Welcome to the teaching team! Here's where you can find all the materials you'll need to teach in this course. Your feedback and contribution are highly appreciated to improve the content further.
Colab Files
We work with Notebook files in the IDE Google Colab. You can find the colabs in Drive.
Homework Colabs
You can find Homework colabs in the drive. However, not every week might have homework yet! In that case, browse the archive and further resources or create a new homework colab.
Student Hub
The student hub helps students navigate the course. We aim to structure the hub as a knowledge base, meaning that concepts of the course are explained in the hub.
GitHub Repo with Notebooks from ReDI Berlin and GitHub Repo from Hamburg - Feel free to reuse the material. If you use the material please add it to the Google Drive folder so that we keep all material in one place.
If you taught in the past semester at ReDI, you might have existing material you would like to reuse. That is fantastic! Please add the content to the drive. You can also reach out to Julian on Slack or via email (julian@redi-school.org) for further questions on how to add or use prior material.
We are aware that the material is not perfect. Probably you would like to change and improve it! Please do so! As the session owner, you can structure the session as you wish. The existing material is a suggestion. By changing the material, you help us improve the content. Here is an explanation of how to change it:
Google Drive - Add or change material on Google Drive - To access Google Drive content, you need to be enrolled in the Google Classroom. If you are not, ask your Course Manager.
Gitbook - Your changes are also highly welcome in the Student Hub Gitbook. Get editor access to Gitbook to make changes to the student hub. Please ask your course manager about it.
We use Google Classroom to share material with the students. Please have a look here:
Google ClassroomIf you find good material, ReDI could use, and if you have feedback or further ideas, feel free to contact Julian via Slack or email (julian@redi-school.org).
We provide additional tools that you can use to engage students more in your sessions! At ReDI, we like to use the following tools and icebreakers:
Create live polls, word clouds, and Q&A
Perfect for:
Icebreakers: Ask students about their expectations or background knowledge.
Quick polls: Check understanding of a topic in real-time.
Exit tickets: Gather feedback at the end of a session.
Login credentials in teachers' Slack channel
Quiz-based learning with competitive elements
Perfect for Revision & Recaps - You create a quiz, and students participate live in class via browser or cell phone.
Login credentials in teachers' Slack channel
You can use quick icebreakers at the start of your sessions to energize participants, build connections, and create an engaging and interactive learning environment. Here is a list of icebreakers. They shouldn't take more than 5 minutes to run.
Description: Participants share three statements about themselves—two true and one false. The group has to guess which one is the lie.
How to Run: Use breakout rooms for smaller groups or let everyone participate in the main room.
Objective: Participants get to know each other in a fun way.
Description: Give participants a list of items to find in their home within 1-2 minutes (e.g., something red, something that makes noise).
How to Run: Ask them to bring the items back to the camera and share a quick story about one of them.
Objective: The activity is an energizer.
Description: Pose a question or statement (e.g., "How are you feeling about today’s session?") and ask participants to respond using emojis only.
How to Run: Use the chat in Zoom.
Objective: It is an easy way for participants to share how they are doing.
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.
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.
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
The Final Project is the highlight of the Machine Learning & AI course and a powerful opportunity for learners to apply what they’ve learned to a real-world dataset or problem. This phase challenges students to build, train, and evaluate machine learning models—while telling a compelling story about their findings.
After completing the main curriculum, students transition into the final project phase, where they work in small teams to explore a machine learning problem from end to end.
Learners will:
Work individually or in teams (up to 3 people)
Select a dataset or receive one from the teaching team
Define a clear machine learning goal
Clean and preprocess the data
Train, evaluate, and interpret ML models
Present findings in a clear and insightful way
💡 Goal: Build a small, focused machine learning project that shows off practical understanding and supports portfolio or career goals.
Each project must include:
A defined machine learning objective (e.g. classification, regression, clustering)
A well-documented Jupyter Notebook or py files
Use of libraries such as scikit-learn, pandas, and matplotlib/seaborn
A final presentation with a summary of methods, results, and learnings
Students are encouraged to explore topics they’re passionate about. Possible ideas include:
Predicting loan approval or credit risk
Classifying text reviews or news articles
Predicting house prices or stock trends
Clustering customer behavior patterns
Any dataset that is realistic in scope and allows for meaningful ML application
Need inspiration? Take a look at these projects from previous semesters:
Milestone
Date
Project Launch
Tuesday, June 3
Class Demo Day
Wednesday, June 18
Official Demo Day
Date to be confirmed
📌 Attendance and presentation in the Class Demo Day are required for students to receive a certificate.
The Class Demo Day is a supportive, internal event where students present their projects to classmates and the teaching team. The goal is to:
Practice presenting technical results
Receive peer and instructor feedback
Reflect on the ML process and learnings
Celebrate collaboration and growth
The Official Demo Day is an on-site event where selected student teams present their projects to the wider ReDI community, including partners and alumni.
It highlights projects across all tracks
Teams selected to present will receive mentoring to prepare
To help learners prepare their pitch, here’s a suggested format:
Length: Max. 5 minutes
Mode: Slides and or Jupyter Notebook walkthrough
Proposed Structure:
Intro – What’s the project, and what problem does it solve?
Demo – Show the live demo (notebook, code, visuals)
Challenges & Learning – What went well? What was hard? What did you learn?
To receive a ReDI certificate, learners must:
Attend at least 80% of the course
Participate in 2 Career Workshops
Complete and present a Final Project
Attend the Internal Class Demo Day
Complete 2 IBM SkillsBuild Courses
💬 “We grow by doing, and by helping each other.”
Encourage an open, collaborative environment
Use class time for mentoring, troubleshooting, and peer feedback
Support teams with check-ins and technical coaching
Let’s celebrate the end of the semester together 🎉