- Level Professional
- Duration 17 hours
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Offered by
About
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.Auto Summary
Enhance your data science skills with "Applied Data Science for Data Analysts." This professional-level course, part of Coursera's Data Science with Databricks specialization, focuses on real-world problem-solving using unsupervised and supervised learning, feature engineering, and model optimization. Taught by Coursera, it spans approximately 1020 minutes and is available through Starter and Professional subscriptions. Ideal for data analysts seeking advanced expertise.