Course Overview
Welcome to ReDI School! We really appreciate that you are part of our community. In this page, you'll find an overview of the course. By volunteering, you contribute to our main goal: help our students gain the necessary skills to find a job in tech. ReDI School has now helped over 17.000 people advance their tech skills. This is only possible with the support of our volunteers <3
ReDI Students
Our student community brings together people from over 138 countries. Your course won't be different. Your students will come from a wide range of countries. They also come from diverse professional backgrounds - some are currently unemployed or underemployed, while others are students looking to prepare for their careers. With an average age of 32, many of our students hold a university degree and have several years of work experience. What unites all students is their passion for technology and their aim to build a career in the tech industry.
❤️ Thank you for supporting our students as they take another step in their journey! To learn more about ReDI students and our community, visit About ReDI School.
Curriculum
The Data Analytics Course is designed for students who have a basic understanding of Python and want to deepen their skills in data manipulation, SQL, statistics, and visualization. Each cohort consists of 25 students who meet twice a week (Mondays and Wednesdays from 19:00-21:00). The course follows a project-based learning approach, ensuring that students gain practical experience with industry-relevant tools.
Students progress through three key learning phases:
SQL & Data Processing – Covers database queries, joins, and aggregations, along with an introduction to Looker Studio for visualization.
Python for Data Analysis – Introduces Pandas for data manipulation, statistical methods, and exploratory data analysis (EDA).
Final Capstone Project – Students apply their knowledge by analyzing a real-world dataset, creating data visualizations, and presenting their findings on Demo Day.
Each phase includes weekly exercises, hands-on projects, and a recap week to reinforce learning before moving to the next stage.
Structure
The weekly schedule consists of two regular classes. Monday begins with a review of the previous week’s content. Teachers provide feedback on completed assignments and discuss solutions. Students work on hands-on exercises to apply SQL or Python techniques to datasets. On Wednesday, teachers introduce new data analytics topics, such as SQL queries, statistical concepts, or visualization techniques. Students engage in hands-on coding demonstrations and guided exercises. The session concludes with the assignment of the weekly homework task.
Between sessions, students are expected to dedicate 10-12 hours per week to coding assignments, and independent study.
Sessions
The course has two online sessions per week. For on-site events, check out On-site Activities. The session format differs from what you might have seen before.
Roles
As a session owner, you lead the Input session. You introduce the milestone of the week and the relevant concepts to work on it. You prepare the session and coordinate with the teaching assistant.
4 hours per week
As a teaching assistant, you support the session owner in the input session. You open the Zoom call, track attendance, help answer questions, and provide support in break-out rooms.
3 hours per week
As a backup teacher, you are available and ready to jump in the case one of the teachers assigned for the day should have issues, or get sick. As a backup teacher, you don’t need to attend the session unless an emergency arises.
2 hours per week
As a homework reviewer, you correct assignments between Monday 7pm and Wednesday. You do this asynchronously and do not need to attend any sessions.
3 hours per week
On-site Activities
We are organizing on-site activities in our three main locations. Find out more below.
We invite you to four on-site community events throughout the semester if you are located in Berlin and the surrounding. The Onboarding will also take place in person in Berlin. You are more than welcome to join!
Conclusion
We hope that by reading this, you have a better idea of the course and what it means to volunteer at ReDI. Let's explore the Timeline now 📅.
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