Databricks Certified Data Engineer Associate

Databricks Certified Data Engineer Associate
Course 1: Databricks Lakehouse Platform
Description
Learn foundational Databricks capabilities including compute, storage, notebooks, and jobs to build scalable data solutions.
Learning Objectives
Create clusters and configure runtime environments

Perform exploratory analysis with notebooks

Schedule and monitor multi-task workflows

Course 2: Databricks SQL
Description
Master Spark SQL for reading, transforming, and loading data at scale. Learn techniques like data validation, custom business logic, and slowly changing dimensions.
Learning Objectives
Query data in notebooks with Spark SQL

Handle complex data types

Apply data quality rules

Implement slowly changing dimensions

Course 3: Databricks ML
Description
Build ML models with Python and Scala APIs in Databricks. Learn best practices for feature engineering, hyperparameter tuning, and model evaluation.
Learning Objectives
Engineer features from raw data

Tune models with cross validation

Evaluate model performance

Operationalize models with MLflow

Course 4: Databricks Data Engineering
Description
Architect reliable and performant data infrastructure with Delta Lake, streaming, and autoscaling.
Learning Objectives
Implement ACID transactions

Build streaming ETL solutions

Autoscale infrastructure to meet SLAs

Migrate data warehouses to lakehouse

Course 5: Workloads with Jobs
Description
Orchestrate workloads using multi-task Jobs with configurable scheduling, dependencies, and error handling.
Learning Objectives
Schedule notebooks, jobs and pipelines

Set dependencies across tasks

Handle and retry failures

Monitor runs using the Jobs UI

Course 6: Data Access with Unity Catalog
Description
Provide governed data access across storage like ADLS, S3, and GCS using Unity Catalog.
Learning Objectives
Deploy a Unity Catalog

Manage credentials securely

Apply object-level security

Query data from storage tiers

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