Introduction to Data Science

1. Data analytics

1.1. What it is?

1.1.1. Data analytics helps individuals and organizations make sense of data.

1.2. Differences from data science

1.2.1. The way they work with the data (statistical analysis)

2. Big Data

2.1. What it is?

2.1.1. Tools that facilitate the analysis and storage of the data.

2.2. To have a risk-controlled decisions

2.2.1. Statistical analysis

2.2.1.1. Science of changing your mind

3. Skills

3.1. This video tell us more context about this skills.

3.2. Statistical analysis and computing

3.3. Machine Learning

3.4. Data Visualization

3.5. Mathematics

3.6. Programming

4. To know more..

4.1. https://0-eds-p-ebscohost-com.biblioteca-ils.tec.mx/eds/detail/detail?vid=1&sid=e3b81315-35fa-47b5-938b-68d1c6e6f07e%40redis&bdata=Jmxhbmc9ZXMmc2l0ZT1lZHMtbGl2ZSZzY29wZT1zaXRl#AN=bdis.b1844114&db=cat03431a

4.2. This book tell us What is data science, What is data and what is a dataset?, The data science ecosystem

5. What it is?

5.1. Field of applying advanced analytics techniques and scientific principles that analyze data for actionable insights.

6. Applications

6.1. Banking

6.1.1. An example was the movie clip 2, banks through the use of their users' data, implemented rules to create mortgages.

6.2. Marketing

6.2.1. As through a data study, a company can predict sales in the music field.

6.3. Other disciplines

6.3.1. Healthcare

6.3.2. Sports and gaming

6.3.3. Social media

6.3.4. E-commerce

6.3.5. Government

6.3.6. Transportation

7. Importance

7.1. In this talk, Joseph Kachiliko speaks to the everyday person on the benefits of becoming more data literate.