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Data Science—Discover the hidden patterns
Develop an understanding of data science by learning how to find, organize, manage, and process large volumes of real-world data. In this streamlined package of introductory data science courses, you’ll perform data manipulation and analysis using Python.
By leveraging your mathematical and statistical skills to find patterns, value, and insights, you’ll gain valuable insights and gain expertise in creating stunning visualizations and statistical models using R.
Learning outcomes
Students completing this program should be able to:
- Develop complex functions and scripts to perform complicated calculations to solve engineering, financial, mathematical, and scientific problems and visualize the results of these calculations.
- Install and configure Python and essential Python development tools and write programs to perform data analysis, statistical analysis, learning, and AI techniques.
- Manage and manipulate data, perform data type conversions, merge datasets, deal with missing values, and extract, delete, or transform subsets of data based on logical criteria.
- Discuss the importance of data analysis for data science, data visualization, and exploration.
Courses
Stackable skills
You can learn more in this field in the Data Engineering specialization or the more in-depth Data Science and Data Analysis certificate program.
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Program Overview
Estimated Cost: $2,920 (You pay only for courses you enroll in.)
Program Requirements: 3 courses (9 quarter units)
Minimum Hours of Instruction: 90
Estimated Duration: 6 – 9 months
Modality: You can complete this program fully online, in person, or choose a mix of course formats.
Special Programs: This program is not approved for workforce or international students.
Courses
Course | Quarter Units | Fall | Winter | Spring | Summer |
---|---|---|---|---|---|
1. Required Course(s): You must successfully complete the three courses below.
| |||||
Dashboards and Data Visualization | 3.0 | Winter Flexible | Summer Flexible | ||
Data Analysis, Introduction | 3.0 | Fall Flexible | Winter Flexible | Spring Flexible | Summer Flexible |
Python for Data Analysis | 3.0 | Fall Live-Online | Winter Live-Online | Spring Flexible | Summer Flexible |
2. Completion Review
| |||||
Specialization in Data Science Completion Fee | None | Fall Online | Winter Online | Spring Online | Summer Online |