Course Outline
Introduction
- Overview of Python and its Powerful Ecosystem for Data Analysis
Getting Started
- Setting up the development environment
- Installing Python, Numpy, and Pandas
- Installing Jupyter
Python Programming for Data Analysis
- Overview of Python syntax
- Writing and running Python code
Working with Data
- Importing a dataset
- Cleaning the data
The Python Data Frame
- Understanding data frames
- Manipulating data in a date frame
Gaining Insights from Data
- Summarizing the data
- Generating reports
- Visualizing data
Saving Your Python Code
- Saving your code in a version control repository
- Allowing others to access your code
Improving Your Code
- Testing your code and fixing the errors
- Tightening your code using an iterative approach
Taking Your Code to Production
- Uploading your code to a website
- Automating the executing of your code
Python Programming Best Practices
Summary and Conclusion
Requirements
- Programming experience in any language
Audience
- Developers
- Beginning data scientists
- Business analysis with technical skills
Testimonials
clear explanation with adequate examples.
Raphael Reynold - Bertrand Chen, MINDEF
The trainer explains in simple terms for easier understanding of the subject.
Bertrand Chen, MINDEF
Patience of the trainer while making sure everyone understand the lesson
Yeo Yu Xin - Ministry of Defence, Singapore
It's very hands-on and I can follow despite the lack of calculus background.
Wei Pin Ho - Ministry of Defence, Singapore
Very hands-on practice, engaging and good amount of breaks in between. Thus did not feel tired/lethargic.