This is the 4th in a six-part series providing an introduction to Python with a strong orientation to open data science practices for researchers. This will be a highly interactive/hands on series with plenty of practice provided each week.

Topics for this course includes an overview of the Python programming language as needed for data science from variables, data structures, loops, conditional statements (old and new), and object-oriented methods (functions and classes). With this foundation we will explore open data, how to obtain it, how to explore, change, manipulate and visual it.

Week 1: Python Fundamentals Part 1
Week 2: Python Fundamentals Part 2
Week 3: Python object-oriented methods
Week 4: Obtaining and working with data
Week 5: Working with Data
Week 6: Introduction to Exploratory Data Visualization

All along the way you will discover bountiful tips and tricks based on commonly asked questions from your very own peers, coworkers, instructors and advisors!

Who is this workshop for: Both people new to Python as well as seasoned veterans looking for the newer/better methods of using Python for Data science.

What will I walk away with: A better and firm understanding of Python methods to work with obtaining, analyzing, wrangling and munging, and using visualization to explore and publish your data.