Python Intermediate

Virtual Environments, Git

Recap: Data Types, Variables, Conditionals

Recap: Functions, Dicts, Data Manipulation

SQL Introduction

Numerical Calculations with numpy

Data Handling with pandas

Data Preparation (cleaning, ...)

Data Visualisation (matplotlib, seaborn, plotly)

Object Oriented Programming

Networking: Web Scraping, REST APIs (create and consume)

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 have an interest in data and what to do with it.

You have a good understanding of basic Python programming or completed the ReDI course Intro to Compute Science.

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.

Register on dataquest.io and finish the following modules:

You will have built a Data Science Pipeline with Python.

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

You get the Data Science mindset and can tell a story with data.

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.