Developing Data Science ApplicationsCornell Course
Science Applications
Cornell CourseDeveloping Data Science Applications ()
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Course Overview
Python is much more than a programming language. In this course, you will leverage the comprehensive Python ecosystem of libraries, frameworks, and tools to develop complex data science applications. Throughout this course, you will practice using the different Python tools appropriate to your dataset. You will leverage library resources for data acquisition and analysis as well as machine learning. Dataframes will be introduced as a means of manipulating structured data tables for advanced analysis. Additionally, you will practice basic routines for data visualization utilizing Jupyter Notebooks.
You are required to have completed the following courses or have equivalent experience before taking this course:
- Constructing Expressions in Python
- Writing Custom Python Functions, Classes, and Workflows
Key Course Takeaways
- Import Python modules and libraries to access additional functionality
- Use Python libraries for data science
- Choose the right Python tools for your datasets
- Use Jupyter Notebooks to integrate data analysis, visualization, and documentation
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Course Length
3 weeks
Effort
3-5 hours per week
Format
100% online, instructor-led
Course Author
Chris Myers
Adjunct Professor
Cornell University Center for Advanced Computing
Senior Research Associate / Adjunct Professor Cornell University Center for Advanced Computing
Bio coming soon
Who Should Enroll
- Data analysts and business analysts
- Database managers
- Technical and systems analysts
- Programmers interested in data science
- Marketers
- Business managers
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