Data Science

I learned how to use the best visualization for my dataset, and how to interpret common plot types like histograms, scatter plots, line plots and bar plots. I also got familiar with the best practices for using colors and shapes in your plots, and how to avoid common pitfalls.

This course introduced me to the basic Python syntax and popular Data Science modules like Matplotlib (for charts and graphs) and pandas (for tabular data).

This non-technical course introduced me to Data Science. I learned about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data.

This non-technical course covered the following topics: "How does machine learning work, when can you use it, and what is the difference between AI and machine learning?"

In Process

In Process