Intermediate SQL for data analysis (no installation needed!)
What you'll learn
- sql
- sql server
- analytics
- data analysis
- no installation required
Course content
- Preview01:38
Requirements
- basic knowledge of sql
- select statements (from, group by, where, having, order by)
- joins (left, inner)
- built in functions (sum, min/max, count, count distinct etc.)
Description
This course is for people who already own basic knowledge of SQL who want to expand their knowledge and really become data savvy and either land a BI job, improve their skills, or become a self reliant business user in their organization. If you want to get work as a data analyst, if you are a junior analyst and want to get better fast, or if you are a developer, a data scientist or a student who is used to working with R and Python but need to up your SQL game - this is the course for you. If you are a sophisticated business user who uses sql mainly to extract data to worksheets and continue in excel - you will be delighted in what you'll be able to do WITHOUT excel after this course. The course focuses on tackling real life day to day problems, and does not waste time with endless joins and needless focus on syntax. Syntax is always a google search away, understanding what's possible (i.e., know what you don't know) is not.
Who this course is for:
- junior analysts
- beginner analysts
- college students or graduates in data driven fields
- data scientists or developers that want to improve their sql
- any corporate user who has access to data bases and wants to do more than just retrieve data into spreadsheets
Instructor
![Guy Manova](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.1 Instructor Rating
- 26 Reviews
- 3,160 Students
- 1 Course
During the last decade+ I have worked in tech start ups analyzing and visualizing data, building data products and designing and engineering data flows and data automation. I love to teach and share knowledge, and believe you can't be successful in today's work places without being extremely data literate - able to obtain data by yourself, analyze it, understand it, and be aware of it's pitfalls, misrepresentations and biases.