University of Colorado Boulder - Data Understanding and Visualization
- Offered byCoursera
Data Understanding and Visualization at Coursera Overview
Duration | 25 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Data Understanding and Visualization at Coursera Highlights
- Earn a certificate of completion
- Add to your LinkedIn profile
- 4 quizzes, 1 assignment
Data Understanding and Visualization at Coursera Course details
- What you'll learn
- Understand and communicate the various statistical aspects of datasets, including measures of central tendency, variation, location, and correlation.
- Utilize Pandas for data manipulation and preparation to set the foundation for data visualization.
- Utilize Matplotlib and Seaborn to create accurate and meaningful data visualizations.
- The "Data Understanding and Visualization" course provides students with essential statistical concepts to comprehend and analyze datasets effectively. Participants will learn about central tendency, variation, location, correlation, and other fundamental statistical measures. Additionally, the course introduces data visualization techniques using Pandas, Matplotlib, and Seaborn packages, enabling students to present data visually with appropriate plots for accurate and efficient communication.
- Learning Objectives:
- 1. Understand and communicate the various aspects of statistics of datasets, including measures of central tendency, variation, location, and correlation.
- 2. Gain insights into basic statistical concepts and use them to describe dataset characteristics effectively.
- 3. Utilize Pandas for data manipulation and preparation to set the foundation for data visualization.
- 4. Master the utilization of Matplotlib and Seaborn to create accurate and meaningful data visualizations.
- 5. Choose appropriate plot types for different data types and research questions to enhance data comprehension and communication.
- Throughout the course, students will actively engage in practical exercises and projects, enabling them to explore statistical concepts, conduct data analysis, and effectively communicate insights through compelling visualizations.
- Throughout the course, students will actively engage in practical exercises and projects that involve statistical analysis and data visualization. By the end of the course, participants will be equipped with the knowledge and skills to explore, analyze, and communicate insights from datasets effectively through descriptive statistics and compelling visualizations.
Data Understanding and Visualization at Coursera Curriculum
Data Statistics
Data Statistics
Assessment Strategy
Activity Strategy
Data Statistics Demo
Data Statistics Case Study
Data Statistics Quiz
Data Statistics Exploration Exercise
Data Visualization with Pandas
Data Visualization with Pandas
Data Visualization with Pandas Demo
Data Visualization with Pandas Case Study
Data Visualization with Pandas Quiz
Data Visualization with Pandas Exploration Exercise
Data Visualization with Matplotlib
Data Visualization with Matplotlib
Data Visualization with Matplotlib Demo
Data Visualization with Matplotlib Case Study
Data Visualization with Matplotlibb Quiz
Data Visualization with Matplotlib Exploration Exercise
Data Visualization with Seaborn
Data Visualization with Seaborn
Data Visualization with Seaborns Demo
Data Visualization with Seaborn Case Study
Data Visualization with Seaborn Quiz
Self Reflection
Data Visualization with Seaborn Exploration Exercise
Data Understanding and Visualization at Coursera Admission Process
Important Dates
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