Who should take this course?
Intermediate Python developers looking to use Python to explore and visualize large or complex data sets. Check out our Introduction to Python course if you’re new to Python.
Prerequisites
The Training Covers These Topics:
- Learn how to use data science with Python.
- Create data pipeline workflows to analyze, visualize, and gain insights from data.
- Build a portfolio of data science projects with real world data.
- Analyze your own data sets and gain insights through data science.
- Master critical data science skills.
- Replicate real-world situations and data reports.
- Learn NumPy for numerical processing with Python.
- Conduct feature engineering on real world case studies.
- Learn Pandas for data manipulation with Python.
- Learn Matplotlib to create fully customized data visualizations with Python.
- Learn Seaborn to create beautiful statistical plots with Python.
- Construct a modern portfolio of data science resume projects.
- Get set-up quickly with the Anaconda data science stack environment.
1 – Python
2 – Jupyter Notebooks
3 – Numpy
4 – Pandas
- Data I/0: including Excel, CSV, and SQL
- Convert datasets to dataframes
- Alter specific data using custom functions
- Handle missing data
- Aggregate data
5 – Matplotlib for Fully Customizable Plots
- Implement customer figures and axis
6 – Seaborn for Statistical Plots
- Scatter Plots
- Distribution Plots
- Box Plots