Databricks Machine Learning Associate Exam Questions 2024
- We are offering 423 latest real Databricks Machine Learning Associate Exam Questions 2024 Exam Questions 2024 for practice, which will help you to score higher in your exam.
- Aim for above 85% or above in our mock exams before giving the main exam.
- Do review wrong & right answers and thoroughly go through explanations provided to each question which will help you understand the question.
- Master Cheat Sheet was prepared by instructors which contain personal notes of them for all exam objectives. Carefully written to help you all understand the topics easily.
- It is recommended to use the Master Cheat Sheet just before 2-3 days of the main exam to cram the important notes.
The Databricks Certified Machine Learning Associate credential validates your ability to perform fundamental machine learning tasks using Databricks. This can be a valuable asset for data professionals seeking to advance their careers in data science or machine learning engineering. According to Indeed, data scientists with Databricks expertise command an average salary that’s around 10% higher than the national average for data scientists.
Exam format:
- Number of questions: 45 multiple choice
- Time limit: 90 minutes
- Delivery method: Online proctored exam (no physical location required)
- Cost: $200 USD (plus applicable taxes)
- Validity: 2 years (recertification required after 2 years to maintain certification)
- Allowed materials: No outside materials or aids are permitted during the exam
Exam Focus: Core ML Skills on Databricks
The exam delves into several key areas to assess your proficiency in Databricks-powered machine learning:
- Data Preparation: Get ready for questions on how to effectively prepare and wrangle data for ML tasks within the Databricks environment.
- Model Building and Evaluation: You’ll be evaluated on your grasp of training and evaluating machine learning models using Databricks’ built-in tools and functionalities.
- Spark ML Expertise: Expect questions on designing and implementing machine learning workflows with Spark ML, a library within the Apache Spark ecosystem for distributed machine learning.
- Databricks ML Features: The exam will assess your understanding and ability to apply features offered by Databricks Machine Learning, including AutoML for automated model selection and Feature Store for centralized feature management.
- Scaling Considerations: A crucial aspect of production machine learning is model scalability. The exam will gauge your understanding of how to scale ML models effectively on Databricks.
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