DCPDS Exam Information and Guideline
Databricks Certified Professional Data Scientist
Below are complete topics detail with latest syllabus and course outline, that will help you good knowledge about exam objectives and topics that you have to prepare. These contents are covered in questions and answers pool of exam.
Exam Detail:
The DCPDS (Databricks Certified Professional Data Scientist) exam is a certification exam that validates the knowledge and skills of individuals in data science using Databricks. Here are the exam details for the DCPDS certification:
- Number of Questions: The exam typically consists of multiple-choice questions and hands-on exercises. The exact number of questions may vary, but typically, the exam includes around 60 to 80 questions.
- Time Limit: The time allocated to complete the exam is 2 hours (120 minutes).
Course Outline:
The DCPDS certification course covers various topics related to data science using Databricks. The course outline typically includes the following topics:
1. Introduction to Databricks:
- Understanding the basics of Databricks and its role in data science.
- Navigating the Databricks workspace and user interface.
2. Data Exploration and Preparation:
- Exploring and understanding data using Databricks.
- Performing data preprocessing tasks such as data cleaning, transformation, and feature engineering.
3. Machine Learning with Databricks:
- Applying machine learning algorithms and techniques using Databricks.
- Building and training machine learning models.
- Evaluating and tuning model performance.
4. Advanced Analytics and Visualization:
- Using Databricks for advanced analytics tasks such as clustering, time series analysis, and text analysis.
- Visualizing data and model results using Databricks' visualization tools.
5. Model Deployment and Monitoring:
- Deploying machine learning models in production using Databricks.
- Monitoring and evaluating model performance and making necessary adjustments.
6. Collaborative Workflows:
- Working collaboratively with other data scientists and stakeholders in Databricks.
- Sharing and presenting insights and results using Databricks' collaboration features.
Exam Objectives:
The objectives of the DCPDS exam are as follows:
- Assessing candidates' understanding of Databricks and its role in data science.
- Evaluating candidates' knowledge and proficiency in data exploration and preparation using Databricks.
- Testing candidates' skills in applying machine learning algorithms and techniques using Databricks.
- Assessing candidates' ability to perform advanced analytics tasks and visualize data in Databricks.
- Evaluating candidates' competence in deploying and monitoring machine learning models in Databricks.
- Testing candidates' understanding of collaborative workflows and effective communication in Databricks.
Exam Syllabus:
The specific exam syllabus for the DCPDS certification covers the following areas:
1. Databricks Basics: Understanding the Databricks workspace, user interface, and collaborative features.
2. Data Exploration and Preparation: Performing data exploration, cleaning, and transformation using Databricks.
3. Machine Learning with Databricks: Applying machine learning algorithms and techniques in Databricks.
4. Advanced Analytics and Visualization: Performing advanced analytics tasks and visualizing data in Databricks.
5. Model Deployment and Monitoring: Deploying and monitoring machine learning models in Databricks.
6. Collaborative Workflows: Working collaboratively and effectively communicating with stakeholders in Databricks.