# Foundations of Data Science: a 7-Part SEries

This collection of seven courses – five currently available and two in production – provides a gentle introduction to the field of data science from a conceptual, non-technical level.

## Data Science: An Introduction: Foundations of Data Science, Part 1.

### Course Description

Data science sits at the intersection of statistics, computer programming, and domain expertise. This non-technical overview introduces the basic elements of data science and how it is relevant to work in the real world.

### Course Information

- Introductory level
- 22 streaming video tutorials
- 1 hour 40 minutes of instruction
- Created by Barton Poulson, PhD

## Data Sourcing: Foundations of Data Science, Part 2.

### Course DESCRIPTION

Data science can’t happen without data. That means the first task in any project is to source – that is, *to get* – the raw materials that you will need. This short course discusses some of the more familiar methods of gathering data and some of the less familiar that are specific to data science.

### COURSE INFORMATION

- Introductory level
- 14 streaming video tutorials
- 53 minutes of instruction
- Created by Barton Poulson, PhD

## Data Visualization: Foundations of Data Science, Part 3.

### Course DESCRIPTION

Images are extraordinarily dense in information, which makes the graphical visualization of data one of the most insightful and important steps in any data science project.

*This course is currently in development with a planned release in the fall of 2017.*

## Coding: Foundations of Data Science, Part 4.

### Course DESCRIPTION

Data science professionals rely on a range of tools, from basic spreadsheets to advanced languages like R and Python. In these videos, we’ll cover the basic elements of the most important tools for data science. Coding is the fourth of seven courses designed to outline the principles and practices of applied data science.

### COURSE INFORMATION

- Introductory level
- 16 streaming video tutorials
- 1 hour 28 minutes of instruction
- Created by Barton Poulson, PhD

## Mathematics: Foundations of Data Science, Part 5.

### Course DESCRIPTION

Data science relies on several important aspects of mathematics. In this course, you’ll learn what forms of mathematics are most useful for data science, and see some worked examples of how math can solve important data science problems.

### COURSE INFORMATION

- Introductory level
- 10 streaming video tutorials
- 52 minutes of instruction
- Created by Barton Poulson, PhD

## Statistics: Foundations of Data Science, Part 6.

### Course DESCRIPTION

Statistics is distinct from - but critical to - data science. In this non-technical, conceptual overview, you can learn how statistical practices such as data exploration, estimation, and feature selection give data science its power and insight.

### COURSE INFORMATION

- Introductory level
- 15 streaming video tutorials
- 1 hour 18 minutes of instruction
- Created by Barton Poulson, PhD

## Machine Learning: Foundations of Data Science, Part 7.

### Course DESCRIPTION

Machine learning, deep learning, and artificial intelligence are the superstars of the data science world. We’ll review the critical elements of this field, including how machine learning algorithms are programmed, how they can be applied, and what they mean to people in all walks of life.

*This course is currently in development with a planned release in the fall of 2017.*