Machine Learning

Munich | Data Analytics Courses

2 sessions / week
This is a FREE course

ReDI Career Track: Data Analytics

Become a Data Analyst, Data Scientist, Data Engineer

Course Overview

In this course, you will learn the core concepts of machine learning that a beginner must know. We will cover 'classical machine learning' primarily using Scikit-learn. You will virtually “travel around the world” as we apply these classic techniques to data from many areas of the world to allow you to learn while building.

- Apply the core concepts of machine learning
- Consider fairness when using machine learning techniques
- How to use regression, classification ML, and clustering ML techniques
- How to use language processing, time series forecasting, and reinforcement learning ML techniques
- Apply your knowledge in real-world applications for ML
- You can speak English
- You can commit to at least 10 hours a week (classes + self-study) and at least 8 hours for career workshops or trainings during the semester.
- You have successfully completed Data Analytics OR you already have similar skills.
- You can start looking for internships and junior positions in data analytics.
- Career & Soft Skills Workshops & Trainings, Company Visits
- ReDI Mentorship Program (mentors in the IT industry)
- ReDI Talent Pool (job listing platform)
- Further Online Learning resources such as IBM SkillsBuild self-paced eLearning (by IBM & ReDI)

Course Impressions

Testimonials

“The ReDI School has had a tremendously positive impact on my career path. I'm still wondering what to do next, but I know that integrating digital skills definitely opens doors.”

“I am just a newbie to Tech and I see a long way ahead, but I always feel motivated. Thank you and I am glad that ReDI is always by my side throughout this journey.”

“When I say the opportunity I had at ReDI School was life changing, it was because I saw that it was worth coming here, betting my last coins and actually staying in Berlin and bulding my life here. Everything is still in a process. But for the first time, I feel strong enough and useful with the skill I learned this semester. Thank you”

Munich - Online
Tue & Thu, 19:00 - 21:00
Spring Semester: March-June
Fall Semester: September-December
Teaching language: English

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