Mastering Databricks: Unified Data Analytics

Harness the power of Databricks for enterprise-grade big data processing, AI integration, and advanced analytics.

  • English
  • Certified Course
Databricks Course

What you'll learn

Develop deep expertise in Databricks and design scalable data-driven solutions using Apache Spark.

  • Gain a comprehensive understanding of Databricks architecture and core platform capabilities
  • Perform distributed data processing at scale using Apache Spark
  • Build and deploy machine learning models seamlessly within the Databricks environment
  • Design and optimize robust data pipelines for ETL and real-time processing
  • Apply best practices for building responsive analytics systems with enterprise-grade reliability

This course is meticulously crafted for data engineers, analysts, and AI professionals aiming to master unified analytics on Databricks.

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Course Content

  • Deep dive into Databricks’ architecture and unified analytics platform
  • Fundamental principles of Apache Spark and its distributed computing ecosystem
  • Configuring and deploying your first Databricks workspace in a cloud environment

  • Ingesting and transforming diverse datasets (structured and unstructured)
  • Designing high-throughput ETL pipelines with Spark
  • Performance tuning and optimization techniques for Spark-based data workflows

  • Building and managing ML models using integrated MLflow tools
  • Operationalizing AI through deployment on the Databricks platform
  • Leveraging real-world use cases to implement AI across business verticals

Requirements

  • Foundational understanding of cloud platforms and data analytics principles
  • Prior experience with Python or SQL is advantageous
  • Strong interest in scalable data processing and applied artificial intelligence
  • No previous experience with Databricks is necessary

Description

  • Acquire industry-relevant skills in processing large-scale datasets with Databricks
  • Engineer scalable ML pipelines and AI models using Apache Spark
  • Explore high-impact applications of AI and optimize performance in unified analytics environments