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Databricks is a cloud-based data platform that provides an open-source Apache Spark-based analytics platform. It is used by many leading companies across the world, such as Shell, HP, and Cisco, to name a few. The Databricks Certified Professional Data Scientist Exam is designed to test the skills and knowledge of data scientists who use Databricks software in their work.
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Databricks Certified Professional Data Scientist certification exam is designed to test the skills and knowledge of data scientists working with the Databricks platform. Databricks-Certified-Professional-Data-Scientist exam covers a wide range of topics including data preparation, data exploration, machine learning, deep learning, natural language processing, and model deployment. Databricks Certified Professional Data Scientist Exam certification is ideal for data scientists who are looking to demonstrate their expertise in using Databricks to solve complex data problems and build scalable machine learning models.
Databricks Certified Professional Data Scientist certification exam is a highly respected and recognized certification that validates the skills and knowledge of individuals in the field of data science. Databricks Certified Professional Data Scientist Exam certification exam is designed to test the candidate's proficiency in using Databricks for data manipulation, modeling, and analysis. Databricks-Certified-Professional-Data-Scientist exam is developed and administered by Databricks, the leading provider of cloud-based data analytics platforms.
Reference: https://credentials.databricks.com/group/227970
A Databricks Certified Professional Data Scientist has the skills and knowledge needed to work effectively with data using Databricks tools. They can prepare data, build machine learning models, and perform data analysis to derive insights that can be used to inform business decisions. Databricks Certified Professional Data Scientist Exam certification demonstrates that the individual has a deep understanding of data science concepts and can apply them effectively in real-world scenarios.
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Databricks Databricks-Certified-Professional-Data-Scientist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Model Management & Deployment | 20% | - Model registry and versioning - Experiment tracking and reproducibility with MLflow - Monitoring and interpretability - Model deployment and serving on Databricks |
| Model Development & Algorithms | 30% | - Spark MLlib and distributed algorithms - Unsupervised methods: clustering, PCA, anomaly detection - Regression models: linear, logistic, regularized - Tree-based models: decision trees, random forest, gradient boosting |
| Machine Learning Fundamentals | 25% | - Statistical concepts and bias-variance tradeoff - Types of machine learning: supervised, unsupervised, reinforcement - In-sample vs out-of-sample evaluation |
| Data Preparation & Feature Engineering | 25% | - Feature construction, scaling, encoding, and selection - Using Databricks for data processing - Data cleaning, transformation, and validation |
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