Machine Learning

• What is Machine Learning?

Introduction to the ML Pipeline

Inspection of dataset and classification workflow

Logistic regression

Decision trees and random forests

Clustering

• 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 are able to understand and speak English

you have experience in self-study

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

you have a good understanding of Python

You have prepared yourself for the course with the following self-learning contents:

• Discover data analysis on MS Learn

• Introduction to Machine Learning on MS Learn

you registered on dataquest.io and finished the following modules:

• Python Intermediate: Cleaning and Preparing Data in Python

• Pandas and NumPy Fundamentals (first 2 modules)

Note: Graduates from our Data Analytics & AI courses who have a good understanding of Python will be preferred!

you have build your own ML or data visualization project

you know how to start analyzing a dataset

you know about Data Science Tools (pandas, sklearn, ...)

you have a Data Science mindset

you can continue learning with our Data Analytics alumni group

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 eLearning (by IBM & ReDI)

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