Data Science Foundations
Data Science Foundations builds an applied understanding of topics in data science. Each section covers topics from a conceptual standpoint without assuming prerequisite knowledge in statistics and programming. Concepts are reinforced by learning questions that build understanding and confidence. Interactive applets within the course material build dynamic data visualizations and explore new concepts. At the end of the course, students will have the necessary skills to dive further into the more quantitative and technical aspects of data science and machine learning.
Data Science Foundations builds an applied understanding of topics in data science. Each section covers topics from a conceptual standpoint without assuming prerequisite knowledge in statistics and programming. Concepts are reinforced by learning questions that build understanding and confidence. Interactive applets within the course material build dynamic data visualizations and explore new concepts. At the end of the course, students will have the necessary skills to dive further into the more quantitative and technical aspects of data science and machine learning.
Overview
Data Science Foundations builds an applied understanding of topics in data science. Each section covers topics from a conceptual standpoint without assuming prerequisite knowledge in statistics and programming. Concepts are reinforced by learning questions that build understanding and confidence. Interactive applets within the course material build dynamic data visualizations and explore new concepts. At the end of the course, students will have the necessary skills to dive further into the more quantitative and technical aspects of data science and machine learning.
What You Will Learn
- Understand fundamental concepts in data science, including data types, sources, and visualization techniques.
- Develop an applied understanding of statistical concepts relevant to data science, including descriptive statistics, exploratory data analysis, and hypothesis testing.
- Build confidence in using programming concepts relevant to data science, including data manipulation and cleaning, data visualization, and introductory machine learning.
Course Highlights
- Interactive Course Book and Aplets to support learning