Machine Learning & AI

Part 1: Introduction

• Machine Learning Introduction

• Environment Setup

• Models

• Supervised Learning: Regression, Regularization

• Model Preparation, Evaluation

• Classification

• Unsupervised Learning: Clustering, Dimensionality Reduction

• AI Applications: Explore practical applications like computer vision, natural language processing, and generative AI.

Part 2: Frameworks

• TensorFlow

• PyTorch

Part 3: Final Project:

• Apply previously learned concepts to a project and present your project on Demo Day to your colleagues in the course.

• You are interested in Data Analytics and Machine Learning

• You have a solid understanding of Python and Data Analytics (pandas, seaborn, numpy)

• You have a first understanding of Machine Learning 

• You are interested in self-study and independent project work

• You can understand and speak English

• You can commit at least 15 hours a week

• Sessions: Two sessions a week. It is essential that you attend both sessions. 80% of attendance and homework completion is required for graduation.

• Hybrid: Depending on whether you are based in Hamburg, Berlin, or NRW, different on-site activities occur. In Hamburg, one session a month is on-site. In Berlin and NRW, you can join on-site community events. All other sessions are online via Zoom. 

• Teachers: Your teachers are experts in the industry and volunteer to support your learning journey. 

• Learning Style: At ReDI, we believe in learning by coding. You are asked to apply the newly learned concepts in weekly homework and in a final project. This requires a lot of independent self-study. The teachers help you explain the concepts only at a high level. You are putting them into practice in your homework and project.

• Active Work: Note this is NOT a passive, lecture-style environment. Each learner is expected to be self-driven and motivated to code and work hands-on each week on the assignments. ReDI to start coding? Then join us!

• Monday: Every Monday from 19:00 to 21:00, you have an online session in which you discuss your homework and where you will be introduced and practice new concepts.

• Wednesday: Every Wednesday from 19:00 to 21:00, you have an online session where the volunteer teachers introduce you to new concepts. They will share the weekly homework with you in this session.

• Thursday - Sunday: You work on your weekly homework. That means you will be coding hands-on by yourself! If you run into problems, you can contact your class on Slack. You upload your homework before the Monday session.

• You’re familiar with Data Science methods and tools

• You’ll be able to use Machine Learning Frameworks 

• You have a Data Science Mindset 

• You are ready to apply for ReDI’s Data Circle where you deepen your ML skills by working on realistic data & ML projects.

• Career & Soft Skills Workshops, Company Visits 

• ReDI Mentorship Program (mentors in the IT industry) 

• ReDI Talent Pool (job listing platform) 

• Further Online Learning resources such as SkillBuild self-paced eLearning (by IBM & ReDI)

• Further Online Learning resources such as SkillBuild Self-paced learning (by IBM & ReDI School)