Join Dan Sullivan for an in-depth discussion in this video Exercise files, part of Advanced SQL for Data Scientists.
- [Instructor] If you have access to the Exercise Files for this course, you can follow along. The Exercise Files are organized into folders, one for each chapter that has an Exercise File. Each chapter folder is further organized into videos. Each video that has an Exercise File has a folder. Within that folder, you'll see one or more SQL files. These files contain SQL commands we will use throughout the course. I will type most of the commands through this course, but we will execute one file to create our database schema and load data.
I'd like to point out that the dataset you'll be working with is going to be set up in Chapter Two. Now because of that, the subsequent Exercise Files aren't start states, rather they're files with faux queries that we'll be running. Also, there are some actions in the middle of the course that you'll have to follow along with so that the later queries work.
The course begins with a brief overview of SQL. Then the five major topics a data scientist should understand when working with relational databases: basic statistics in SQL, data preparation in SQL, advanced filtering and data aggregation, window functions, and preparing data for use with analytics tools.
- Data manipulation
- ANSI standards
- SQL and variations
- Statistical functions in SQL
- String, numeric, and regular expression functions in SQL
- Advanced filtering techniques
- Advanced aggregation techniques
- Windowing functions for working with ordered data sets
Skill Level Advanced
SQL: Data Reporting and Analysiswith Emma Saunders2h 16m Intermediate
1. SQL as a Tool for Data Science
SQL data definition features5m 32s
2. Basic Statistics with SQL
3. Data Munging with SQL
4. Filtering, Joins, and Aggregation
5. Window Functions and Ordered Data
6. Preparing Data for Analytics Tools
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