Machine Learning

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 can commit at least 8 hours for career workshops or trainings during the semester

• You are able to understand and speak English

• 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 free content:

• Discover data analysis on MS Learn

• Introduction to Machine Learning on MS Learn

Register on dataquest.io and finish 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 Intermediate 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 start looking for internships and junior positions

• Career & Soft Skills Workshops, Company Visits

• ReDI Mentorship Program (mentors in the IT industry)

• ReDI Talent Pool (job listing platform)

• SkillBuild Self-paced learning (by IBM & ReDI School)

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