*Note: We expect to sell out by January 1st. Be sure to RSVP soon to secure your spot.
Are you interested in learning more data science? You know it’s necessary to be a strong programmer, but you don’t know how to get started. In this six week workshop, you’ll learn how to program in Python; after completing the six week course, you’ll be better prepared to learn data science.
This workshop is for analysts, product managers, statisticians, business managers and anyone else who wants to build their Python skills for data science.
What You’ll Learn / Takeaway:
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
Who Should Take this Class?
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.
• Bring your laptop and power cable.
• Install Anaconda with Python version 2.7 on your machine: http://docs.continuum.io/anaconda/install.html
• Install a text editor: http://www.sublimetext.com/
• If you have trouble with installation, we will assist on the first day.
Tuesday & Thursday
6:00pm – 9:00pm
Week 1: Jan 24th & 26th
Week 2: Jan 31st & Feb 2nd
Week 3: Feb 7th & 9th
Week 4: Feb 14th & 16th
Week 5: Feb 21st & 23rd
Week 6: Feb 28th & Mar 2nd
About Your Instructors
Ryan Henning is our Lead Instructor. He will teach and oversee the instruction of this course. Software Engineer turned Data Scientist, Ryan worked in industry on a large C++ data acquisition (DAQ) framework as a Software Engineer before returning to academia. In graduate school Ryan researched deep neural networks (deep learning) for image processing and classification, specifically using neural networks to detect leukocoria in photos of children. Leukocoria is a cardinal symptom of a common pediatric cancer, retinoblastoma. Ryan and his colleagues at Baylor deployed this research in an iOS app that is saving lives around the world.
Full Course Outline:
First class: Introduction to git, Github, Unix, Downloading software (Anaconda, git, sublime)
Second Class: Variable assignment, Variable declaration, Loops, Control flow, Logic
First class: Introduction to Python data structures, Python libraries, Lists, Strings
Second Class: Tuples, Dictionaries, and Sets
First class: Functions and Scope
Second Class: Lab 1: Linking it all together
First class: Object Oriented Programming (OOP)
Second Class: OOP
First class: Lab 2 – OOP
Second Class: Introduction to Pandas, Dataframes
First class: DataFrame operations, Numpy
Second Class: Introduction to Statistical Modeling – SciKit Learn and Statsmodels
Cost of the entire course: $1,500.00 + Eventbrite registration fees.
For questions, please email enrollment at firstname.lastname@example.org.