1929502_9383_95

IBM: SQL for Data Science

92,00 

Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases – a must for anyone working in the data science field.

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About this course

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Much of the world’s data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and extracting various data types from databases. A working knowledge of databases and SQL is necessary to advance as a data scientist or a machine learning specialist. The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment.

The emphasis in this course is on hands-on, practical learning. As such, you will work with real databases, real data science tools, and real-world datasets. You will create a database instance in the cloud. Through a series of hands-on labs, you will practice building and running SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python.

No prior knowledge of databases, SQL, Python, or programming is required.

At a glance

  • Institution: IBM
  • Subject: Data Analysis & Statistics
  • Level: Introductory
  • Prerequisites:
    None
  • Language: English
  • Video Transcripts: اَلْعَرَبِيَّةُ, Deutsch, English, Español, Français, हिन्दी, Bahasa Indonesia, Português, Kiswahili, తెలుగు, Türkçe, 中文
  • Associated programs:
    • Professional Certificate in Data Science Foundations
    • Professional Certificate in Data Engineering Fundamentals
    • Professional Certificate in IBM Data Science
    • Professional Certificate in Data Analyst
    • Professional Certificate in Data Engineering
  • Associated skills:Python (Programming Language), Relational Databases, Jupyter, Data Science, Machine Learning, SQL (Programming Language)

What you’ll learn

  • Explain fundamentals of databases and relational database management systems (RDBMS)
  • Execute basic SQL queries using SELECT, INSERT, UPDATE, and DELETE
  • Use string patterns and ranges to query and filter data
  • Sort and group data in result sets and use built-in database functions
  • Query multiple tables and compose nested SELECT statements and sub-queries
  • Analyze data in a database using Python and Jupyter Notebooks

Additional information

Weeks

4

Language

English

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