Develop

Elements of

Data Science

35 hours
390 CHF / month

In this course you will understand how to automate data gathering, analysis and reporting to gain insights, contribute to strategic discussions and make data-driven decisions. You will gain practical experience across the data science pipeline by learning the basics of the coding language R and the Tidyverse. You will work with tabular data and by the end of it, you will be able to create reports using R markdown where code and text smoothly coexist.

Ready to start learning?

Enroll now

Join our Discovery Webinar

This complimentary online session will provide a high-level overview of how to automate data to gain insights and how to produce data-driven storytelling, including an overview of the online courses available to gain these sought-after skills.

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Why you should take
this course

Data is information. Acquiring strong data literacy by knowing how to work with data will make you a valuable asset for any employer in a data-driven world.

Organizations need
employees who
understand data

Companies are increasingly looking for data-savvy professionals. In fact, a lack of data skills is a major challenge for 44% of companies, while 69% of employers would choose a candidate with data skills over one without.

Data literacy is
now a job requirement

As more companies shift to a data-driven business model and with every department using data for business analytics, basic data literacy is becoming a requirement across functions and levels. This is not just for career advancement, but increasingly for job security.

Who is it for?

Elements of Data Science is for those who already work with structured data—spreadsheets and data tables—and who need to understand how to automate data to gain insights, contribute to strategic discussions and make data-driven decisions.

Learners who successfully complete the Elements of Data Science course can choose to continue their upskilling journey with the Foundations of Data Science course by starting the course where they left off in Elements of Data Science (completing the remaining 1115 hours instead of 150 hours).

" The EPFL brand caught me. The content was interesting. The price was good as was the flexibility of learning remotely from home. The model is just right. "

Bartosz, EPFL Extension School Learner

Course curriculum

The Elements of Data Science course gives you the essential knowledge, vocabulary and skills for data management and communication. With video trainings, written lessons and hands-on exercises, you’ll gain a broad understanding of the tools and techniques used to work with data.

What is Data: Learn about data types, structures and frameworks
Interacting with Data: Understanding how data is used and how to use data
Storing & Structuring Data: Importing, cleaning and exporting tabular datasets
Cleaning Data: Working with messy or incomplete data sets
Analyzing Data: Gaining insights on data using tables and visualisation
Visualizing Data: Best practices and tools for data visualization and presentation, with ggplot2 and R Markdown

These course details are subject to change; please refer to the program outline at the time of registration.

Prerequisites

This course is taught at beginner-level. You should have the following tools, skills and abilities prior to registering for this course:

English at B1 level
A computer with a webcam, microphone and a minimum internet connection of 2Mbps download / 512kbps upload, enabling you to stream videos with sound and to effectively participate in video chats