Introduction to Data Science With Python for Data Pros - SQL Sat PHX Precon
Data Science is currently the hottest topic among data analysts and technologists, but getting started can sometimes be daunting or confusing to many data professionals. We aim to change that with this full-day, hands-on course in which you will be introduced to data science and its basic methodologies using the Python programming language!
Together we will work through some real-world data analyses using several of the most popular Python libraries, such as NumPy, pandas, Matplotlib, and SciPy. Next we'll cover collecting and importing data, and introduce basic statistics around our data. From there we'll move on to create some simple visualizations of our data to help us identify trends and patterns, and then finish up by putting our newfound Python skills to the test by tackling a detailed real-world scenario.
• DBAs and Database Developers looking to branch out into the wider world of data science.
• Data Analysts who want an introduction to the features and methods available in the Python data science toolset.
• Anyone who is looking for a fun, hands-on way to get started in the data science field.
• Part 1 - Python In The Real World, With SQL Server (introductory presentation)
• Part 2 - Setup and Python Basics (hands-on lab)
• Part 3 - Arrays and mathematics with Numpy (hands-on lab)
• Part 4 - pandas data frames (hands-on lab)
• Part 5 - Visualizing data with Matplotlib (hands-on lab)
• Part 6 - Data Exploration (hands-on lab)
• Slides - 10%
• Demos - 10%
• Hands-on Labs - 80%
Note that as this is a hands-on pre-con, participants will be required to bring a laptop with a working Python installation. Full details on this will be provided prior to the session.
Chris Hyde is an independent SQL Server BI and DBA consultant based in Albuquerque, NM, and is the leader of the Albuquerque PASS local user group. He is a part of the Friends of Redgate program and was a member of the Idera ACE class of 2018. He loves loud music and cricket, but not usually at the same time.