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Daniel Ciocîrlan

UPDATED FOR SPARK 3.0

In this course, we will learn how to write big data applications with Apache Spark 3 and Scala. You'll write 2000+ lines of Spark code yourself, with guidance, and you will become a rockstar.

This course is for Scala programmers who are getting started with Apache Spark and big data. The course is not for advanced Spark engineers.

Why Spark in Scala:

Read more

UPDATED FOR SPARK 3.0

In this course, we will learn how to write big data applications with Apache Spark 3 and Scala. You'll write 2000+ lines of Spark code yourself, with guidance, and you will become a rockstar.

This course is for Scala programmers who are getting started with Apache Spark and big data. The course is not for advanced Spark engineers.

Why Spark in Scala:

  • it's blazing fast for big data

  • its demand has exploded

  • it's a highly marketable skill

  • it's well maintained, with dozens of high-quality extensions

  • it's a foundation for a data scientist

I like to get to the point and get things done. This course 

  1. deconstructs all concepts into the critical pieces you need

  2. selects the most important ideas and separates them into what's simple but critical and what's powerful

  3. sequences ideas in a way that "clicks" and makes sense throughout the process of learning

  4. applies everything in live code

The end benefits are still much greater:

  • a completely new mental model around data processing

  • significantly more marketable resume

  • more enjoyable work - Spark is fun.

This course is for established programmers with experience with Scala and with functional programming at the level of the Rock the JVM Scala beginners course. I already assume a solid understanding of general programming fundamentals.

This course is NOT for you if

  • you've never written Scala code before

  • you don't have some essential parallel programming background (e.g. what's a process/a thread)

The course is comprehensive, but you'll always see me get straight to the point. So make sure you have a good level of focus and commitment to become a badass programmer.

I believe both theory and practice are important. That's why you'll get lectures with code examples, real life code demos and assignments, plus additional resources, instructions, exercises and solutions. At the end of the course, you'll have written thousands of lines of Spark.

I've seen that my students are most successful - and my best students work at Google-class companies - when they're guided, but not being told what to do. I have exercises waiting for you, where I offer my (opinionated) guidance but otherwise freedom to experiment and improve upon your code.

Definitely not least, my students are most successful when they have fun along the way.

So join me in this course and let's rock the JVM.

Enroll now

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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Develops a new mental model around data processing
Taught by Daniel Ciocîrlan who are recognized for their work in Apache
Teaches skills that are highly relevant to industry
Teaches skills that are a foundation for data scientists
Examines Apache Spark for big data
Requires learners to have some knowledge of parallel programming

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Reviews summary

Spark 3.0 & scala: essential big data skills

According to students, this course provides a comprehensive and practical foundation in Apache Spark 3.0 for Scala developers. Learners frequently praise the instructor's exceptional clarity and concise explanations of complex big data concepts, which are delivered at a fast but engaging pace. The course's strength lies in its extensive hands-on coding examples and challenging exercises, allowing students to gain deep practical skills. While updated for Spark 3.0, a few learners noted that the prerequisites might be more demanding than anticipated, requiring a very strong Scala and functional programming background to keep up.
Fast-paced content, suitable for experienced learners.
"The pace is fast, which I liked, but might be challenging for some."
"The course has good content, but it moves very quickly. I felt like I needed to pause frequently and rewatch sections."
"I found this course extremely difficult. The instructor rushes through concepts without enough explanation..."
Features updated material for Spark 3.0.
"A very solid course. The updated Spark 3.0 content is a huge plus."
"The Spark 3.0 update was crucial."
"I appreciated the depth on RDDs, DataFrames, and Datasets, and how he tackled common pitfalls."
Provides invaluable practical coding examples and exercises.
"The hands-on examples and practical exercises are invaluable."
"The practical coding sessions are very helpful."
"Plenty of hands-on coding examples."
"The assignments are challenging but rewarding."
Explains complex Spark concepts with exceptional clarity.
"Absolutely fantastic! Daniel is a brilliant instructor who explains complex Spark concepts with incredible clarity."
"The instructor makes complex topics understandable. I learned a ton about efficient Spark programming."
"Instructor explains everything clearly and concisely."
Requires very strong Scala and functional programming knowledge.
"It assumes a *very* strong Scala and functional programming background, even more so than stated."
"I struggled a bit with the exercises. Maybe not for 'getting started' but more for 'accelerating'..."
"Definitely for developers, not for complete beginners to programming or Scala."
"Recommended for those with strong FP Scala."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Spark 3.0 & Big Data Essentials with Scala | Rock the JVM with these activities:
Review Intro to Scala
Ensure a solid foundation in Scala before diving into Spark, refreshing memory on fundamental Scala concepts and syntax.
Browse courses on Scala
Show steps
  • Review materials from a previous Scala course or online tutorial.
  • Go through Scala documentation and tutorials.
  • Complete practice exercises to reinforce understanding.
Connect with Spark Experts
Seek guidance from experienced professionals to enhance learning, gain industry insights, and explore career opportunities in Spark.
Show steps
  • Attend industry events or meetups related to Spark.
  • Reach out to professionals on LinkedIn or other networking platforms.
  • Request informational interviews to learn from their experiences.
Coding Challenges for Spark Novices
Practice writing Spark code to solidify understanding of key Spark concepts and deepen coding skills, laying the groundwork for the course content.
Browse courses on Scala
Show steps
  • Enroll in a coding challenge platform that offers Scala or Spark-specific challenges.
  • Start solving beginner-level challenges to gain hands-on experience with Scala and Spark.
  • Review solutions and explanations to understand best practices and improve coding.
Three other activities
Expand to see all activities and additional details
Show all six activities
Follow Spark Tutorials
Supplement the course material with practical, hands-on tutorials to enhance understanding and apply Spark concepts in real-world scenarios.
Browse courses on Spark Programming
Show steps
  • Identify reputable online platforms offering Spark tutorials.
  • Select tutorials that align with the course syllabus.
  • Follow the tutorials step-by-step, implementing Spark code.
  • Review and troubleshoot any errors encountered.
Scala/Spark Study Group
Collaborate with peers to reinforce concepts, discuss challenges, and share insights, fostering a supportive and interactive learning environment.
Show steps
  • Form or join a study group with fellow Scala and Spark learners.
  • Meet regularly to discuss course material, work on projects, and troubleshoot issues.
  • Take turns presenting and facilitating discussions.
Spark: The Definitive Guide
Gain a comprehensive understanding of Apache Spark's architecture, core APIs, and advanced techniques, reinforcing concepts covered in the course.
Show steps
  • Read selected chapters relevant to the course content.
  • Take notes and highlight key concepts.
  • Complete exercises and examples provided in the book.

Career center

Learners who complete Spark 3.0 & Big Data Essentials with Scala | Rock the JVM will develop knowledge and skills that may be useful to these careers:
Product Manager
Product Managers use their knowledge of product development and marketing to develop and launch new products. They work closely with other product professionals to ensure that products meet the needs of users. This course may be useful for Product Managers who want to learn how to use Apache Spark and Scala to develop big data products.
Risk Analyst
Risk Analysts use their knowledge of risk management principles and practices to identify and assess risks. They use this information to help businesses develop strategies to mitigate risks. This course may be useful for Risk Analysts who want to learn how to use Apache Spark and Scala to develop big data models for risk analysis.
Actuary
Actuaries use their knowledge of mathematics and statistics to develop models that can predict financial outcomes. They use this information to help businesses make sound financial decisions. This course may be useful for Actuaries who want to learn how to use Apache Spark and Scala to develop big data models for actuarial analysis.
Financial Analyst
Financial Analysts use their knowledge of financial markets and instruments to develop investment strategies. They use this information to help businesses make better investment decisions. This course may be useful for Financial Analysts who want to learn how to use Apache Spark and Scala to develop big data models for financial analysis.
Business Analyst
Business Analysts use their knowledge of business processes and systems to develop solutions to business problems. They work closely with other business professionals to ensure that solutions meet the needs of the business. This course may be useful for Business Analysts who want to learn how to use Apache Spark and Scala to develop big data solutions for business problems.
Big Data Engineer
Big Data Engineers use their knowledge of big data technologies to design, develop, and maintain big data systems. They work closely with other IT professionals to ensure that big data systems meet the needs of users. This course may be useful for Big Data Engineers who want to learn how to use Apache Spark and Scala to develop big data applications.
Data Architect
Data Architects use their knowledge of data architecture principles to design and develop data systems. They work closely with other IT professionals to ensure that data systems meet the needs of users. This course may be useful for Data Architects who want to learn how to use Apache Spark and Scala to develop big data systems.
Cloud Architect
Cloud Architects use their knowledge of cloud computing technologies to design and develop cloud-based applications. They work closely with other IT professionals to ensure that cloud-based applications meet the needs of users. This course may be useful for Cloud Architects who want to learn how to use Apache Spark and Scala to develop big data applications in the cloud.
DevOps Engineer
DevOps Engineers use their knowledge of DevOps principles and practices to improve the collaboration between development and operations teams. They work closely with other IT professionals to ensure that software applications are delivered quickly and efficiently. This course may be useful for DevOps Engineers who want to learn how to use Apache Spark and Scala to develop and deploy big data applications.
Software Architect
Software Architects use their knowledge of software architecture principles and practices to design and develop software systems. They work closely with other IT professionals to ensure that software systems meet the needs of users. This course may be useful for Software Architects who want to learn how to use Apache Spark and Scala to develop big data systems.
Quantitative Analyst
Quantitative Analysts use their knowledge of mathematics and statistics to develop models that can predict financial outcomes. They use this information to help businesses make better investment decisions. This course may be useful for Quantitative Analysts who want to learn how to use Apache Spark and Scala to develop big data models for financial analysis.
Data Analyst
Data Analysts use their knowledge of data analysis techniques to identify trends and patterns in data. They use this information to make recommendations to businesses about how to improve their operations. This course may be useful for Data Analysts who want to learn how to use Apache Spark and Scala to analyze big data.
Data Scientist
Data Scientists use their knowledge of data science techniques to develop models that can predict future outcomes. They use this information to help businesses make better decisions. This course may be useful for Data Scientists who want to learn how to use Apache Spark and Scala to develop big data models.
Machine Learning Engineer
Machine Learning Engineers use their knowledge of machine learning techniques to develop models that can learn from data. They use this information to help businesses automate tasks and improve their operations. This course may be useful for Machine Learning Engineers who want to learn how to use Apache Spark and Scala to develop big data machine learning models.
Software Developer
Software Developers use their knowledge of programming languages to design, develop, and test software applications. They work closely with other IT professionals to ensure that software applications meet the needs of users. This course may be useful for Software Developers who want to learn how to use Apache Spark and Scala to develop big data applications.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Spark 3.0 & Big Data Essentials with Scala | Rock the JVM.
Is the official guide to Apache Spark. It provides a comprehensive overview of Spark's architecture, programming model, and features.
Comprehensive guide to Apache Spark, providing a solid foundation for understanding the fundamentals of big data processing with Spark. It covers key concepts, including Spark's architecture, programming model, and optimization techniques.
Provides a comprehensive guide to advanced analytics with Spark. It covers a wide range of topics, from machine learning to graph analytics.
Provides a deep dive into the internals of Apache Spark. It covers topics such as memory management, task scheduling, and performance tuning.
Provides a hands-on introduction to machine learning with Spark. It covers a wide range of topics, from data preparation to model evaluation.
Provides a comprehensive overview of big data principles and best practices. It covers a wide range of topics, from data storage and processing to real-time analytics.
Provides a comprehensive introduction to functional programming in Scala. It covers the fundamentals of functional programming, as well as more advanced topics such as monads and type classes.
Collection of recipes that provide solutions to common problems encountered when working with Scala. It covers a wide range of topics, from basic syntax to advanced concurrency.

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