Description
Welcome to our comprehensive course on Databricks Certified Machine Learning Engineer Associate certification. This course is designed to help you master the skills required to become a certified Databricks ML engineer associate.Databricks is a cloud-based data analytics platform that offers a unified approach to data processing, machine learning, and analytics. With the growing demand for data engineers, Databricks has become one of the most sought-after skills in the industry.
The minimally qualified candidate should be able to:
- Use Databricks Machine Learning and its capabilities within machine learning workflows, including:
- Databricks Machine Learning (clusters, Repos, Jobs)
- Databricks Runtime for Machine Learning (basics, libraries)
- AutoML (classification, regression, forecasting)
- Feature Store (basics)
- MLflow (Tracking, Models, Model Registry)
- Implement correct decisions in machine learning workflows, including:
- Exploratory data analysis (summary statistics, outlier removal)
- Feature engineering (missing value imputation, one-hot-encoding)
- Tuning (hyperparameter basics, hyperparameter parallelization)
- Evaluation and selection (cross-validation, evaluation metrics)
- Implement machine learning solutions at scale using Spark ML and other tools, including:
- Distributed ML Concepts
- Spark ML Modeling APIs (data splitting, training, evaluation, estimators vs. transformers, pipelines)
- Hyperopt
- Pandas API on Spark
- Pandas UDFs and Pandas Function APIs
- Understand advanced scaling characteristics of classical machine learning models, including:
- Distributed Linear Regression
- Distributed Decision Trees
- Ensembling Methods (bagging, boosting)
Who this course is for:
- Anyone wants to Pass Databricks Certified Machine Learning Associate Exam
