Machine Learning & AI

Introduction

• Machine Learning Introduction

• Environment Setup

• Models

• Supervised Learning: Regression, Regularization

• Model Preparation, Evaluation

• Classification

• Unsupervised Learning: Clustering, Dimensionality Reduction

• Deep Learning Introduction: Tensors, Neural Nets from Scratch

• Model class, learning rate, batches, hyperparameters

• Classification Models

• Computer Vision: Image classification, CNN, Object Detection, Transformers

• Natural Language Processing

• Model Deployment

Frameworks:

• TensorFlow

• PyTorch

Final project

• Job Readiness: Soft skills through career trainings geared towards preparing you for job applications & interviews, networking events and job fairs.

• You will learn from experts in the industry to start a career in tech.

• You can commit at least 10 hours a week (classes + self-study), 80% attendance of the course is required for graduation.

• You are able to understand and speak English.You have experience in self-study

• You have a good understanding of Python

• You have passed the equivalent of Python Intermediate.

• You have an interest in Data Science and/or Machine Learning

Prepare yourself for the course with the following self-learning contents:

• Discover data analysis on MS Learn

• Introduction to Machine Learning on MS Learn

Registered on dataquest.io and finished the following modules:

• Python Intermediate: Cleaning and Preparing Data in Python

• Pandas and NumPy Fundamentals (first 3 modules)

• Elements of the Command Line (first module only)

Note: Graduates from our Python Foundation course will be preferred!

You’ll be able to:

• Be familiar with Data Science methods and tools.

• Use Machine Learning Frameworks

You have a Data Science mindset

You can join the Data Circle to work on your projects

• Soft skills trainings

• Workshops

• A mentor

• A job fair

• The ReDI Talent Pool

You have two sessions per week. One is taking place online, the other one on-site.

Mondays: Online Session

Wednesdays: On-site at the Factory Görlitzer Park, Berlin

Homework, group projects and your personal study takes place online. It is important that you can attend both sessions per week. You cannot take this course purely online.

• Career & Soft Skills Workshops, Company Visits

• ReDI Mentorship Program (mentors in the IT industry)

• ReDI Talent Pool (job listing platform)

• SkillBuild self-paced eLearning (by IBM & ReDI)

• You should expect to spend a minimum of 8 hours for career workshops or trainings during the semester.