What you'll learn

Skills you'll gain

There are 4 modules in this course

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 Visualization with Pandas

Data Visualization with Matplotlib

Data Visualization with Seaborn

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