In this course, you will develop your data science skills while solving real-world problems. You'll work through the data science process to and use unsupervised learning to explore data, engineer and select meaningful features, and solve complex supervised learning problems using tree-based models. You will also learn to apply hyperparameter tuning and cross-validation strategies to improve model performance.
本課程是 Data Science with Databricks for Data Analysts 專項課程 專項課程的一部分
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課程信息
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完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 3 門課程（共 3 門）
中級
Completion of the first two courses in the Data Science with Databricks for Data Analysts Coursera specialization. This course is the final course.
完成時間大約為16 小時
英語（English）
字幕：英語（English）
您將學到的內容有
Explore data using unsupervised machine learning.
Solve complex supervised learning problems using tree-based models.
Apply hyperparameter tuning and cross-validation strategies to improve model performance.
您將獲得的技能
- Data Science
- Machine Learning
- Databricks
可靈活調整截止日期
根據您的日程表重置截止日期。
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。
第 3 門課程（共 3 門）
中級
Completion of the first two courses in the Data Science with Databricks for Data Analysts Coursera specialization. This course is the final course.
完成時間大約為16 小時
英語（English）
字幕：英語（English）
提供方
数据块
Databricks is the data and AI company. Founded by the creators of Apache Spark™, Delta Lake and MLflow, organizations like Comcast, Condé Nast, Nationwide and H&M rely on Databricks’ open and unified platform to enable data engineers, scientists and analysts to collaborate and innovate faster.
授課大綱 - 您將從這門課程中學到什麼
完成時間為 2 小時
Welcome to the Course
完成時間為 2 小時
8 個視頻 （總計 40 分鐘）, 2 個閱讀材料, 1 個測驗
完成時間為 3 小時
Applied Unsupervised Learning
完成時間為 3 小時
15 個視頻 （總計 69 分鐘）, 2 個閱讀材料, 6 個測驗
完成時間為 3 小時
Feature Engineering and Selection
完成時間為 3 小時
17 個視頻 （總計 71 分鐘）, 2 個閱讀材料, 6 個測驗
完成時間為 6 小時
Applied Tree-based Models
完成時間為 6 小時
14 個視頻 （總計 60 分鐘）, 10 個閱讀材料, 9 個測驗
關於 Data Science with Databricks for Data Analysts 專項課程
This specialization is intended for data analysts looking to expand their toolbox for working with data. Traditionally, data analysts have used tools like relational databases, CSV files, and SQL programming, among others, to perform their daily workflows. In this specialization, you will leverage existing skills to learn new ones that will allow you to utilize advanced technologies not traditionally linked to this role - technologies like Databricks and Apache Spark. By the end of this specialization, you'll be able to solve real-world business problems with Databricks and the most popular machine learning techniques.
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