Foundations in Python for Scaling Data Analysis

This course is best for data practitioners seeking to enhance their efficiency and expand their technical capabilities by using Python for data preprocessing, statistical analysis, and data visualization. It offers an exploration of Python’s powerful data analysis libraries. Through hands-on exercises and real-world examples, participants will learn to manipulate, analyze, and visualize complex datasets effectively. These foundational skills will unlock access to cutting-edge technical tools within the Python ecosystem (including AI & ML libraries) and increase productivity on both routine and complex analyses.

Key skills covered in this course: 

• Data Analysis
• Data Visualization
• Jupyter Notebooks
• Python Programming

Upon successful completion of the course, learner outcomes include: 

• Write basic Python EDA notebooks using control structures
• Implement an exploratory data analysis in Python on company-provided data*
• Perform basic data cleaning techniques in Python
• Manipulate date data types in Python for time series analyses
• Filter, sort, transform, and summarize data with Python and the pandas library
• Create exploratory data visualizations using the Matplotlib and seaborn libraries

Potential learners:

• Analysts
• Software Engineers
• Statisticians

Prerequisites: 

• Knowledge of descriptive statistics 
• Experience with Exploratory Data Analysis (EDA)

* We require company-provided datasets for the learners to explore during the course so that they can leverage their existing expertise while learning the new analytics tools. These can be actual company data (preferred) or anonymized/randomized alternatives. Our Solutions Architects will work with your data specialists to source appropriate materials 4 weeks before the course starts.