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 executing Python code
Working with Data
- Importing datasets
- Cleaning the data
The Python Data Frame
- Understanding data frames
- Manipulating data within a data frame
Gaining Insights from Data
- Summarizing data
- Generating reports
- Visualizing data
Saving Your Python Code
- Storing code in a version control repository
- Enabling others to access your code
Improving Your Code
- Testing code and fixing errors
- Refining code using an iterative approach
Taking Your Code to Production
- Deploying code to a website
- Automating code execution
Python Programming Best Practices
Summary and Conclusion
Requirements
- Programming experience in any language
Audience
- Developers
- Entry-level data scientists
- Business analysts with technical skills
Testimonials (6)
very comprehensive in regards to doing data analysis using python
Mervin Lau - MINDEF
Course - Python for Data Analysis
Trainer was very patient with helping us resolve problems that we had faced as well as clarifying our doubts.
Chua Wei Zhi - MINDEF
Course - Python for Data Analysis
clear explanation with adequate examples.
Raphael Reynold - MINDEF
Course - Python for Data Analysis
Patience of the trainer while making sure everyone understand the lesson
Yeo Yu Xin - Ministry of Defence, Singapore
Course - Python for Data Analysis
It's very hands-on and I can follow despite the lack of calculus background.
Wei Pin Ho - Ministry of Defence, Singapore
Course - Python for Data Analysis
Very hands-on practice, engaging and good amount of breaks in between. Thus did not feel tired/lethargic.
