Machine Learning Course | 6 weeks online

Program overview

Machine Learning is one of the fundamental blocks of Data Science. Its methods are being actively applied across various industries. The goal of this course is to teach you how to successfully apply Machine Learning to real-world business problems while avoiding common pitfalls. By the end of the course you will be able to:

● Convert a business problem into a Machine Learning problem.
● Define requirements for a Machine Learning project (including key performance indicators) using an ML canvas.
● Create different types of Machine Learning pipelines (supervised and unsupervised), including data transformation, feature engineering, building a data pipeline, hyper-parameter tuning, loss functions, and cross-validations on several regression and classification tasks.
● Identify bias and fairness of Machine Learning problems and Machine Learning model explainability and interpretability.
● Design and solve several real-world Machine Learning use-cases, e.g., predictive maintenance, churn prediction, customer segmentation.

Upcoming dates

Schedule: Mon & Wed, 16:00 - 19:00 (remote)

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Course dates

Tuition

22. Oct 21

25. Oct 21 - 01. Dec 21

CHF 1'800

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What you'll learn

1

End-to-End Machine Learning Pipelines

2

Classification Models

3

Unsupervised Learning and Ensemble Models

4

Model Explainability and Selection

5

Model Deployment, Experiment Tracking and Monitoring

6

Mini Project

Weekly schedule

Mo

Tue

Wed

Thu

Fr

Sat

09H00

12H00

13H00

15H40

16H00

17H00

18H00

19H00

Remote

Q&A Session

During these sessions, you are totally free to connect and ask any questions about the covered topics.

Lecture

Learn from our instructors who are experts in their respective fields and get introduced to new topics during live lectures.

Practice

Work on a set of interesting and challenging exercises related to the topics covered in the previous lesson.

Tools we teach

Python
Jupyter notebooks
Pandas
Matplotlib
Seaborn
Scikit-Learn
Auto-ML (TPOT, PyCaret, MLJAR)
Evidently
Flask
AWS

Application process and prerequisites

This course is suitable for beginners and intermediate Python programmers.

Simply apply to the program here.

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Dipanjan Sarkar

Lead Data Scientist & Instructor

Dipanjan (DJ) is a Lead Data Science Consultant & Instructor, leading advanced analytics efforts aro...

Albin Plathottathil

Data Science Consultant

Soon after graduating with a Bachelor’s in Computer Engineering, Albin found his interest in working...