課程信息

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中級
完成時間大約為13 小時
英語(English)
字幕:英語(English)

您將學到的內容有

  • U​se the collaborative Databricks workspace and write SQL code that executes against a cluster of machines

  • Use Spark UI to analyze performance and identify bottlenecks

  • Create an end-to-end pipeline that reads data, transforms it, and saves the result

  • B​uild a linear regression model and make predictions using SparkSQL

您將獲得的技能

Data ScienceApache SparkSQL
可分享的證書
完成後獲得證書
100% 在線
立即開始,按照自己的計劃學習。
可靈活調整截止日期
根據您的日程表重置截止日期。
中級
完成時間大約為13 小時
英語(English)
字幕:英語(English)

提供方

加州大学戴维斯分校 徽標

加州大学戴维斯分校

教學大綱 - 您將從這門課程中學到什麼

1

1

完成時間為 3 小時

Introduction to Spark

完成時間為 3 小時
6 個視頻 (總計 32 分鐘), 3 個閱讀材料, 2 個測驗
6 個視頻
Why Distributed Computing?7分鐘
Spark DataFrames6分鐘
The Databricks Environment8分鐘
SQL in Notebooks3分鐘
Import Data2分鐘
3 個閱讀材料
A Note From UC Davis10分鐘
Readings and Resources40分鐘
Assignment #1 - Queries in Spark SQL30分鐘
2 個練習
Assignment #1 Quiz - Queries in Spark SQL30分鐘
Module 1 Quiz30分鐘
2

2

完成時間為 2 小時

Spark Core Concepts

完成時間為 2 小時
6 個視頻 (總計 25 分鐘), 2 個閱讀材料, 2 個測驗
6 個視頻
Spark Terminology3分鐘
Caching5分鐘
Shuffle Partitions7分鐘
Spark UI3分鐘
Broadcast Joins3分鐘
2 個閱讀材料
Readings30分鐘
Assignment #2 - Spark Internals30分鐘
2 個練習
Assignment #2 Quiz - Spark Internals30分鐘
Module 2 Quiz30分鐘
3

3

完成時間為 3 小時

Engineering Data Pipelines

完成時間為 3 小時
7 個視頻 (總計 43 分鐘), 2 個閱讀材料, 2 個測驗
7 個視頻
Spark as a Connector6分鐘
Accessing Data10分鐘
File Formats8分鐘
Schemas and Types4分鐘
Writing Data6分鐘
Managed and Unmanaged Tables4分鐘
2 個閱讀材料
Readings1小時
Assignment #3 - Engineering Data Pipelines30分鐘
2 個練習
Assignment #3 Quiz - Engineering Data Pipelines30分鐘
Module 3 Quiz30分鐘
4

4

完成時間為 5 小時

Machine Learning Applications of Spark

完成時間為 5 小時
7 個視頻 (總計 35 分鐘), 2 個閱讀材料, 3 個測驗
7 個視頻
Applications of Machine Learning4分鐘
Machine Learning Fundamentals6分鐘
Linear Regression6分鐘
Training Linear Regression Model8分鐘
Applying Machine Learning with UDFs4分鐘
Course Summary3分鐘
2 個閱讀材料
Readings1小時
Assignment #4 - Logistic Regression Classifier10分鐘
2 個練習
Assignment #4 Quiz - Logistic Regression Classifier30分鐘
Module 4 Quiz30分鐘

審閱

來自DISTRIBUTED COMPUTING WITH SPARK SQL的熱門評論

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關於 Learn SQL Basics for Data Science 專項課程

This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, and more. These topics will prepare you to apply SQL creatively to analyze and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering, use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets....
Learn SQL Basics for Data Science

常見問題

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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