$29.95
$19.99
0% Off
$0
$0
$29.95
$19.99
0% Off
$0
$0
The Databricks Certified Machine Learning Associate course covers building and tracking ML models using Databricks and MLflow. You'll work through structured video lessons and exam-style practice questions that mirror the real ML Associate exam, building the practical judgment needed to apply these skills on the job. By the end, you'll be ready to sit the ML Associate exam and earn the Databricks Certified Machine Learning Associate credential. This Databricks Certified Machine Learning Associate training pairs guided lessons with a full Databricks Certified Machine Learning Associate practice test, so you walk into the ML Associate exam fully prepared.
Whether you're brand new to this area or brushing up before the ML Associate exam, this course paces the material so nothing feels rushed.
ML workflows on the Databricks Lakehouse platform
Model training and evaluation with common libraries
Experiment tracking and model management with MLflow
Basic model deployment concepts
24x7 support from Databricks-certified experts
This course is valid for 2 years from the date of purchase
Practice tests with unique, exam-style questions
Detailed explanations for every practice question
Hands-on labs using real Databricks services
Downloadable ML Associate cheat sheet for quick revision
Official domain-by-domain weightings for the ML Associate exam were not included in the source data for this page, so the skill areas below are listed without percentage breakdowns. Verify current weightings on the vendor's official Databricks Certified Machine Learning Associate exam guide before publishing.
ML workflows on the Databricks Lakehouse platform
Model training and evaluation with common libraries
Experiment tracking and model management with MLflow
Basic model deployment concepts
The Databricks Certified Machine Learning Associate course lays out a clear path to the ML Associate exam, so you're not guessing what to study next.
Start with the video lessons in this Databricks Certified Machine Learning Associate course to build a working understanding of the core concepts the ML Associate exam covers. Then move into the hands-on labs to apply what you've learned in a real environment instead of just reading about it.
Next, work through the ML Associate practice test set. Each Databricks Certified Machine Learning Associate practice test question comes with a detailed explanation, so a wrong pick becomes a lesson you actually retain.
When your ML Associate practice test scores stay consistently above the passing mark, you're ready to book the Databricks Certified Machine Learning Associate exam. For a fuller walkthrough, refer to a dedicated Databricks Certified Machine Learning Associate exam preparation guide alongside this course.
The ML Associate certification has no mandatory prior certification requirement.
Once you pass, the Databricks Certified Machine Learning Associate certification stays valid for 2 Years. Before it expires, you can renew the ML Associate certification by retaking the current exam.
Many learners treat the Databricks Certified Machine Learning Associate certification as a step within a broader vendor certification track. Check Whizlabs' related course listings for a logical next-level credential once you've completed this ML Associate course.
This certification validates your ability to work with building and tracking ML models using Databricks and MLflow. It signals to employers that you can apply these skills in real Databricks projects, supporting stronger roles, responsibilities, and career growth.
Positions you for data scientists and ml engineers roles, and signals proven, job-ready expertise in building and tracking ML models using Databricks and MLflow.
Helps your organization apply building and tracking ML models using Databricks and MLflow more effectively, reducing risk and improving efficiency in real deployments.
Deepens your hands-on understanding of building and tracking ML models using Databricks and MLflow, moving beyond theory into practical, job-ready skills.
Associate-level certifications like this are consistently linked to stronger salaries and career growth in Databricks-related roles.
Exam Format and Information
Prior Certification
Not Required
Exam Validity
2 Years
Exam Fee
200 USD
Exam Duration
90 Minutes
No. of Questions
45 Questions
Passing Score
70%
Best for those with hands-on or working familiarity with building and tracking ML models using Databricks and MLflow.
English.
Multiple choice questions.
There are no formal prerequisites for this exam. Hands-on experience with building and tracking ML models using Databricks and MLflow makes it more approachable. It's designed for data scientists, ml engineers, and anyone building these skills.
Data scientists working with building and tracking ML models using.
ML engineers preparing for associate-level certification.
IT professionals expanding into this specialization.
Consultants advising clients on Databricks best practices.
Students and career changers entering the field.
Anyone pursuing the ML Associate credential.
Yes, you can pass Databricks Certified Machine Learning Associate Certification without any working experience.
Databricks machine learning certification costs around $200 (Databricks partners get 50% off the registration fee).
Deep learning and machine learning are both subfields of artificial intelligence (AI) that adopt machines to learn from data. Machine learning contains a broader set of techniques, including traditional statistical methods, while deep learning specifically employs neural network-based approaches.
Azure Databricks, built on Spark, supports commonly used programming languages such as Python, R, and SQL.
Databricks Certified Machine Learning Associate Certification has a validity period of two years. This period is measured from the date on which the candidate successfully passes the certification exam. After the two-year timeframe, individuals are typically required to recertify to maintain the validity of their certification.
Engaging in this certification can offer a deeper understanding of how Databricks can be effectively utilized to address machine learning-related challenges.
Databricks function as an Extract, Transform, Load (ETL) tool to improve the efficiency and capabilities of data processing and analysis within ETL pipelines.
Yes, Databricks is widely regarded as a robust platform for Machine Learning (ML). It provides a unified analytics platform built on top of Apache Spark, making it efficient for handling large-scale data processing and ML tasks. Databricks offers a collaborative environment that seamlessly integrates with popular ML libraries and frameworks.
