# Machine Learning & AI (Online)

{% hint style="success" %}
**Get Started**

* Are you new to this course: [Course Overview](https://redi-school-1.gitbook.io/machine-learning-and-ai/self-onboarding/your-course)
* Start your Onboarding: [Get Started](https://redi-school-1.gitbook.io/machine-learning-and-ai/self-onboarding/get-started)
  {% endhint %}

### Course Plan <a href="#get-started" id="get-started"></a>

<table><thead><tr><th width="105.2005615234375">Day</th><th width="167.08154296875">Date</th><th>Topics</th></tr></thead><tbody><tr><td>Mon</td><td>16.03.2026</td><td>Onboarding</td></tr><tr><td>Wed</td><td>18.03.2026</td><td><strong>Course Kick off online</strong><br><br></td></tr><tr><td>Mon</td><td>23.03.2026</td><td>Welcome Session <br>Workspace Prep + Git</td></tr><tr><td>Wed</td><td>25.03.2026</td><td>Data cleaning + eda<br>Git and tech support in breakout rooms</td></tr><tr><td>Mon</td><td>30.03.2026</td><td>ML Intro <br>What are models, being responsible (bias &#x26; ressources like water) - skills beyond the pure tech - high-level course overview Feature engineering usage and why its important</td></tr><tr><td>Wed</td><td>01.04.2026</td><td>Regression example: Linear Regression -> Data preparation, encoding and other small topics, train/test split</td></tr><tr><td>Mon</td><td>06.04.2026</td><td>Public Holiday- NO CLASS</td></tr><tr><td>Wed</td><td>08.04.2026</td><td>ML Regression<br>Intro - what is it?</td></tr><tr><td>Mon</td><td>13.04.2026</td><td>Practice Session</td></tr><tr><td>Wed</td><td>15.04.2026</td><td>Under-/Overfitting, Introduce validation split for: Hyperparametertuning,<br>Start Regression challenge</td></tr><tr><td>Mon</td><td>20.04.2026</td><td>ML Classification: Classification Theory Confusion Matrix, ROC</td></tr><tr><td>Wed</td><td>22.04.2026</td><td>Mid-semester feedback (15 minutes at the beginning of the class). ML Classification: Classification Practical implement Logistic Regression, Tree based models</td></tr><tr><td>Mon</td><td>27.04.2026</td><td>Discuss regression challenge data preparation<br>random forest, xgboost</td></tr><tr><td>Wed</td><td>29.04.2026</td><td>End of Regression Challenge<br>Start of Classification Challenge (Release the dashboard)<br>-- Databricks, MLflow, The ML Workflow as a whole</td></tr><tr><td>Mon - Thu</td><td>04.05.2026-07.05.2026</td><td>Career Week<br>NO CLASS <br>Join the online workshops</td></tr><tr><td>Mon</td><td>11.05.2026</td><td>LLMs</td></tr><tr><td>Wed</td><td>13.05.2026</td><td>LLMs</td></tr><tr><td>Mon</td><td>18.05.2026</td><td>Final Project Kick-Off</td></tr><tr><td>Wed</td><td>20.05.2026</td><td>AI Assisted Review</td></tr><tr><td>Mon</td><td>25.05.2026</td><td>Public Holiday - NO CLASS</td></tr><tr><td>Wed</td><td>27.05.2026</td><td>LLMs</td></tr><tr><td>Mon</td><td>01.06.2026</td><td>RAG</td></tr><tr><td>Wed</td><td>03.06.2026</td><td><p>End classification challenge</p><p>Final Project Work</p></td></tr><tr><td>Mon</td><td>08.06.2026</td><td>Final Project Work</td></tr><tr><td>Wed</td><td>10.06.2026</td><td>Final Project Work</td></tr><tr><td>Mon</td><td>15.06.2026</td><td>Online Class Demo Day</td></tr></tbody></table>

### **⭐️ Help**

For help, you can message your Contact Person or post in the Course Channel on Slack.