Data I

Programming Skills

programming skills

model building

University of Kansas

Author

Will Duncan

Course Description

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and sys- tems to derive knowledge and insights from data. This course teaches students the critical concepts of inference and computing, working with real behavioral, economic, geographic, physical, social, and text data. Students obtain basic statistics training from a computational perspective using simulation to answer questions, explore problems, and delve into social issues surrounding data analysis such as privacy and design.

Course Objective

Upon successful completion of this course, students will be able to: - Have learned the basic concepts and skills of data science. – Work with data from multiple sources and identify relevant questions. – Understand and process data and organize information. – Analyze data by identifying and applying statistical methods. – Visualize and communicate data. – Translate results into solutions and communicate findings in a way that positively affects policy or organizational decisions. - Become familiar with the programming language of Python, particularly in the use of data science and statistical modeling.

Prerequisite: NONE

Syllabus

Lecture

Lecture 1: Introduction Click!

Lecture 2: Causality Click!

Lecture 3: Introduction to Tables and Data Types Click!

Lecture 4:Arrays & Ranges Click!

Lecture 5: Creating Tables Click!

Lecture 6: Data Visualization Click!

Data I

Course Description

Course Objective

Syllabus

Lecture

In-Class Activity

Assignment

Data

Resources

Textbook

Google Colab