# Data science

This is the first installment in the datalab.cc series "Foundations of Data Science."

# DATA SCIENCE: An INtroduction // FOUNDATIONS OF DATA SCIENCE, PART 1

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. _Data Science: An Introduction_ is the first of five courses designed to outline the principles and practices of applied data science.

## Course Information

- Introductory level
- 22 streaming video tutorials
- 1 hour 40 minutes of instruction
- Created by Barton Poulson
- Released 26 July 2016

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Welcome - Data Science: An Introduction - 1.1 - YouTube

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[Welcome - Data Science: An Introduction - 1.1](https://www.youtube.com/watch?v=0uKk6YPWS50) [datalabcc](https://www.youtube.com/channel/UC4FWYTxQi-ht7W2JXHeQDuw)

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_Note._ To navigate the videos, click on the menu icon (☰) at the top right of the video.

## Table of Contents

### INTRODUCTION

- Welcome {1:58}

### DEFINING DATA SCIENCE

- Demand for data science {5:45}
- The data science Venn diagram {6:58}
- The data science pathway {4:49}
- Roles in data science {4:00}
- Teams in data science {3:32}

### CONTRASTS

- Big data {4:57}
- Coding {3:02}
- Statistics {4:17}
- Business intelligence {3:05}

### ETHICAL ISSUES

- Do no harm {6:02}

### METHODS

- Methods overview {2:21}
- Sourcing overview {3:41}
- Coding overview {3:32}
- Math overview {4:00}
- Statistics overview {4:03}
- Machine learning overview {2:44}

### COMMUNICATING

- Interpretability {9:07}
- Actionable insights {5:15}
- Presentation graphics {7:12}
- Reproducible research {6:11}

### CONCLUSION

- Next steps {3:11}