Working knowledge of SQL (or Structured Query Language) is a must for data professionals like Data Scientists, Data Analysts and Data Engineers. Much of the world's data resides in databases. SQL is a powerful language used for communicating with and extracting data from databases. In this course you will learn SQL inside out- from the very basics of Select statements to advanced concepts like JOINs. You will: -write foundational SQL statements like: SELECT, INSERT, UPDATE, and DELETE -filter result sets, use WHERE, COUNT, DISTINCT, and LIMIT clauses -differentiate between DML & DDL -CREATE, ALTER, DROP and load tables -use string patterns and ranges; ORDER and GROUP result sets, and built-in database functions -build sub-queries and query data from multiple tables -access databases as a data scientist using Jupyter notebooks with SQL and Python -work with advanced concepts like Stored Procedures, Views, ACID Transactions, Inner & Outer JOINs through hands-on labs and projects You will practice building SQL queries, work with real databases on the Cloud, and use real data science tools. In the final project you’ll analyze multiple real-world datasets to demonstrate your skills.
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What is Data Science?
Databases and SQL for Data Science with Python
Data Science Methodology
Introduction to Data Analytics
Excel Basics for Data Analysis
Google Data Analytics Capstone: Complete a Case Study
Data Analysis with R Programming
Ask Questions to Make Data-Driven Decisions
Process Data from Dirty to Clean
Data Visualization and Dashboards with Excel and Cognos
Foundations: Data, Data, Everywhere
Tools for Data Science
Analyze Data to Answer Questions
Prepare Data for Exploration
Accelerate Your Job Search with AI
Share Data Through the Art of Visualization
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Primary 4 Mathematics
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Mga Komento
10 Mga Komento
Outer Joins
Outer Joins
Outer Joins
Inner Join
Inner Join
Inner Join
Join Overview
Join Overview
Join Overview
ACID Transactions
