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.
Ce cours fait partie de la Spécialisation Data Science with Databricks for Data Analysts
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À propos de ce cours
Completion of the first two courses in the Data Science with Databricks for Data Analysts Coursera specialization. This course is the final course.
Ce que vous allez apprendre
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.
Compétences que vous acquerrez
- Data Science
- Machine Learning
- Databricks
Completion of the first two courses in the Data Science with Databricks for Data Analysts Coursera specialization. This course is the final course.
Offert par

Databricks
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.
Programme de cours : ce que vous apprendrez dans ce cours
Welcome to the Course
Applied Unsupervised Learning
Feature Engineering and Selection
Applied Tree-based Models
Avis
- 5 stars68,96 %
- 4 stars13,79 %
- 2 stars10,34 %
- 1 star6,89 %
Meilleurs avis pour APPLIED DATA SCIENCE FOR DATA ANALYSTS
Great course for an overview but with a high level of abstraction (usage of existing libraries but very little coding of algorithms that show the details of the principles)
À propos du Spécialisation Data Science with Databricks for Data Analysts
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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