Most important Resources

Course Material

Weekly Class Schedule

Teaching Roles Overview

About ReDI

• Find out more about ReDI: About ReDI

• Find out about the career services ReDI offers: Career Services

Help

• Check out: I can't teach tonight, I am dropping out, I feel uncomfortable.

• Reach out to Caro, your Course Manager, for help via Slack.

❤️ Thank you for supporting the ReDI students ❤️

Welcome!

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

Our Students

• Come from 138+ countries with diverse professional backgrounds

• Average age: 32, many with university degrees and work experience

• Data Circle Students have prior knowledge in Python, Data Analytics, and/or Machine Learning

• A mix of ReDI alumni and new students with varying skill levels

• United by their passion for tech and career growth goals

❤️ 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.

Learning Concept

The Data Circle takes a hands-on approach to learning through realistic projects. Instead of traditional lectures, students work actively on data analysis or machine learning projects in small teams. This means students learn by doing - working on their code, analyzing data, and solving problems independently. The guides (you) support and steer students in the right direction. Nonetheless, we ask the students to be the main drivers behind the project. Each team tackles a semester-long project in three sprints, allowing students to apply their skills to real challenges while receiving regular guidance and feedback. This approach helps students build not just technical skills but also the independence and problem-solving abilities needed for a career in data science.

You can read more about what we share with the students on the applicant hub.

Project Structure

Timeline

1. Setup Phase (Weeks 1-3)

   • Team formation and social activities

   • Technical setup

   • Project selection

   • Git & Github workshop

2. Project Sprints (Weeks 4-13)

   • Three 3-week sprints

   • Each sprint includes planning, development, and review

3. Final Phase (Week 14)

   • Project completion

   • Demo Day preparation and presentations

Sessions

Two weekly online sessions (Tuesday & Thursday, 19:00-21:00):

• Brief updates in the main room (15 min)

• Team breakout rooms for project work (90 min)

• Regular check-ins with Guides

Team Structure

• 2-3 students per team (self-formed groups)

• Focus on collaboration and peer learning

• Regular guidance from volunteer mentors

Deliverables

Each sprint requires:

1. Code on GitHub

2. Documentation

3. Sprint presentation

4. Progress report

Activities Description

Best Practices

Project Management

• Light agile ceremonies

• GitHub for project tracking

• Regular team check-ins

Support Activities

• Stand-ups: Quick status updates and blocker identification

• Planning: Ensure meaningful work distribution

• Demos: Showcase progress

• Retros: Review and improve process

• Ad-hoc lessons on specific topics as needed

On-Site Activities

We are organizing on-site activities in our three main locations. Find out more below.

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 📅.

The Circle is all about projects. That's why we don't have a lot of content to share, but rather project guidelines and material. For Spring 2025, we aim to review the project ideas and enhance the structure of the project guidelines we share with the students.

Previous Projects

• Previous Projects include Stack Overflow data and Twitter Data (Project Introduction).

• The projects lacked a clear goal of what the students could achieve with it. This is what we want to improve for Spring 2025.

Project Framework

Project Requirements

• Goal - Each project needs a clear, achievable goal - either a product to build or a specific problem to solve

• Structure - Projects should be pre-structured, including deliverables, so that students clearly understand what to deliver

• Dataset - Data sets must be pre-validated to ensure feasibility and quality

Project Guidelines

• We aim to create project guidelines in a GitHub repo that include a structured project roadmap and a breakdown of the complex tasks into more manageable steps.

• Guidelines should include:

  • Description

  • Technologies

  • Dataset

  • Deliverables

  • Evaluation Criteria

  • Plagiarism & AI

  • Resources

• An example we can use as a template: ML Zoomcamp Projects

Spring 2025 Project Ideas

1. Flu Shot Learning (DrivenData)

   • Predict H1N1 and seasonal flu vaccine adoption

   • Focus: Classification and healthcare analytics

   • Flu Shot Learning: Predict H1N1 and Seasonal Flu Vaccines

2. Water Table Analysis (DrivenData)

   • Data mining for water pump functionality prediction

   • Focus: Feature engineering and classification

   • Pump it Up: Data Mining the Water Table

3. Disaster Tweet Classification (Kaggle)

   • NLP analysis of disaster-related tweets

   • Focus: Natural language processing and text classification

   • Natural Language Processing with Disaster Tweets

4. Store Sales Forecasting (Kaggle)

   • Time series analysis for sales prediction

   • Focus: Time series forecasting and business analytics

   • Store Sales - Time Series Forecasting

5. Stock Market Analytics (ML Zoomcamp)

   • Build a stock market analysis and prediction system

   • Focus: Financial data analysis, time series modeling, deployment

   • Includes working with real market data and creating an end-to-end ML pipeline

   • Bonus: Opportunity to build a web interface for predictions

   • Stock Market Analytics ML Zoomcamp

6. Your Ideas! Feel free to propose more ideas in the planning session

The projects for Spring 25 are not set, and we are keen to discuss them with you. Thanks for reading through them. Let's complete the self-onboarding now: Complete your Self-Onboarding

The Circle is all about projects. That's why we don't have a lot of content to share, but rather project guidelines and material. For Spring 2025, we aim to review the project ideas and enhance the structure of the project guidelines we share with the students.

Previous Projects

• Previous Projects include Stack Overflow data and Twitter Data (Project Introduction).

• The projects lacked a clear goal of what the students could achieve with it.

Project Framework

Project Requirements

• Goal - Each project needs a clear, achievable goal - either a product to build or a specific problem to solve

• Structure - Projects should be pre-structured, including deliverables, so that students clearly understand what to deliver

• Dataset - Data sets must be pre-validated to ensure feasibility and quality

Project Guidelines

• We aim to create project guidelines in a GitHub repo that include a structured project roadmap and a breakdown of the complex tasks into more manageable steps.

• Guidelines should include:

  • Description

  • Technologies

  • Dataset

  • Deliverables

  • Evaluation Criteria

  • Plagiarism & AI

  • Resources

• An example we can use as a template: ML Zoomcamp Projects

Spring 2025 Project Ideas

1. Flu Shot Learning (DrivenData)

   • Predict H1N1 and seasonal flu vaccine adoption

   • Focus: Classification and healthcare analytics

   • Flu Shot Learning: Predict H1N1 and Seasonal Flu Vaccines

2. Water Table Analysis (DrivenData)

   • Data mining for water pump functionality prediction

   • Focus: Feature engineering and classification

   • Pump it Up: Data Mining the Water Table

3. Disaster Tweet Classification (Kaggle)

   • NLP analysis of disaster-related tweets

   • Focus: Natural language processing and text classification

   • Natural Language Processing with Disaster Tweets

4. Store Sales Forecasting (Kaggle)

   • Time series analysis for sales prediction

   • Focus: Time series forecasting and business analytics

   • Store Sales - Time Series Forecasting

5. Stock Market Analytics (ML Zoomcamp)

   • Build a stock market analysis and prediction system

   • Focus: Financial data analysis, time series modeling, deployment

   • Includes working with real market data and creating an end-to-end ML pipeline

   • Bonus: Opportunity to build a web interface for predictions

   • Stock Market Analytics ML Zoomcamp

6. Your Ideas! Feel free to propose more ideas in the planning session

How do I share material with students?

We use Google Classroom to share material with the students. Please have a look here:

How do I create more engagement in class?

Best practices for teaching?

More material, feedback, or ideas?

If you find good material, ReDI could use, and if you have feedback or further ideas, feel free to contact us via Slack or email (dcp@redi-school.org).

Teaching Method: I Do, We Do, You Do

The "I Do, We Do, You Do" method is a teaching method designed to help students learn new concepts by first observing, then practicing with guidance, and finally working independently.

• I Do: The teacher demonstrates the task while explaining the steps and thought process aloud. This stage is about modeling the correct way to approach the task and highlighting key concepts and techniques.

• We Do: The session owner walks the students through an activity. The students follow along (code or design along). This collaborative stage allows students to apply what they've seen with support, ask questions, and receive immediate feedback.

• You Do: Students work independently on the task. This stage allows them to practice the skill on their own.

Example: Introducing Javascript

• I Do: The teacher introduces JavaScript and demonstrates a simple script that shows an alert when clicking a button. Key concepts like variables, functions, and events are explained briefly.

• We Do: The teacher walks the students through creating a function that changes a heading's color when clicking a button. The students follow and code along. The teacher shares their screen and gives the students time to code along. Together, the teacher and the students write the function, select the element, and add an event listener, with the teacher guiding and asking questions to engage students.

• You Do: Students independently write JavaScript to change the text of a paragraph when a button is clicked in a breakout room. They practice using variables, functions, and event listeners and then share their work for feedback.

Tips and Tricks

• Context before content - We experienced that explaining why a concept is important helps a lot in understanding what the concept is about. Why should you learn this concept? Try to give the context. Maybe explain where you use it in your daily work life. Or explain how this concept can help to solve a bigger problem

• Engage with Students: Ask questions to check understanding. Use their names and keep the tone friendly and encouraging.

• Be Prepared but Flexible: Have a plan but adapt based on student needs.

• Feedback is Key: Provide constructive feedback to help students improve. Celebrate small wins to keep motivation high.

More Resources

• Watch this video on how to run the Regular Class.

• Ice Breakers and Energizers - Do you want to start the session with an energizer? Have a look at Class Engagement

🎤 Class Demo Day

The Class Demo Day is an internal presentation day held in the final week of the course. Each student (team) presents their project to their classmates and teachers. It’s a supportive environment focused on:

• Showcasing the project

• Practicing technical presentations

• Sharing challenges and lessons learned

• Celebrating the team’s work

🧑‍🏫 This day helps students build confidence and receive feedback from peers and instructors.

🎉 Demo Day

The Demo Day is a public, on-site event where selected student teams present their projects to the broader ReDI community, including partners.

• The event highlights excellence, creativity, and collaboration

• Students present in a more formal setting with networking opportunities

• It’s a moment of celebration and recognition for everyone involved

📅 Timeline (Spring 2025)

📌 Attendance and presentation at the Class Demo Day are required for students to receive a certificate.

🗣️ Presentation Guidelines

To help learners prepare their pitch, here’s a suggested format:

• Length: Max. 5 minutes

• Mode: Slides or Live Demonstration

• Proposed Structure:

  1. Intro – What’s the project, and what problem does it solve?

  2. Demo – Show the live website

  3. Challenges & Learning – What went well? What was hard? What did you learn?

🧑‍🏫 Encourage learners to rehearse and help each other practice!

🧾 Certification Requirements

To receive a ReDI certificate, learners must:

• Attend at least 80% of the course

• Complete and present the Project

• Attend the Internal Class Demo Day

• Complete 2 IBM SkillsBuild Courses

🤝 Class Culture & Support

💬 “We grow by doing, and by helping each other.”

• Foster a positive, collaborative learning

• Dedicate class time to mentoring, code reviews, and feedback

• Celebrate all wins—big or small—as students build real web apps

🎉 Let’s end the Circle by cheering each other on!

Overview

In the Circle, guides support students in building real-world projects. Rather than traditional teaching, guides help students develop practical skills through hands-on project work and agile development practices.

Guide Roles

As a guide, you basically have two roles in one :) You support the students as a product manager and as a mentor in the sessions.

1. Product Manager

• Runs team meetings (standups, planning, refinement)

• Prepares and prioritizes tasks for sprints

2. Mentor

• Conducts code reviews

• Provides one-on-one support during work sessions

• Helps students discover solutions independently

• Identifies areas where students may need additional support

Session Structure

Regular Sessions (Monday/Wednesday, 19:00-21:00)

• Standup meetings (15 minutes)

• Work time with active mentoring

• Optional micro-lectures as needed

• Team-based project work

Sprint Cycles (3 weeks)

• Sprint planning and kickoff

• Regular refinement sessions

• Demo presentations

• Retrospectives

Key Responsibilities

Before the Session

• Allocate a responsible to track attendance

During Sessions

• Facilitate team meetings

• Provide hands-on guidance

• Review code and give feedback

• Support student collaboration

Between Sessions

• Answer questions via Slack

• Prepare for upcoming sprints

• Share relevant resources

Best Practices

Supporting Students

• Encourage self-learning

• Guide rather than provide direct solutions

• Foster team collaboration

• Maintain consistent communication

Project Management

• Help break down tasks into manageable pieces

• Ensure clear acceptance criteria

• Monitor progress and address blockers

• Facilitate effective team discussions

Resources

• Student Hub - Gitbook

• Team communication via Slack

• Additional support from ReDI React teachers when needed

Semester Outline

• Weeks 1 - 3: Tools configuration, development environment setup, project management process overview

• Remaining weeks: Split into 3-week sprints. Each sprint contains a focus topic according to the project type that needs to be completed. Milestones will break down the project into smaller deliverables. Expect weekly homework (project work) during this period.

• Demo Day: At the end of the semester, each team will present their projects to the audience of ReDI course community members.

Weekly Sessions

Sprint Outline

More Information about the Semester & Sprint Flow

Activity Description