Applied Data Science for Data Analysts
Updated on
Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Intermediate
- Deadline
- Flexible
- Duration
- 16 hours
- Certificate
- Paid Certificate Available
- Course author
- Kevin Coyle
-
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.
Description
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.NOTE: This is the third and final course in the Data Science with Databricks for Data Analysts Coursera specialization. To be successful in this course we highly recommend taking the first two courses in that specialization prior to taking this course. These courses are: Apache Spark for Data Analysts and Data Science Fundamentals for Data Analysts.
