Introduction To Data Analysis Using R

This is the second course in the Data Analyst R pathway. This course expands upon the programming concepts and techniques covered in Intro to R. It will also teach you how to use the most common data structures in data analysis. This information is crucial for data professionals.

This is the third course of our Data Analyst in Rails path. This course builds on the R programming skills that you have acquired in the previous two courses and allows you to perform more complex operations in R.

This course will teach you about control flow, including if-else statements and conditionals. Next, you will learn about functional programming and functions.

Iteration will be …

This course is part of the Data Analysis in R career path. This course will build upon the skills and knowledge that you have acquired in the previous three courses.

First, you'll learn string indexing techniques and concatenation techniques for understanding, processing and analysing text data. You will use the lubridate package to overcome the unique problems associated with working in R …

Data science is more than just being able to analyze data. To communicate your insights and help others understand them, you must be able create captivating visualizations.

Although data cleaning is not the most glamorous task in data science it is a necessary requirement for anyone wanting to work in a data-related area.

Databases are everywhere. Databases are everywhere. Every day data and information flow in and out of databases. This SQL fundamentals course is a great place to start learning SQL. This course explains the interdependencies between databases and helps you learn new skills. This interactive course is suitable for all levels of SQL knowledge.

You'll be able from the very beginning to execute …

Our SQL Intermediate in R course will build on the SQL skills that you have acquired in the SQL Fundamentals course. You'll be confident that you can answer business questions using SQL by the end of this course.

The Data Analyst in R course will allow you to use the R programming skills that you have acquired to unlock new data sources: APIs.

The course ends with a challenge that will help you understand how web scraping works across different websites. Next, you will be guided through a project that will allow you to add your own spin on web-scraped data analytics.

Our Statistics Fundamentals course will give you an overview of statistics and show you how it is used in data science.

Our statistics intermediate course for R users will teach you how to summarize distributions using mean, median, or mode. We'll also cover when and how to use them. Finally, we will discuss which statistic provides the most information about a distribution so you don't just understand how to apply them but why.

Our Probability: Fundamentals course with R will give you a critical understanding of the mathematical concepts underpinning a lot data science work.

Our Hypothesis Testing in R course will teach you advanced statistical concepts like significance testing and multi-category, chi-square testing to improve your data analysis.

This course will build upon what we have learned and teach new techniques to improve our ability to estimate probabilities. The entire course will focus on how to calculate probabilities using certain conditions, hence the term conditional probability.

Linear Regression Modeling with R Course teaches you the basics of linear regression and how to use it for predictions and inferences.

Both data analysts and data scientists report that there are "sexier" aspects to their jobs, but most of their time is spent cleaning and preparing data.

Our Hypothesis Testing: Fundamentals course will teach you advanced statistical concepts like significance testing and multi-category Chi-square testing to make your data analysis more robust and powerful.

You will learn the basics of machine learning in our Introduction to Machine Learning with R course. We will cover concepts like K-Nearest Neighbors Algorithms (KNN), and discuss error metrics such the Mean Squared Error, and Root Mean Squared Error. Hyperparameter optimization is a technique that optimizes machine learning algorithms to improve the accuracy and performance. You'll also learn …

This course will cover advanced SQL concepts such as summary statistics and aggregate functions. These concepts are crucial in helping learners to perform various useful functions to gain insight from large datasets.