Analyzing Big Data with SQL

Analyzing Big Data with SQL

МООК
en
Английский
17 h
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Source
  • From www.coursera.org
Conditions
  • Self-paced
  • Free Access
More info
  • 6 Sequences
  • Introductive Level

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Course details

Syllabus

WEEK 1 - Orientation to SQL on Big Data
9 videos (Total 47 min), 5 readings, 2 quizzes

WEEK 2 - SQL SELECT Essentials
16 videos (Total 83 min), 4 readings, 2 quizzes

WEEK 3 - Filtering Data
14 videos (Total 85 min), 6 readings, 2 quizzes

WEEK 4 - Grouping and Aggregating Data
15 videos (Total 82 min), 6 readings, 2 quizzes

WEEK 5 - Sorting and Limiting Data
14 videos (Total 70 min), 1 reading, 2 quizzes

WEEK 6 - Combining Data
12 videos (Total 61 min), 5 readings, 3 quizzes

Prerequisite

To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements:
• Windows, macOS, or Linux operating system (iPads and Android tablets will not work)
• 64-bit operating system (32-bit operating systems will not work)
• 8 GB RAM or more
• 25GB free disk space or more
• Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled;
on Windows and Linux computers, you might need to enable it in the BIOS)
• For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)

Instructors

Ian Cook
Senior Curriculum Developer
Cloudera

Editor

Cloudera

Platform

Coursera - это цифровая компания, предлагающая массовые открытые онлайн-курсы, основанные учителями компьютеров Эндрю Нгом и Стэнфордским университетом Дафни Коллер, расположенные в Маунтин-Вью, штат Калифорния.

Coursera работает с ведущими университетами и организациями, чтобы сделать некоторые из своих курсов доступными в Интернете, и предлагает курсы по многим предметам, включая: физику, инженерию, гуманитарные науки, медицину, биологию, социальные науки, математику, бизнес, информатику, цифровой маркетинг, науку о данных и другие предметы.

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