Data Science with Python
- Level High School
- Contact Hours 85
- Timeframe Semester
This course equips students with the essential skills of a data scientist which include data collection, cleanup, transformation, analysis, and visualization. Students will write algorithms, tell data stories, and build statistical models using Python libraries.
To view the entire syllabus, click here or click to explore the full course.
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The Data Science Life Cycle
Students will learn and apply the process of the data science life cycle. This includes asking statistical questions, collecting or obtaining reliable raw data, analyzing the data using measures of central tendency and spread and interpreting and summarizing the results. |
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Data Science for Change
Students will use and analyze data to better understand a problem, measure the scope of a problem, or understand how people are affected by the problem. They will learn more about cleaning a dataset and filtering by column, rows, and conditions. |
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Data Storytelling
Students will use and analyze data to tell a data story. They will create a visually appealing infographic that displays important data visualizations. The infographic will also tell a story based on their interpretation after exploring, analyzing, and visualizing the data. |
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Data Science for Business
Students will gather business data that can be used to make decisions about how to better the company or product. They will present their findings in a business report that suggests several action items that they predict will help the business's performance and growth. |
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Final Exam
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What's Next?
Students explore the next chapter in learning about data science and the careers that are available and growing. |
Explore programs that your students will build throughout this course!
Here are a few examples of teacher resources and materials to use in the Data Science with Python course
Data Science with Python is aligned with the following standards
| Standards Framework | View Alignment |
|---|---|
| New York 9-12 | View (60.6%) |
| North Carolina Computer Science II | View (55.6%) |
| Natrona Computer Programming 1 | View (47.6%) |
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