@ -52,9 +52,9 @@ In addition, a low-stakes quiz before a class sets the intention of the student
| 08 | Working with Python | [Working With Data](2-Working-With-Data/README.md) | Basics of using Python for data exploration with libraries such as Pandas. Foundational understanding of Python programming is recommended. | | |
| 09 | Data Preparation | [Working With Data](2-Working-With-Data/README.md) | Topics on data wrangling, which are techniques for cleaning and transforming the data to handle challenges of missing, inaccurate, or incomplete data. | | |
| 10 | Visualizing Quantities | [Data Visualization](3-Data-Visualization/README.md) | Learn how to use Matplotlib to visualize bird data 🦆 | [Quantities](3-Data-Visualization/10-visualization-quantities/README.md) | Jen |
| 11 | Visualizing Distributions of Data | [Data Visualization](3-Data-Visualization/README.md) | Distributions | | Jen |
| 11 | Visualizing Distributions of Data | [Data Visualization](3-Data-Visualization/README.md) | Visualizing observations and trends within an interval. | | Jen |
| 12 | Visualizing Proportions | [Data Visualization](3-Data-Visualization/README.md) | Visualizing discrete and grouped percentages. | | Jen |
| 13 | Visualizing Relationships | [Data Visualization](3-Data-Visualization/README.md) | Visualizing connections and correlations between sets of data and their variables. | | Jen |
| 14 | Meaningful Visualizations | [Data Visualization](3-Data-Visualization/README.md) | Techniques and guidance for making your visualizations valuable for effective problem solving and insights. | | Jen |
| 15 | Capturing | [Lifecycle](4-Data-Science-Lifecycle/README.md) | Introduction to the data science lifecycle and its first step of acquiring and extracting data | | |
| 16 | Processing | [Lifecycle](4-Data-Science-Lifecycle/README.md) | This phase of the data science lifecycle focuses on techniques to classify and summarize data. | | |
Jasmine
3 years ago