This Data Analytics Course provides you the analytical skills you need to open the door to a new career as a Data Analyst. Data modeling has become a pervasive need in today's business environment. Often the quantity of data you would need to process goes beyond the capabilities of spreadsheet modeling. As a result of this, the statistical programing language R offers a strong alternative.
No programming experience is required for this course. The course is targeted at beginners who want to find out the way to import, clean, manipulate, visualize and analyze data in R. After this course, you'll be able to conduct data analytics tasks by yourself and gain insights from data using different statistical techniques.
- This course does not require sophisticated mathematical knowledge or extensive programming experience.
- No programming experience is required for this course
Module 1: Getting Started with R
Module 2: Exploratory Data Analysis
- R Overview
- Vectors in R
- Lists in R
- Matrices in R
- Subsetting in R
- Packages in R
Module 3: Hypothesis Testing
- Importing Data into R
- Data Manipulation and Transformation
- Data Visualization with GGplot
- Apply Family of Functions
- Handling Missing Values
Module 4: Linear Regression
- One sample T-Test
- Two Sample T-Test
- Two Sample Paired T-Test
- Analysis of Variance
- Post-Hoc Test
Module 5: Logistic Regression
- Introduction to Linear Models
- Assumptions of Linear Regression
- Simple Linear regression
- Multiple Linear Regression
- Application of Linear Regression
- Introduction to Logistic Regression
- Odds and Odd Ratio
- Application of Logistic Regression
Who Should Take this Course?
- Anyone who aspires to work in a data-centric field such as: Data Science, Data Engineering, Data Analytics, Business Analytics, etc..