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Mastering Azure Databricks and PySpark: From basic to Pro
Rating: 3.9 out of 5(65 ratings)
1,825 students

Mastering Azure Databricks and PySpark: From basic to Pro

Empower Your Data Engineering Journey: Master Azure Databricks and PySpark for Scalable, Efficient, and Data Processing
Created byAtchyut Kumar, Edufulness EFN
Last updated 9/2024
English

What you'll learn

  • Gain a comprehensive knowledge of Azure Databricks, starting with the basics.
  • Learn to navigate the platform, understand its architecture, and leverage its key features for efficient big data processing.
  • Explore PySpark, the Python API for Apache Spark, from the ground up. Understand the core concepts of distributed data processing, transformations, and actions
  • Dive into real-world scenarios that replicate industry challenges.
  • Through practical examples and case studies, learn how to apply Azure Databricks and PySpark to solve common data processing issues, ensuring readiness
  • Build a live project from scratch, guiding students through the entire project lifecycle.
  • From data ingestion and cleaning to advanced analytics and visualization, students will apply their knowledge in a practical setting, reinforcing key concepts.
  • Discover optimization strategies and best practices to enhance the performance of your Azure Databricks and PySpark projects.
  • Learn how to troubleshoot common issues, implement efficient coding practices, and maximize the capabilities of the platform for streamlined data processing.

Course content

5 sections • 15 lectures • 2h 52m total length

  • Introduction6:48

    Azure Databricks unifies Apache Spark with a cloud platform to develop, deploy, and manage big data solutions, enabling data transformations, business intelligence, and machine learning workflows.

  • Azure Databricks Architecture11:53

    Explore Azure Databricks architecture by distinguishing the control plane and compute plane, then see how notebooks, clusters, and jobs run on compute using dbfs and data lake gen2.

  • In-memory computation and Map-Reduce in Hadoop4:55
  • Difference between Current Spark Environment and Databricks Serverless9:08

    Contrast the current spark environment with databricks serverless, highlighting auto scaling, usage-based pricing, optimized spark engine, multi-language support, notebooks, collaborative workspaces, and production-ready pipelines.

  • Databricks Community Edition Creation11:03

    Learn to set up the Databricks community edition, create clusters, and use the workspace, data, and compute tools for PySpark notebooks and basic data processing.

  • Driver Program, Worker Program and Cluster Manager12:24
  • Notebook Creation and Introduction5:46

    Create notebooks in Databricks with multi-language support for Python, SQL, Scala, and R. Configure per-cluster settings to match data volumes and run code in independent cells.

  • Markdown in Notebook2:14

    Switch to markdown in your notebook using the %md magic, then document data frame creation with bold text and headings for clear notes.

Requirements

  • No prerequisites

Description

Welcome to the comprehensive course, 'Mastering Azure Databricks and PySpark for Data Engineers.' This transformative learning experience is carefully curated for data engineers, offering an in-depth exploration of the dynamic duo – Azure Databricks and PySpark.

Course Highlights:

  1. Foundational Knowledge: Begin your journey by gaining a solid understanding of Azure Databricks. Navigate the platform effortlessly, grasp its architecture, and delve into the core features that make it a powerhouse for big data processing.

  2. PySpark Mastery: Uncover the versatility of PySpark, the Python API for Apache Spark. From essential concepts to advanced functionalities, this course equips you with the skills to leverage PySpark for distributed data processing and analysis.

  3. Real-world Application: Elevate your skills through real-time scenario analysis. Dive into practical examples and case studies that mirror industry challenges, ensuring you're well-prepared to apply your knowledge in professional settings.

  4. Live Project Development: Experience the thrill of building a live project from scratch. Walk through each phase of the project lifecycle, from data ingestion and cleaning to advanced analytics and visualization. By the end, you'll have a robust portfolio piece showcasing your proficiency in Azure Databricks and PySpark.

  5. Optimization Strategies: Unlock optimization techniques and best practices to enhance your projects. Learn how to troubleshoot common issues, implement efficient coding practices, and maximize the capabilities of Azure Databricks for seamless data processing.

Who Is This Course For?

This course caters to a diverse audience:

  • Data Professionals and Analysts: Enhance your skills in big data processing and analytics using Azure Databricks and PySpark.

  • Data Engineers and Developers: Build robust, scalable data processing solutions and gain expertise in leveraging PySpark for efficient distributed computing.

  • BI and Analytics Professionals: Leverage Azure Databricks and PySpark for advanced analytics, deriving meaningful insights, and enhancing decision-making processes.

  • Aspiring Data Scientists: Strengthen your foundation in distributed computing and gain practical experience handling real-world data scenarios using PySpark.

  • IT Professionals and Cloud Enthusiasts: Explore cloud-based big data solutions, acquiring hands-on experience with Azure Databricks and PySpark for efficient data processing and analysis.

Enroll Now:

Embark on a learning journey that will redefine your capabilities as a data engineer. Subscribe to 'Mastering Azure Databricks and PySpark for Data Engineers' and equip yourself with the tools and knowledge needed to tackle the challenges of today's data landscape. Transform your career – one module at a time!

Who this course is for:

  • Data Professionals and Analysts
  • Data Engineers and Developers
  • Business Intelligence and Analytics Professionals
  • Aspiring Data Scientists
  • IT Professionals and Cloud Enthusiasts

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