The main objective for this course is for you to leave with a fundamental understanding of programming within Python. If this is your first programming language, then you will feel a very steep learning curve. The goal of this course is to assist you with overcoming that learning curve, so you can not only continue to grow in this environment, but also start learning from the vast amount of information that is available to you through the online community.
Having a strong foundation in math/statistics and programming is imperative to success in the data science world. The aim of this course will be at the foundation of programming. Often the most difficult part is just getting started. We are here to help with that process.
Whether you’ve programmed in other languages or Python is your first, this class will teach you the nuances of Python and how to use them to your advantage in your data science projects. Here’s what you’ll learn:
- Environment Setup
- Data Scientist Workflow
- Ins and Outs of Coding Pythonically
- Object Oriented Programming
- Popular Data Science Libraries including Matplotlib, Pandas, Numpy, Sklearn
For those of you interested in learning to program in Python, so you may be better prepared for self study in data science, this course will help you get up to speed. Those of you who are interested in gaining the skills required for admittance to the Data Science Immersive; this course is designed to help you meet that bar.
Desire to learn. Readiness to make mistakes and fail forward.
- Bring your laptop and power cable.
- See the Installation Guide
- If you have trouble with installation, we will assist on the first day.
Twice per week, generally either
Mondays & Wednesdays at 6:30 pm, or
Tuesdays & Thursdays at 6:30 pm.
The exact dates and times may vary by campus and session.
- Week 1:
- First class: Introduction to git, Github, Unix, Downloading software (Anaconda, git, Atom)
- Second Class: Variable assignment, Variable declaration, Loops, Control flow, Logic
- Week 2:
- First class: Introduction to Python data structures, Python libraries, Lists, Strings
- Second Class: Tuples, Dictionaries, and Sets
- Week 3:
- First class: Functions and Scope
- Second Class: Lab 1: Linking it all together
- Week 4:
- First class: Object Oriented Programming (OOP)
- Second Class: OOP
- Week 5:
- First class: Lab 2 – OOP
- Second Class: Introduction to Pandas, Dataframes
- Week 6:
- First class: DataFrame operations, Numpy
- Second Class: Introduction to Statistical Modeling