machine Learning including the concept of Data Science using R programming. Flexibility and ease are the desire of every Data Scientist or machine learning expert, but because of steep learning, student get tired and overwhelmed. The journey of machine learning especially got confused due to Math and Statistics behind! R and Python are interchangeably used in the industry where R has its own strengthen with respect to the statistical packages support on it. In the modern world where the Data is around everywhere study of R with Machine Learning play a tremendous role to clean and filter out the data to make it useful for future predication. In the Job market if you know R programming your chances are high to get job as compare to other languages in the filed of statistics and machine learning. The Course designed is such a way, that will be useful for all level specially student who are learning and under working on it. This separate session in Module I is all about R programming including Theoretical and Practical work using R Studio IDE, whereas in Module II, the individually session of supervised and unsupervised machine learning algorithm will be discussed. The discussion of each session based on live and real life example and dataset to make you understand in better way. The Course has Two Module, in Module-I you will learn: What is R, Installation, HELLO WORLD! Variable and Data types Operators in RData Structure Atomic vector All Operations List   All Operations Array   All Operations Matrices   All Operations Data Frame   All Operations Factors   All Operations Control structures (if statements / Family)Switch statements Loops (For, while, repeat)Jump Statements Functions & Types Data Visualization Advance Data Visualization using ggplot2. In Module-II you will learn: Machine Learning Introduction and Dataset Regression Linear Regression Multiple Linear Regression Polynomial Regression Support Vector Regression Classification Logistic Regression Support Vector Classification K Nearest Neighbors Classification Clustering Hierarchical Clustering Algorithm K Means Clustering Algorithm Association Apriori Algorithm Eclat Algorithm F-P Growth Algorithm In Final words, the Couse is useful for all skill level, even you do not know about any programming language and Statistics behand it. As we know Learning never end so be focus on skill and technology to make your life comfortable and easy! Now, I will be very excised to see you in the course. Regards, Fahad Hussain