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.
本课程是 Data Science with Databricks for Data Analysts 专项课程 专项课程的一部分
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第 3 门课程（共 3 门）
中级
Completion of the first two courses in the Data Science with Databricks for Data Analysts Coursera specialization. This course is the final course.
完成时间大约为16 小时
英语（English）
字幕：英语（English）
您将学到的内容有
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.
您将获得的技能
- Data Science
- Machine Learning
- Databricks
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 3 门课程（共 3 门）
中级
Completion of the first two courses in the Data Science with Databricks for Data Analysts Coursera specialization. This course is the final course.
完成时间大约为16 小时
英语（English）
字幕：英语（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.
授课大纲 - 您将从这门课程中学到什么
完成时间为 2 小时
Welcome to the Course
完成时间为 2 小时
8 个视频 （总计 40 分钟）, 2 个阅读材料, 1 个测验
完成时间为 3 小时
Applied Unsupervised Learning
完成时间为 3 小时
15 个视频 （总计 69 分钟）, 2 个阅读材料, 6 个测验
完成时间为 3 小时
Feature Engineering and Selection
完成时间为 3 小时
17 个视频 （总计 71 分钟）, 2 个阅读材料, 6 个测验
完成时间为 6 小时
Applied Tree-based Models
完成时间为 6 小时
14 个视频 （总计 60 分钟）, 10 个阅读材料, 9 个测验
关于 Data Science with Databricks for Data Analysts 专项课程
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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