Skip to main content
STATISTICS AND R

14.06.2023 |

In this 4-week self-paced Data Science course in English, you’ll dedicate 2 to 4 hours per week to build your skills. The course, designed for intermediate learners, offers the option to audit for free or obtain a Verified Certificate for $129

You will delve into essential statistical concepts, including random variables, distributions, inference using p-values and confidence intervals, exploratory data analysis, and non-parametric statistics.

Due to the diverse educational backgrounds of the students, the series is divided into seven parts. You have the flexibility to enrol in the entire series or choose individual courses that align with your interests.

Course description

We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation. Problem sets requiring R programming will be used to test understanding and ability to implement basic data analyses. We will use visualization techniques to explore new data sets and determine the most appropriate approach. We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches. By using R scripts to analyze data, you will learn the basics of conducting reproducible research.

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

Details

Target audience

Digital skills for ICT professionals

Digital technology

Digital skills

Big Data

Level

Middle

Format of the training

Online

Training fee

Free training

Duration of the training

Type of training

Language of the training

English

Country providing the training

Other

Classification

Single opportunity

Leave a Reply