Python Foundations

Part 1: Fundamentals of Python

• Data types, variables

• Operators & Precedence

• Conditional Operations

• Using and Writing Functions

• Python classes and objects​ (OOP)

• Using libraries

• Version control with Git & GitHub

• Error handling & Unit Testing

Part 2: Advanced Topics (time permitting)

• How to use python to analyze data

• SQL

• Basic Visualizations

• You have an interest in programming

• You are familiar with basic computer terminology

• You are confident with using a computer, creating files and folders, and browsing the web

• You are looking for a basic course to start your journey into Data Analytics and/or Machine Learning & AI

• 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

• Watch the How Computers Work YouTube series

• Watch this video titled Introduction to Computer Science for Beginners

• Watch these introductory videos on the topics we will cover in Intro Computer Science

• You will have written a first program with Python, including loops, variables and functions

• You have received an introduction to Data Analytics

• You are prepared to continue with the Python Intermediate course for the Data Analytics Track

• 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)