[Voiceover]- The first thing I wanna talk about in terms of…Programming and Data Science is the role of spreadsheets…in Data Science.…Now, spreadsheets may not seem…like a very fancy or sophisticated tool,…but they are often the right tool…for the job that you're working on.…There's a few reasons for this.…First off, spreadsheets are everywhere.…Microsoft Excel is on nearly every PC ever made,…Google Sheets can be accessed from all of them,…also, spreadsheets are often the preferred format…from the client.…
When they give you the data,…it'll often be in a spreadsheet, so you have to be able to…work fluently with them, simply to get started…for your analysis.…Also, for data transfer, the spreadsheet format 'CSV',…or Comma Separated Values, is sort of like a 'Lingua Franca'…between data programs.…Any program can read a CSV file; any program can write them.…It allows you to transfer data from one program to another.…Also, easy to use; there are some operations…that are actually easier to do in spreadsheets…than in other programs, and I'll show you…
- Assess the skills required for a career in data science.
- Evaluate different sources of data, including metrics and APIs.
- Explore data through graphs and statistics.
- Discover how data scientists use programming languages such as R, Python, and SQL.
- Assess the role of mathematics, such as algebra, in data science.
- Assess the role of applied statistics, such as confidence intervals, in data science.
- Assess the role of machine learning, such as artificial neural networks, in data science.
- Define the components of effective data visualization.
Skill Level Beginner
1. What Is Data Science?
2. Fields of Study
Ethical issues2m 39s
4. Data Sources
5. Data Exploration
8. Applied Statistics
9. Machine Learning
Next steps2m 17s
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