Use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions.
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.
- Introduction to Data Analysis.
- Practical Statistics.
- Data Wrangling.
- 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.