This repository shows my projects during the Data Science with Python course by Datacamp. This course teaches how to import, clean, manipulate and visualize data, all skills for a data professional or researcher. It has hands-on projects with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, etc. The projects has real-world datasets to learn the statistical and machine learning techniques to train decision trees and use natural language processing (NLP).
- Introduction to Python
- Intermediate Python
- Data Manipulation with pandas
- Joining Data with pandas
- Introduction to Data Visualization with Matplotlib
- Introduction to Data Visualization with Seaborn
- Python Data Science toolbox (part 1)
- Python Data Science toolbox (part 2)
- Intermediate Data Visualization with Seaborn
- Introduction to Importing Data in Python
- Intermediate Importing Data in Python
- Cleaning Data in Python
- Working with Dates and Times in Python
- Writing functions in Python
- Exploratory Data Analysis in Python
- Analyzing Police Activity with pandas
- Statistical thinking (part 1)
- Statistical thinking (part 2)
- Supervised learning with scikit-learn
- Unsupervised learning in Python
- Machine Learning with Tree-Based Models in Python
- Case Study: School Budgeting with Machine Learning in Python
- Cluster Analysis in Python
Datacamp - https://www.datacamp.com/