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  • What is the course about?
  • Why should you take this course?
  • Learning Format
  • Weekly Homework
  • Course Outline
  • A typical week
  • Onsite Activities
  • After the course
  • How to Graduate from the Course?
  • How to apply?
  • Sign up to Join Open Day
  • Complete Prework
  • Hand in Application Form
  • Interview (25.08 - 29.08)
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  1. Data / AI Track

Data Analytics

PreviousPrework - Python FoundationsNextPrework - Data Analytics

Last updated 8 days ago

What is the course about?

Do you want to understand and work in Data Analytics? Then this course is for you! Join us to learn how to analyze, interpret, and present data using powerful tools like Python and SQL. You deepen your Python knowledge and apply data analysis techniques.

Through hands-on projects and real-world examples, you’ll gain practical skills to work with datasets, uncover insights, and tell compelling stories with data. Join us and take your first step toward a career in the growing field of data analytics!

Course Details

  • Classes: Monday and Wednesday, 19:00 - 21:00

  • Time Invest: 15 hours per week

  • Timeline: Start Date is 08th of September 2025, End Date is 08th of December 2025 (14-weeks)

  • Hybrid: Certain events take place in person in the following locations: NRW, Berlin, Hamburg.

Why should you take this course?

  • You learn:

    • Python for Data Analysis: Use Python to clean, analyze, and visualize data.

    • Data Tools: Work with Pandas, NumPy, and Matplotlib for efficient data manipulation and visualization.

    • SQL Basics: Query databases and extract insights.

    • Statistics Fundamentals: Learn descriptive and inferential statistics for data interpretation.

    • Visualization Techniques: Create clear charts and graphs to present data.

  • Your Start - This course is the perfect starting point for your journey toward becoming Data Analyst or Data Scientist. By the end of the course, you will have a solid foundation in Python, a GitHub portfolio showcasing your projects, and a ReDI Certificate. Afterward, you can advance your skills by enrolling in the Machine Learning & AI course.

  • Final Project: Apply skills to real-world datasets and complete data analysis projects. You have the chance to present your project to your colleagues in the course.

  • Industry Experts - The teachers are volunteers from the industry. They are experts in web development and will help you start your journey toward a tech career!

Learning Format

In the two weekly sessions, teachers introduce key concepts to the students and practice them with small exercises and live coding. Next to the two sessions, students are asked to apply the newly learned concepts in weekly homework and a final project.

Weekly Homework

Every Wednesday, students will receive homework to be submitted by Sunday evening. Homework review is part of the Monday session. There is a requirement for students to complete 80% of the homework throughout the course in order to graduate. Homework is not graded.

Course Outline

The Course Outline may change before the start.

Week
Topic
Content

1

Kick-Off

Teachers & Students get to know each other

2

Preparation

Students learn about the tech setup

3

SQL

Introduction to SQL and Bigquery SQL in BigQuery - Basic functions and Joins. Introducing Looker

4

SQL

Advanced (Date, Aggregate and Window Functions) Visualization theory and practice.

5

Pandas

Intro to Pandas

6

Pandas

Transformation

7

Pandas & Preject

Students work on a small project (preject) Pandas data cleaning & missing values

8

Statistics

Data Representation & Tools Statistics

9

Statistics

Bayesian Statistics A/B Testing

10

Career Week

Students can participate in a variety of career workshops.

11

Recap

Key concepts are reviewed

12

Final Project

Students implement what they have learned in a final project.

13

Final Project

Students implement what they have learned in a final project.

14

Demo Day

Students present their final project.

A typical week

Monday 19:00 - 21:00

Every Monday from 19:00 to 21:00, you have an online session in which you discuss your homework and where you will be introduced and practice new concepts.

Wednesday 19:00 - 21:00

Every Wednesday from 19:00 to 21:00, you have an online session where the volunteer teachers introduce you to new concepts. They will share the weekly homework with you in this session.

Thursday - Monday

You work on your weekly homework. That means you will be coding hands-on by yourself! If you run into problems, you can contact your class on Slack. You upload your homework before the Monday session.

Onsite Activities

Based on your location there are different on-site activities. Find out more below.

If you are located in Berlin and surrounding, we invite you to four on-site community events throughout the semester.

If you are located in NRW, we invite you to four on-site community events throughout the semester. The Demo Day will also take place in person in Düsseldorf.

If you are based in Hamburg, you will join the course four times in person: Onboarding, two regular course sessions, and Demo Day.

After the course

  • You have built your own Data Analytics project (ML or data analysis)

  • You know how to start analyzing a dataset, and about Data Science Tools (pandas, sklearn, ...)

  • You can continue learning with our Data Analytics alumni group

  • You can start looking for internships or continue learning in the Machine Learning & AI course or in the Data Circle.

How to Graduate from the Course?

To graduate and receive the ReDI Certificate, we ask you to:

  • Submit 80% of homework and a final project

Is this course for me?


How to apply?

1

Optional for current ReDI students. Join us to find out more about the courses and requirements.

2

Complete it before the application deadline. Start early! The Prework might take up to 20 hours in total. The deadline is stated in the email with the link to the application form.

3

Hand in Application Form

We ask you for the link to your completed prework in the application form.

4

Interview (25.08 - 29.08)

Depending on your course, you may be interviewed by the teachers.

5

Onboarding (08.09)

Your course starts!

Complete Your Prework


FAQ

Not sure which track you are interested in?

If you don't have any experience with tech, apply to our introduction course: HTML & CSS, Infrastructure Basics, Python Foundations or UX/UI Design Bootcamp. To understand which tech career interests you, check out the following link:

Not sure which course level to apply for?

Attended 80% of the sessions (We have a )

you are committed to working in the

to Join Open Day

Complete

Start applying now by completing the !

Check out the of the different levels. If you are a little bit challenged but able to complete a Prework, then the level is right for you.

📊
camera on policy
ReDI style
Sign up
Prework
Data Analytics Prework
How to choose a tech career?
Career Changer Playbook
Prework
More information
Career Tech Guide

Timeline

Month
Topics
Description

June

Open Days

Join Info Sessions to get to know ReDI School & Fall 2025

July

Open Days Application Open

Join Info Sessions to get to know ReDI School & Fall 2025 Complete the application form and finish your prework.

August

Student Interviews

Students are interviewed for the course.

September

Kick-Off Course runs

We kick-off the semester.

October

Course runs

You join the sessions and work on your project.

November

Course runs

You join the sessions and work on your project.

December

Demo Day

Present their final project.

Still unsure what to do..?

You tried our - and didn’t find the answer you needed? Please make sure to review the Applicant Hub carefully, your answer is likely there. Still stuck? Check our . Alternatively, you can reach out to us via email: .

🤖 Unsure about the course?

Try out our (you need a ChatGPT account to access it). Please keep in mind that the Chatbot might make mistakes. You can find all the correct information on the Applicant Hub.

💬
AI Bot
FAQ Page
dcp@redi-school.org
AI Chatbot on Open AI

ReDI Style

This course is about active participation. You will be asked to work independently on weekly homework to apply your newly learned skills. You are in charge of your learning journey. Are you ready to work hands-on and participate actively in the sessions? Then join us!