Use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions.

Necessary preparation

In order to succeed in this program, we recommend having experience working with data in Python (specifically NumPy and Pandas) and SQL. This includes:

• Python standard libraries.
• Working with data with Pandas and NumPy.

For those who want to

• Advance your programming skills and refine your ability to work with messy, complex datasets. 
• Learn to manipulate and prepare data for analysis, and create visualizations for data exploration.
• Learn to use your data skills to tell a story with data.

The Program 

1. Introduction to Data Analysis.
2. Practical Statistics.
3. Data Wrangling.
4. Data Visualization with Python.

What will you learn

• The data analysis process of wrangling, exploring, analyzing, and communicating data.
• Work with data in Python, using libraries like NumPy and Pandas.
• How to apply inferential statistics and probability to real-world scenarios, such as analyzing A/B tests and building supervised learning models.
• The data wrangling process of gathering, assessing, and cleaning data.
• To use Python to wrangle data programmatically and prepare it for analysis.
• To apply visualization principles to the data analysis process. Explore data visually at multiple levels to find insights and create a compelling story.