Apache Spark with Scala - Learn Spark from a Big Data Guru

Learn Apache Spark and Scala by 12+ hands-on examples of analyzing big data

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What this Apache Spark course is about

What is this course about:

This course covers all the fundamentals about Apache Spark with Scala and teaches you everything you need to know about developing Apache Spark applications with Scala Spark. At the end of this course, you will gain in-depth knowledge about Apache Spark Scala and general big data analysis and manipulations skills to help your company to adapt Apache Scala Spark for building big data processing pipeline and data analytics applications.

This course covers 10+ hands-on big data examples involving Apache Spark. You will learn valuable knowledge about how to frame data analysis problems as Scala Spark problems. Together we will learn examples such as aggregating NASA Apache web logs from different sources; we will explore the price trend by looking at the real estate data in California; we will write

Scala Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker spaces are distributed across different regions in the United Kingdom. And much much more.

Why shall we learn Apache Spark:

Apache Spark gives us unlimited ability to build cutting-edge applications. It is also one of the most compelling technologies of the last decade in terms of its disruption to the big data world.

Apache Scala Spark provides in-memory cluster computing which greatly boosts the speed of iterative algorithms and interactive data mining tasks.

Apache Spark is the next-generation processing engine for big data.

Tons of companies are adapting Apache Spark to extract meaning from massive data sets, today you have access to that same big data technology right on your desktop.

Apache Spark is becoming a must tool for big data engineers and data scientists.

Master Apache Spark with Scala

What you will learn from this course:

  • An overview of the architecture of Apache Spark.
  • RDD transformations and actions
  • Spark SQL
  • Develop Apache Spark 2.0 applications with Scala
  • Advanced techniques to optimize and tune Apache Spark jobs
  • Spark on Amazon's Elastic MapReduce service
  • Big data ecosystem overview
  • Datasets and DataFrames
  • Analyze structured and semi-structured data
  • broadcast variables and accumulators
  • Best practices of working with Apache Spark in the field.
  • Big data ecosystem overview.

Bite Sized, Referenceable and Easy To Digest Videos with No Fluff

By the end of watching this course, you'll feel confident to build Apache Spark applications with Scala, RDD and Spark SQL.

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What programming language is this course taught in?

This course is taught in Scala. Scala is the next generation programming language for functional programing that is growing in popularity and it is one of the most widely used languages in the industry to write Apache Spark programs.

Let's learn how to write Apache Spark programs with Scala to model big data problem today!

30-day Money-back Guarantee!

You will get 30-day money-back guarantee from Udemy for this course.

If not satisfied simply ask for a refund within 30 days. You will get a full refund. No questions whatsoever asked.

Are you ready to take your big data analysis skills and career to the next level, take this course now!

You will go from zero to Spark hero in 4 hours.

Get started now!

Your Instructor

James Lee
James Lee
James Lee is a passionate software wizard working at one of the top Silicon Valley-based startups specializing in big data analysis.
In the past, he has worked on top-tier IT companies companies such as Google and Amazon
In his day job, he works with big data technologies such as Apache Spark and ElasticSearch, and he is an absolute Docker technology geek and IntelliJ IDEA lover with strong focus on efficiency and simplicity.
James Lee has a MS degree in Computer Science from McGill University and many years of experience as a teaching assistant for various computer science classes.

Course Curriculum

  Spark Architecture and Components
Available in days
days after you enroll
  Additional Learning Materials
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days after you enroll

30-Day Money-Back Guarantee

Try it risk-free

You can ask for a refund any time during the first 30 days
if you decide the course isn’t for you.

Frequently Asked Questions

When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

Students of Level Up Academy Worked at

"muy buen curso, bien explicado con lo esencial para tirar adelante.

very good course, well explained with the essentials to pull forward."

- Paul Van Branteghem, Senior Data Scientist at Deloitte Digital

"Very useful step-by-step for learning thank you, so fantastic for me as newbie jump into"

- Pong Tredees

"I really enjoyed this course. The instructors are very fast answering the questions and the lectures are concise and direct to the point."

- Jesús Rodríguez Pérez, Web application developer at Carrefour

Are you ready to become
an Apache Spark rockstar?

Stop wasting your time jumping from one tutorial to another. Enroll in the course to get:

    4 hours of HD videos

    Exercises and solutions

    Real-world projects

    Little known expert tips

    Best practices to apply

    Common mistakes to avoid

    Unlimited access

    Learn at your own pace

    Watch online or offline

    Watch on any devices

    Downloadable source code

    Certificate of completion

With a 30-day full money-back guarantee, what do you have to lose?

Get started now!