Machine Learning / AI (Hybrid)
Last updated
Last updated
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Are you new to this course:
Start your Onboarding:
Mon
17.03.2025
Course Kick off online Welcome Session + Introduction + Workspace Prep Review of Python, Pandas, NumPy + Matplotlib
Online
Wed
19.03.2025
Review of Python, Pandas, NumPy + Matplotlib
Online
Mon
24.03.2025
ML Intro ML intro, what are models, high-level course overview Feature engineering usage and why its important
Online
Wed
26.03.2025
Lab Class
Online
Mon
31.03.2025
ML Regression Regression types, implement univariate, polynomial, multivariate regression
Online
Wed
02.04.2025
Lab Class
Online
Mon
07.04.2025
ML Regression: Regularization Regression types, implement univariate, polynomial, multivariate regression, Under-/Overfitting, Train/Val/Test Split, Resampling Techniques
Online
Wed
09.04.2025
Lab Class
Online
Mon
14.04.2025
ML Model Prep: Model Preparation and Evaluation Under-/Overfitting, Train/Val/Test Split, Resampling Techniques
Wed
16.04.2025
Lab Class
Online
Mon
21.04.2025
Holiday
Wed
23.04.2025
ML Classification: Classification Theory, Confusion Matrix, ROC
Online
Mon
28.04.2025
ML Classification: Classification Practical implement Logistic Regression, SVM, Random Forest, etc.
Online
Wed
30.04.2025
Lab Class
Online
Mon
05.05.2025
Students mid-Term Feedback Session
Online
Wed
07.05.2025
ML Clustering / DimRed Clustering Techniques, e.g. kmeans, hierarchical clustering, density-based clustering
Online
Mon - Thurs
12.05.2025 - 15.05.2025
Online
Mon
19.05.2025
git OR Dimensionality Reduction Factor Analysis, Principal Component, Intro to Reinforcement Learning
Wed
21.05.2025
Lab Class
Online
Mon
26.05.2025
Final Project Kick Off
Online
Wed
28.05.2025
Project Preparation 1
Online
Mon
02.06.2025
Project Preparation 2
Online
Wed
04.06.2025
Project Preparation 3
Online
Mon
09.06.2025
Holiday
Wed
11.06.2025
Project Preparation 4
Online
Mon
16.06.2025
Project Preparation 5
Online
Wed
18.06.2025
Class Demo Day
Online
Reach out to Sevval, your Course Manager, for help via Slack.
Class on site at
Students Participate in . Pick 2 workshops you like! More info in the!
Class on site at