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Applied SQL For Data Analytics Data Science With BigQuery

      Author: Baturi   |   21 January 2021   |   comments: 0


Applied SQL For Data Analytics  Data Science With BigQuery
Applied SQL For Data Analytics / Data Science With BigQuery
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 10h 32m | 5.14 GB
Instructor: Jeff James


Go from SQL Zero to Hero and develop rich mental models for writing sophisticated SQL statements & solving problems.
What you'll learn
SQL 101: The basics (SELECT, WHERE, HAVING, JOIN's, dealing with dates and timestamps)
SQL 202: Date Handling, CASE statements, Common Table Expressions, Subqueries, Correlated Subqueries
Develop clear models of translating business requirements to SQL
Master Window / Analytic Functions, which are the power tools of modern data-science SQL
100% of videos are code along and provide numerous points to stop and "solve it" before me.
Requirements
Be able to write very basic SQL statements or at least understand what rows and columns are
Have a google account since we use BigQuery
Description
Woah, another SQL course? Yes! Here's why this one is different.
1. We write 100% of the code together and I explain everything precisely and with abundant context. I have over a decade of industry experience over have taught this at the university level.
2. 100% we do is application based. I rarely use toy data to illustrate points, unless it's more illustrative. Hopefully you'll learn much more than SQL throughout the course.
3. ZERO SET-UP. As long as you have a Google Account, you can login to BigQuery and get started immediately. No headaches configuring databases locally. You'll be up and running in under 3 minutes.
4. Spaced repetition to develop mastery. This is NOT a table of contents course. This is NOT a list of disparate exercises. Everything is connected. Concepts are revisited throughout the course so you can see them from different angles and maximize understanding.
5. Can you solve it? I provide tons of mini-challenges throughout the lecture material. The lecture material is basically us solving the problems. No time wasted on theory without context.
6. I'm not boring. I am human. I do make mistakes. I dwell on them so you can master the debugging process. Debugging is much more important than writing code.
Who this course is for:
SQL beginners
Aspiring data scientists or data scientists who don't leverage SQL
Data analysts
Product managers who want to get better with DIY analysis.
Developers who are interested in SQL!
People interested in BigQuery that already know some SQL.
https://www.udemy.com/course/applied-sql-for-data-analytics-data-science-with-bigquery/



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