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    Databricks Courses Online

    Explore Databricks for big data processing and analytics. Learn to use Apache Spark and Databricks for scalable data analysis and machine learning.

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    Explore the Databricks Course Catalog

    • W

      Whizlabs

      Data Governance with Databricks

      Skills you'll gain: Data Governance, Extract, Transform, Load, Metadata Management, Role-Based Access Control (RBAC), Data Cleansing, Databricks, Data Management, Data Pipelines, Amazon Web Services, Data Lakes, Data Migration, Data Architecture, Data Security, Personally Identifiable Information, Data Warehousing, Data Quality, General Data Protection Regulation (GDPR), Data Capture

      3.5
      Rating, 3.5 out of 5 stars
      ·
      8 reviews

      Intermediate · Course · 1 - 4 Weeks

    • B

      Board Infinity

      Data Governance with Databricks

      Skills you'll gain: Data Governance, Databricks, Data Management, Data Architecture, Metadata Management, Information Management, Data Strategy, Data Security, Data Quality

      2.7
      Rating, 2.7 out of 5 stars
      ·
      28 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      W

      Whizlabs

      Getting Started with Microsoft Fabric

      Skills you'll gain: Power BI, Data Analysis Expressions (DAX), Data Pipelines, Data Analysis, Data Transformation, Microsoft Azure, Analytics, Data Warehousing, Data Integration, Data Processing, Data Cleansing, Data Modeling, Dashboard, Data Governance

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      P

      Packt

      Advanced Data Management in Azure Databricks

      Skills you'll gain: Databricks, Real Time Data, Data Governance, Data Lakes, Microsoft Azure, Data Architecture, Data Management, Data Pipelines, Apache Spark, Data Quality, Data Integrity

      Advanced · Course · 1 - 4 Weeks

    • Status: New
      New
      F

      Fractal Analytics

      Data Frameworks for Generative AI

      Skills you'll gain: Taxonomy, Data Governance, Generative AI, Data Strategy, Data Quality, Data Architecture, Data Management, Data Infrastructure, Data Access, Large Language Modeling, Prompt Engineering, Information Architecture, Unstructured Data, Data Security, Agentic systems

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      P

      Packt

      Automation and Project Implementation in Azure Databricks

      Skills you'll gain: CI/CD, Databricks, Microsoft Azure, Data Architecture, Cloud Engineering, Secure Coding, Data Storage Technologies, Integration Testing, Automation, Restful API, Command-Line Interface, Systems Design, Software Design, Data Pipelines, GitHub

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      W

      Whizlabs

      Exam Prep DP-100: Microsoft Azure Data Scientist Associate

      Skills you'll gain: Statistical Modeling, MLOps (Machine Learning Operations), Microsoft Azure, Azure Synapse Analytics, Apache Spark, Prompt Engineering, Data Management, Data Science, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Statistics, Cloud Computing, Application Deployment, Data Pipelines, Large Language Modeling, Continuous Monitoring, Data Processing, Generative AI, Data Ethics

      Intermediate · Specialization · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      W

      Whizlabs

      Azure ML: Explore & Configure the Machine Learning Workspace

      Skills you'll gain: Statistical Modeling, Microsoft Azure, Data Science, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Statistics, MLOps (Machine Learning Operations), Azure Synapse Analytics, Cloud Computing, Data Management, Virtual Machines

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Azure Data Fundamentals DP-900 Exam Prep

      Skills you'll gain: Azure Synapse Analytics, Microsoft Azure, Power BI, Databricks, Data Processing, Cloud Services, Data Warehousing, Database Systems, Databases, Dashboard, Data Architecture, NoSQL, Apache Spark, Database Administration, Relational Databases, MySQL, Data Store, SQL, Cloud Storage, Database Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      829 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      ETL and Data Pipelines with Shell, Airflow and Kafka

      Skills you'll gain: Extract, Transform, Load, Apache Airflow, Data Pipelines, Apache Kafka, Data Warehousing, Data Transformation, Data Migration, Web Scraping, Data Integration, Shell Script, Data Processing, Real Time Data, Data Cleansing, Big Data, Performance Tuning, Scalability

      4.5
      Rating, 4.5 out of 5 stars
      ·
      412 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Applied Python Data Engineering

      Skills you'll gain: Data Visualization Software, PySpark, Data Visualization, Snowflake Schema, Data Storytelling, Site Reliability Engineering, Docker (Software), Databricks, Containerization, Interactive Data Visualization, Plotly, Data Pipelines, Kubernetes, Matplotlib, Apache Spark, Dashboard, Virtualization, MLOps (Machine Learning Operations), Devops Tools, Apache Hadoop

      3.8
      Rating, 3.8 out of 5 stars
      ·
      95 reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Engineering Foundations

      Skills you'll gain: Web Scraping, Database Design, SQL, MySQL, Data Transformation, Data Store, Extract, Transform, Load, IBM DB2, Relational Databases, Data Architecture, Jupyter, Data Pipelines, Big Data, Data Warehousing, Data Governance, Data Manipulation, Stored Procedure, Databases, Automation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      56K reviews

      Beginner · Specialization · 3 - 6 Months

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    1234…9

    In summary, here are 10 of our most popular databricks courses

    • Data Governance with Databricks: Whizlabs
    • Data Governance with Databricks: Board Infinity
    • Getting Started with Microsoft Fabric: Whizlabs
    • Advanced Data Management in Azure Databricks: Packt
    • Data Frameworks for Generative AI: Fractal Analytics
    • Automation and Project Implementation in Azure Databricks: Packt
    • Exam Prep DP-100: Microsoft Azure Data Scientist Associate: Whizlabs
    • Azure ML: Explore & Configure the Machine Learning Workspace: Whizlabs
    • Microsoft Azure Data Fundamentals DP-900 Exam Prep: Microsoft
    • ETL and Data Pipelines with Shell, Airflow and Kafka: IBM

    Frequently Asked Questions about Databricks

    Databricks is a unified analytics platform that is designed for big data and machine learning. It provides an interactive workspace where users can collaborate, analyze data, build and deploy machine learning models, and create reports and dashboards. Databricks is known for its powerful Apache Spark engine, which enables processing and analyzing large datasets quickly and efficiently. It also offers a rich set of tools and libraries that make it easier for users to work with big data and perform advanced analytics tasks.‎

    To effectively work with Databricks, it is recommended to acquire the following skills:

    1. Apache Spark: Databricks is built on Apache Spark, a popular big data processing framework. Understanding the concepts, architecture, and usage of Apache Spark will help you leverage the full potential of Databricks.

    2. SQL: Having a strong foundation in SQL (Structured Query Language) is essential when working with Databricks. SQL is used for querying and manipulating data in Databricks, so understanding SQL syntax and advanced SQL operations will be beneficial.

    3. Python or Scala: Databricks supports multiple programming languages, but Python and Scala are commonly used. Familiarity with either Python or Scala will be beneficial for scripting, data analysis, and developing custom code in Databricks.

    4. Data manipulation and analysis: Having skills in data manipulation, cleansing, and analysis is crucial for working with Databricks. This includes understanding data structures, data transformation techniques, and statistical analysis.

    5. Machine Learning: Databricks provides built-in support for machine learning frameworks like TensorFlow, PyTorch, and Scikit-Learn. Knowledge of machine learning concepts, algorithms, and model training will enable you to leverage the machine learning capabilities of Databricks effectively.

    6. Cloud platforms: Databricks is often deployed on cloud platforms like AWS, Azure, or Google Cloud. Familiarity with the cloud platform on which Databricks is used will be advantageous for managing resources, accessing data, and setting up the infrastructure.

    By developing these skills, you will be well-equipped to work with Databricks and harness its potential for data processing, analytics, and machine learning.‎

    With Databricks skills, you can pursue various job opportunities in the field of data analysis and data engineering. Some potential job roles you can obtain include:

    1. Data Engineer: As a data engineer with Databricks skills, you can design, develop, and maintain data pipelines and infrastructure needed to process and analyze vast amounts of data.

    2. Data Analyst: With Databricks skills, you can leverage the platform to analyze and interpret complex datasets in order to uncover insights and make data-driven decisions for organizations.

    3. Data Scientist: Databricks skills can be advantageous for data scientists, allowing them to perform advanced analytics and machine learning tasks on big data using the platform's collaborative and scalable environment.

    4. Big Data Engineer: Companies dealing with large-scale data often seek professionals skilled in Databricks to build and maintain big data processing systems, utilizing Apache Spark and other tools supported by Databricks.

    5. Business Intelligence Developer: Databricks skills can also be valuable for business intelligence developers, enabling them to create interactive dashboards, visualizations, and reports by leveraging the platform's data processing capabilities and integrations.

    6. Cloud Solutions Architect: As a cloud solutions architect with Databricks expertise, you can design and implement scalable and efficient cloud-based data solutions using Databricks in conjunction with cloud platforms like AWS, Azure, or Google Cloud.

    These are just a few examples of the job possibilities with Databricks skills. The demand for professionals with Databricks expertise is continuously growing as organizations recognize the importance of effectively managing and extracting insights from their data.‎

    People who are interested in data analytics, data engineering, or machine learning would be best suited for studying Databricks. Additionally, individuals with a background in programming and a strong understanding of data manipulation and analysis would find Databricks beneficial.‎

    There are several topics related to Databricks that you can study. Here are a few options:

    1. Big Data Analysis: Learn how to work with large datasets efficiently using Databricks' unified analytics platform.

    2. Apache Spark: Dive deep into Apache Spark, the open-source big data processing framework that powers Databricks, and understand its architecture, components, and advanced features.

    3. Data Engineering: Master the skills needed to design, build, and maintain data pipelines using Databricks to handle various data sources, transformations, and integrations.

    4. Machine Learning with PySpark: Explore how to leverage Databricks and PySpark libraries to implement machine learning algorithms for tasks such as classification, regression, clustering, and recommendation systems.

    5. Data Visualization with Databricks: Learn how to create interactive and insightful visualizations using Databricks' collaborative environment, enabling you to gain valuable insights from your data.

    6. Cloud Computing: Understand how Databricks utilizes cloud computing technologies like AWS, Azure, or GCP to provide scalable and performant data processing and analytics solutions.

    7. Data Science with Databricks: Develop skills in data exploration, feature engineering, model training, and evaluation using Databricks' collaborative environment along with popular data science libraries like Pandas, NumPy, and scikit-learn.

    These topics cover a range of skills and knowledge related to Databricks, allowing you to improve your proficiency in big data analytics, data engineering, machine learning, and cloud-based data solutions.‎

    Online Databricks courses offer a convenient and flexible way to enhance your knowledge or learn new Databricks is a unified analytics platform that is designed for big data and machine learning. It provides an interactive workspace where users can collaborate, analyze data, build and deploy machine learning models, and create reports and dashboards. Databricks is known for its powerful Apache Spark engine, which enables processing and analyzing large datasets quickly and efficiently. It also offers a rich set of tools and libraries that make it easier for users to work with big data and perform advanced analytics tasks. skills. Choose from a wide range of Databricks courses offered by top universities and industry leaders tailored to various skill levels.‎

    Choosing the best Databricks course depends on your employees' needs and skill levels. Leverage our Skills Dashboard to understand skill gaps and determine the most suitable course for upskilling your workforce effectively. Learn more about Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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