# Machine Learning / AI (Hybrid)

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

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

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

<table><thead><tr><th width="87.10330200195312">Day</th><th width="127.47882080078125">Date</th><th width="285.7506103515625">Topics</th><th>Format</th></tr></thead><tbody><tr><td>Mon</td><td>16.03.2026</td><td><strong>Onboarding</strong></td><td>Online</td></tr><tr><td>Wed</td><td>18.03.2026</td><td>Course Kick off online</td><td>Online</td></tr><tr><td>Mon</td><td>23.03.2026</td><td><p>Welcome Session + Introduction</p><p>Workspace Prep Review of Python, Pandas, NumPy + Matplotlib</p></td><td>Online</td></tr><tr><td>Wed</td><td>25.03.2026</td><td><p>Welcome Session + Introduction</p><p>Workspace Prep Review of Python, Pandas, NumPy + Matplotlib</p></td><td>Online</td></tr><tr><td>Mon</td><td>30.03.2026</td><td>ML Intro<br>ML intro, what are models, high-level course overview<br>Feature engineering usage and why its important</td><td>Online</td></tr><tr><td>Wed</td><td>01.04.2026</td><td>Practice Session</td><td>Online</td></tr><tr><td>Mon</td><td>06.04.2026</td><td>Public Holiday- NO CLASS</td><td>NO CLASS</td></tr><tr><td>Wed</td><td>08.04.2026</td><td>ML Regression<br>Regression types, implement univariate, polynomial, multivariate regression</td><td>Online</td></tr><tr><td>Mon</td><td>13.04.2026</td><td>Practice Session</td><td>Online</td></tr><tr><td>Wed</td><td>15.04.2026</td><td>ML Regression: Regularization<br>Regression types, implement univariate, polynomial, multivariate regression, Under-/Overfitting, Train/Val/Test Split, Resampling Techniques</td><td>Online</td></tr><tr><td>Mon</td><td>20.04.2026</td><td><p>Mid-semester feedback (15 minutes at the beginning of the class).</p><p>ML Model Prep: Model Preparation and Evaluation<br>Under-/Overfitting, Train/Val/Test Split, Resampling Techniques, Hyperparametertuning</p></td><td>Online</td></tr><tr><td>Wed</td><td>22.04.2026</td><td>Practice Session</td><td>Online</td></tr><tr><td>Mon</td><td>27.04.2026</td><td>ML Classification:<br>Classification Theory &#x26; Confusion Matrix, ROC</td><td>Online</td></tr><tr><td>Wed</td><td>29.04.2026</td><td>ML Classification: Classification Practical implement Logistic Regression, SVM, Random Forest, etc.</td><td>📍 On-site <a href="https://maps.app.goo.gl/DxRWzW1o2fmK8edE9">JAKALA</a>.</td></tr><tr><td>Mon - Thu</td><td>04.05.2026-07.05.2026</td><td>Career Week</td><td>NO CLASS <br>Join the online workshops</td></tr><tr><td>Mon</td><td>11.05.2026</td><td>Practice Session</td><td>Online</td></tr><tr><td>Wed</td><td>13.05.2026</td><td>AI Assisted Review</td><td>Online</td></tr><tr><td>Mon</td><td>18.05.2026</td><td>Final Project Kick-Off</td><td>Online</td></tr><tr><td>Wed</td><td>20.05.2026</td><td>ML Clustering / DimRed<br>Clustering Techniques, e.g. kmeans, hierarchical clustering, density-based clustering</td><td>Online</td></tr><tr><td>Mon</td><td>25.05.2026</td><td>Public Holiday - NO CLASS</td><td>NO CLASS</td></tr><tr><td>Wed</td><td>27.05.2026</td><td>SQL</td><td>Online</td></tr><tr><td>Mon</td><td>01.06.2026</td><td>NLP</td><td>Online</td></tr><tr><td>Wed</td><td>03.06.2026</td><td>Practice Session /End of Classification Challenge</td><td>Online</td></tr><tr><td>Mon</td><td>08.06.2026</td><td>Final Project Work</td><td>Online</td></tr><tr><td>Wed</td><td>10.06.2026</td><td>Final Project Work</td><td>Online</td></tr><tr><td>Mon</td><td>15.06.2026</td><td>Online Class Demo Day</td><td>Online</td></tr><tr><td>Friday</td><td>19.06.2026</td><td><p>ReDI School Demo Day</p><p></p></td><td>📍 On-site <a href="https://www.google.com/maps/place/data=!4m2!3m1!1s0x47b18f427cfec167:0xe4e9fd6c2f182963?sa=X&#x26;ved=1t:8290&#x26;ictx=111">Jakala</a></td></tr></tbody></table>

### **⭐️ Help**

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