Hey there, data enthusiast! You know as well as I do that the world of data processing is vast, exciting, and constantly evolving. That’s why it’s so important to stay up-to-date with the latest tools and technologies, like Apache Beam. This open-source, unified programming model makes it easy to process and manage data streams, regardless of their size or complexity—no wonder it’s become a go-to resource for countless developers and data engineers. But if you’re feeling a little overwhelmed by all the Beam-related knowledge out there, don’t worry: I’ve got you covered. In this post, we’ll dive into some of the best Apache Beam online courses that will get you up and running in no time.
We all learn differently, so I’ve gone ahead and handpicked a varied selection of courses that are sure to cater to your unique learning style. These courses cover everything from the very basics to more advanced topics, ensuring you mop up all the Apache Beam know-how you need for your next big data project. Plus, we’ll highlight the key features, teaching methods, and overall experience each course promises, so you can make an educated decision about which one is the perfect fit for you. Ready to upgrade your data processing skills? Let’s get started!
Apache Beam Courses – Table of Contents
- Apache Beam | A Hands-On course to build Big data Pipelines
- Apache Beam | Google Data Flow (Python)
- Data Engineering with Google Dataflow and Apache Beam on GCP
- Learn Practical Apache Beam in Java | BigData framework
- Batch Processing with Apache Beam in Python
- Data Engineering Essentials using SQL, Python, and PySpark
- Apache Airflow: The Hands-On Guide
- ApachE Beam Is Easy: A Course For Beginners
Apache Beam | A Hands-On course to build Big data Pipelines
Platform:
Udemy
Rating:
4.5 out of 5
Apache Beam is quickly becoming the future of building big data processing pipelines due to its portability and language-agnostic nature. With Apache Beam’s portable programming model, you can now build pipelines that can run across various big data platforms, such as Apache Spark, Flink and Google Cloud Platform’s Cloud Dataflow.
This comprehensive online course covers complete Apache Beam concepts from scratch to real-time implementation. You’ll learn through hands-on examples and get explanations for concepts that can be hard to find online, such as type hints, encoding and decoding, watermarks, windows, and triggers. Additionally, you’ll build two real-time big data case studies using the Apache Beam programming model and learn how to load processed data to Google Cloud BigQuery tables from a Beam pipeline. Codes and datasets used in the lectures are provided, making it easy for you to follow along and master the skills.
Skills you’ll learn in this course:
- Master Apache Beam concepts from scratch to real-time implementation
- Gain hands-on experience with various Apache Beam tools and techniques
- Understand Type Hints, Encoding & Decoding, Watermarks, Windows, and Triggers
- Build and deploy 2 real-time big data case studies using Apache Beam programming model
- Load processed data into Google Cloud BigQuery tables from Beam pipelines
- Develop language-agnostic big data pipelines compatible with multiple big data engines
- Stay updated with the latest trends and best practices in big data processing
- Access and utilize provided course codes and datasets for practice and implementation
Apache Beam | Google Data Flow (Python)
Platform:
Udemy
Rating:
4.4 out of 5
Are you a beginner looking to dive into the world of big data technology? This online course on Apache Beam using Python language might be just what you need! In just 3 hours, you’ll learn about Google Cloud Dataflow and how to build big data pipelines using Google Cloud. What makes this course stand out is its concise yet comprehensive coverage of relevant topics, ensuring that you’ll be ready to use Apache Beam in a real work environment by the end of the course.
In this hands-on course, you’ll be introduced to various topics such as architecture, transformations, side inputs/outputs, streaming with Google PubSub, windows in streaming, handling late elements, using triggers, Google Cloud Dataflow, and Beam SQL on GCP. Apache Beam is considered the future of big data because it runs on top of popular engines like Spark and Flink, is used by big giants like Google, and solves the industry’s biggest problem of migration and unification from one processing engine to another. So if you want to learn the future technology and boost your big data career, this course is the right place to start!
Skills you’ll learn in this course:
- Understanding Apache Beam architecture
- Learning data transformations
- Implementing side inputs/outputs
- Integrating streaming with Google PubSub
- Utilizing windows in streaming
- Managing late elements
- Applying triggers
- Leveraging Google Cloud Dataflow and Beam SQL
Data Engineering with Google Dataflow and Apache Beam on GCP
Platform:
Udemy
Rating:
4.5 out of 5
Dive into the world of data pipeline development with this dynamic course on Apache Foundation’s newest framework: Apache Beam, and its growing popularity in partnership with Google Dataflow. The course is designed to cover essential topics such as understanding the inner workings of Apache Beam, the benefits it offers, how to use it on Google Colab without installation, exploring its main functions, configuring the Apache Beam Python SDK locally, and deploying a Batch pipeline on Google Dataflow. Keep in mind, this course assumes you have a basic understanding of Python and is constantly being updated for the best learning experience.
Before starting, make sure you’re comfortable with Python basics, such as defining functions, creating objects, and working with data types. If you’re interested in the fourth section—deploying a pipeline on Google Dataflow—it’s important to have a free GCP account (requiring a credit card). The course is structured into three main sections: Section 2 – Concepts, Section 3 – Main Functions, and Section 4 – Apache Beam on Google Dataflow. So, get ready to embark on a journey packed with valuable knowledge at an affordable price, and don’t forget to leave a nice rating at the end!
Skills you’ll learn in this course:
- Understanding the inner workings of Apache Beam
- Recognizing the benefits of using Apache Beam
- Utilizing Google Colab for development without local installation
- Exploring Apache Beam’s main functions
- Configuring Apache Beam Python SDK locally
- Deploying Apache Beam resources on Google Dataflow for batch pipelines
- Navigating Google Cloud Platform (GCP) free account set-up process
- Implementing Apache Beam within Google Dataflow operations
Learn Practical Apache Beam in Java | BigData framework
Platform:
Udemy
Rating:
4.2 out of 5
Looking to dive into the world of Apache Beam using Java? This course has got you covered! Designed for both beginners and professionals, it focuses on hands-on, practical examples to help you master Apache Beam from scratch. Get ready to learn, grow, and excel in Java-backed Apache Beam development.
In this tutorial, you’ll be taken on an exciting journey through lab sections for AWS and Google Cloud Platform, Kafka, MySQL, Parquet File, BigQuery, S3 Bucket, Streaming ETL, Batch ETL, and Transformation. By the end of this course, you’ll have all the knowledge and skills you need to tackle Apache Beam projects with confidence. Whether you’re a seasoned pro looking to sharpen your skills or a novice eager to get started, this course has something for everyone.
Skills you’ll learn in this course:
- Mastering Apache Beam fundamentals using Java
- Gaining hands-on experience with AWS and Google Cloud Platform
- Working with data streams using Kafka
- Implementing database management with MySQL
- Handling Parquet files and BigQuery
- Utilizing Amazon S3 Buckets
- Developing Streaming ETL pipelines
- Designing and executing Batch ETL transformations
Batch Processing with Apache Beam in Python
Platform:
Udemy
Rating:
3.3 out of 5
Are you ready to dive into the world of Apache Beam and learn how to build large-scale data processing pipelines? This course has got you covered! By the end, you’ll be able to create your own custom batch data processing pipeline with Apache Beam. Talk about impressive, right?
The course offers 20 bite-sized lectures, complete with full coding screencasts and a real-life coding project to add to your GitHub portfolio. Get ready to follow along with the instructor and learn everything from installing Apache Beam on your machine to deploying your pipeline on Cloud Dataflow. Don’t worry if you’re new to all this – the course is suitable for all levels, and no prior knowledge of Apache Beam or Cloud Dataflow is required. So, gear up and embark on this journey to master Apache Beam like a pro!
Skills you’ll learn in this course:
- Installing Apache Beam on your machine
- Understanding basic and advanced Apache Beam concepts
- Developing a real-world batch processing pipeline
- Defining custom transformation steps
- Deploying your pipeline on Cloud Dataflow
- Building your own custom data processing pipeline in Apache Beam
- Following lectures with full coding screencasts
- Adding a real-life coding project to your Github portfolio
Data Engineering Essentials using SQL, Python, and PySpark
Platform:
Udemy
Rating:
4.4 out of 5
If you’re on the hunt for a comprehensive data engineering course, look no further! This course covers essential data engineering skills, teaching you how to build data pipelines using SQL, Python, Hadoop, Hive, Spark SQL, and PySpark Data Frame APIs. You’ll develop and deploy Python applications using Docker, manage PySpark on multinode clusters, and gain basic know-how on reviewing Spark Jobs using Spark UI. The course also addresses key challenges that learners often face, ensuring that you have a suitable environment, quality content, and adequate exercises to practice.
The course is designed for professionals at all levels and covers a wide range of topics, such as setting up your environment and necessary tables, writing basic and advanced SQL queries with practical examples, performance tuning of queries, Python programming basics, data processing using Pandas, troubleshooting and debugging scenarios, and so much more. You’ll even have the opportunity to work on real-time Python projects! With its emphasis on hands-on learning and in-depth coverage of essential data engineering skills, this course will undoubtedly set you on the path to mastering the art of data processing and pipeline development.
Skills you’ll learn in this course:
- Master data engineering essentials using SQL, Python, and PySpark Data Frame APIs.
- Develop and deploy Python applications using Docker & PySpark on multinode clusters.
- Build various data pipelines, including batch and streaming pipelines.
- Troubleshoot and debug database-related issues and performance tuning of SQL queries.
- Gain proficiency in programming using Python as a language and Python collections for data engineering.
- Work on real-time Python projects and learn data processing using Pandas.
- Set up and work with Google Cloud Platform and Databricks for Spark environment and write basic Spark SQL queries.
- Gain an in-depth understanding of Apache Spark Catalyst Optimizer, Explain Plans, and performance tuning using Partitioning.
Apache Airflow: The Hands-On Guide
Platform:
Udemy
Rating:
4.5 out of 5
Apache Airflow has become a must-have skill for anyone working with data due to its scalability, dynamic nature, extensibility, and modularity. In this course, you’ll learn the fundamentals, such as how the scheduler and web server work, and dive into the Forex Data Pipeline project as a fantastic way to discover many operators in Airflow. You’ll also get to work with tools like Slack, Spark, and Hadoop.
Mastering your Directed Acyclic Graphs (DAGs) is a top priority, and this course covers handling time zones, unit testing your DAGs, structuring your DAG folder, and more. You’ll also explore scaling Airflow through different executors, like the Local, Celery, and Kubernetes Executors. Advanced concepts will be shown through practical examples and exercises, covering security, monitoring your Airflow with Elasticsearch and Grafana, setting up Kubernetes clusters with AWS EKS and Rancher, and addressing security needs for your Airflow instance. With a mix of quizzes and practical exercises, this course will leave you more confident than ever in using Airflow.
Skills you’ll learn in this course:
- Master the fundamentals of Airflow, including its architecture and components.
- Gain hands-on experience with a variety of Airflow operators through the Forex Data Pipeline project.
- Effectively manage and optimize your DAGs, including timezone handling and unit testing.
- Scale Airflow with different executors such as Local, Celery, and Kubernetes.
- Set up and manage Airflow within a Kubernetes cluster, both locally and in the cloud using AWS EKS and Rancher.
- Implement advanced concepts like DAG templating, dependencies, and deadlock prevention.
- Monitor Airflow with tools like Elasticsearch and Grafana.
- Ensure the security of your instance by managing user roles, permissions, and data encryption.
ApachE Beam Is Easy: A Course For Beginners
Platform:
Udemy
Rating:
0 out of 5
Are you eager to dive into Apache Beam and expand your knowledge on the subject? Look no further, because this course is just what you need to get started! Remember, the key to truly mastering Apache Beam is dedicating your time and effort into learning and understanding its various aspects. With this course, you’ll have a great resource at your disposal to help guide you through the world of Apache Beam.
Apache Beam is an incredibly valuable tool for those interested in technology, offering knowledge in coding, informatics, and programming. This course aims to provide you with the essential information and tips to make your learning experience as smooth as possible. Your motivation and dedication to study will ultimately pave the way to success in the realm of Apache Beam. There’s no time like the present, so take this opportunity to embark on your journey and make your first step count! See you on the course!
Skills you’ll learn in this course:
- Gain knowledge about Apache Beam
- Improve coding skills
- Enhance informatics knowledge
- Develop programming abilities
- Master Apache Beam tools
- Learn to study effectively
- Stay motivated during your learning journey
- Embark on a successful Apache Beam career
In conclusion, investing your time and effort into learning Apache Beam through online courses doesn’t just benefit your current professional development. It also opens the door to new job opportunities in the ever-expanding big data processing and analytics field. Learning at your own pace with support from industry experts and a community of fellow learners ultimately provides an excellent foundation for mastering this powerful and versatile tool.
Don’t hesitate to take the plunge and enroll in Apache Beam online courses that best suit your learning style and goals. By doing so, you’ll soon empower yourself to tackle increasingly complex big data challenges, ensuring that your career trajectory remains on an upward path. Happy learning!