Effective immediately in response to COVID-19, all Technology Training classes will be delivered online until further notice.
In advance of each session, Tech Training will provide you with a Zoom link to your class, along with any required class materials.
This six-hour session will review the foundations of data analytics using Excel and then transfer and advance that knowledge to perform a complete data analysis using the Python programming language.
Prerequisite: Learners should have an understanding of Basic Programming and Excel.
You will have the opportunity to learn how to conduct exploratory data analysis, data visualization and hypothesis testing, and how to use Python to access and manipulate Excel files. At the end of the course, you will be able to perform a complete data analysis using Python.
During this course, you will have the opportunity to learn how to:
- Understand the Foundations of Analytics in Excel
- Explore Variables in Excel
- Understand Exploratory Data Analysis
- Understand the Foundations of Inferential Statistics and Hypothesis Testing
- Use the Python Programming Language for Data Analysis
- Access Excel Files Using Python
- Perform Data Visualization and Exploration in Python
- Perform More Efficient and Deeper Data Analyses using Python
- Explore Correlation and Linear Regression in Excel and Python
- Use Python to Manipulate Excel Files and to perform Machine Learning
- Overview of Data Analytics
- Excel Review
i. Foundations of Analytics in Excel
ii. Variables in Excel
iii. Exploratory Data Analysis in Excel
iv. Data Visualization in Excel
- Introduction to the Python Programming Language
i. Installing Anaconda
- Milestone 1: How to use Jupyter Notebooks
i. Python Essentials
ii. Introduction to Pandas
iii. Using Pandas to access Excel files
iv. Data Analysis with Pandas
- Milestone 2: Perform exploratory data analysis using Pandas
i. Using Python for data wrangling
ii. Using Python to manipulate Excel files
iii. Data Visualization in Python: Matplotlib, Pandas, Seaborn
- Milestone 3: Perform data visualization using Python
i. Inferential Statistics and Hypothesis Testing in Python
ii. Correlation and Linear Regression using Excel and Python
iii. Using Python to perform machine learning
- Milestone 4: Perform complete Python data analysis
- Conclusion: Data Analytics in the real world, and next steps.
University IT Technology Training classes are only available to Stanford University staff, faculty, students and Stanford Hospitals & Clinics employees. A valid SUNet ID is needed in order to enroll in a class.