This course will provide your analytics staff with a useful introduction to Python, teaching them how to clean, aggregate, describe, and visualize data. Upon completion, they will be able to analyze numerical, categorical, and time-series data in Python. This course is geared toward individuals who are new to Python but have basic analytical skills and some programming experience.
Metis Senior Data Scientists have real-world business experience and will show your team how to apply machine learning concepts to daily tasks. Your team will then be able to hit the ground running, using their new skills to immediately impact their work.
We offer in-person training, as well as remote training via our Live Online technology. We are able to blend these capabilities so we can teach your entire team, even if they’re not all in one place.
Upon completion of the course, attendees should be able to:
Perform basic analysis in Python using pandas
Edit and create Excel worksheets in Python
Create functions to automate analysis
Python and Pandas Basics
Introduction to the Jupyter notebook
Introduction to pandas
Data sources and I/O
Interacting with Excel
Aggregations, Explorations, and Visualizations
Data Aggregation and Partitions
Pandas for exploratory data analysis
Data visualization in Python
Introduction to regression analysis in Python
Metis was able to engage employees at all skill levels, from those with no background in Python to those who were experienced. Moving large data models over to new systems is a risky proposition, but through Metis, we have the tools to do it now, and we've started moving some of our most important project models over to Python.
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