Data Science and Machine Learning with R
Training TypeLive Training
CategoryData & Analytics
About the Course
Interested in the field of Data Science? Then this course is for you!
This course is designed by industry experts and help it will help our students to grow on the field of Data Science and Machine Learning
We will help our students to learn about Data Science step-by-step with ease.
This course is an exciting way to learn Data Science where we will talk about the technicality as well as statistics behind the concepts. The curriculum is structured the following way:
Part 1 - Data Pre-processing
Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Decision Tree Regression, Random Forest Regression
Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
Part 4 - Clustering: K-Means, Hierarchical Clustering
Also, in this course you will get a chance to work on the practical exercises which are based on real-life examples.
Help students to feel confident about the concepts of Data Science and Machine Learning
Students will get the detailed knowledge of R
Mathematics behind the Machine Learning concepts
Who is the Target Audience?
Those who are interested in Data Science and Machine Learning.
Students with basic understanding of maths
Students with basic knowledge of Data Science and Machine Learning
Any students in college who want to start a career in Data Science.
Any data analysts who want to level up in Machine Learning.
Any people who are not satisfied with their job and who want to become a Data Scientist.
Any people who want to create added value to their business by using powerful Machine Learning tools.
This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science.
Data Split (Test and Training Set)
Simple Linear Regression
Multiple Linear Regression
Decision Tree Regression
Random Forest Regression
K Nearest Neighbours (K-NN)
Support Vector Machine (SVM)
Decision Tree Classification
Random Forest Classification