Complete Data Science using R programming
Description
This course facilitates major part of a data science project activity. The program is divided into three major parts. Part One demonstrates the core syntactical skills needed to code and program using R programming. It covers writing basic to advanced R programs for data science. Part two demonstrates the needed statistics to understand the interpretation that comes out of a statistical data analysis and model making. It helps tune your machine learning model parameters better. The third part is machine learning, you will use previous learnt two parts to build predictive engines for business decision making, classifiers to automate a mundane task and finally a recommendation model to up sell & cross sell business products to consumers.
TECHNOLOGY USED: R core programming, machine learning for R
What Will I Learn?
- Learn to program using R for data science
- Learn to create data structures for machine learning in R
- How to render visuals charts and their interpretations in R
- Use Native statistics modules in R
- Build data reasoning
Topics for this course
Introduction to the Course
How to use R to explore and visualize data
How to use randomization and simulation to build inferential ideas
How to effectively create stories using the ideas to convey information to audience
Introduction to data sources in R (built-in)
What is a data science pipeline?
Introduction and Installation
Data Structures in R
DESCRIPTIVE STATISTICS
DATA MANAGEMENT
INFERENTIAL STATISTICS
MACHINE LEARNING
About the instructors
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