Apache Spark with Python - Big Data with PySpark and Spark
Learn Apache Spark and Python by 12+ hands-on examples of analyzing big data with PySpark
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What is this course about:
This course covers all the fundamentals about Apache Spark with Java and teaches you everything you need to know about developing Spark applications with Java. At the end of this course, you will gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adapt Apache Spark for building big data processing pipeline and data analytics applications.
This course covers 10+ hands-on big data examples. You will learn valuable knowledge about how to frame data analysis problems as 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 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.
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 Python
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 PySpark
- 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 PySpark, RDD and Spark SQL.
What is the target audience?
- Anyone who want to fully understand how Apache Spark technology works and learn how Apache Spark is being used in the field.
- Software engineers who want to develop Apache Spark 2.0 applications using Spark Core and Spark SQL.
- Data scientists or data engineers who want to advance their career by improving their big data processing skills.
What programming language is this course taught in?
This course is taught in Python. Python is currently one of the most popular programming languages in the world! It's rich data community, offering vast amounts of toolkits and features makes it a powerful tool for data processing. Using PySpark (the Python API for Spark) you will be able to interact with Apache Spark's main abstraction, RDDs, as well as other Spark components, such as Spark SQL and much more!
Let's learn how to write Spark programs with PySpark to model big data problems today!
Get started now!
Your Instructor
Course Curriculum
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PreviewRDD Basics (2:50)
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PreviewCreate RDDs (2:32)
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StartSpark Data Sources
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StartMap and Filter Transformation (9:29)
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StartSolution to Airports by Latitude Problem (1:57)
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StartFlatMap Transformation (3:46)
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StartSet Operations (8:26)
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StartSampling with Replacement and Sampling without Replacement
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StartSolution for the Same Hosts Problem (1:54)
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StartActions (9:03)
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StartSolution to Sum of Numbers Problem (2:06)
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StartImportant Aspects about RDD (1:40)
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StartSummary of RDD Operations (2:26)
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StartCaching and Persistance (5:16)
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
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
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?
Instructors of Level Up Academy
JAMES LEE
Co-founder and Instructor
James Lee is a passionate software wizard working at one of the top Silicon Valley-based start-ups specializing in big data analysis. In the past, he has worked on big companies such as Google and Amazon
- James Lee
TAO WE
Co-founder and Instructor
Tao is a passionate software engineer who works in a leading big data analysis company in Silicon Valley. Previously Tao has worked in big IT companies such as IBM and Cisco.
JIARUI ZHOU
Teaching Assistant
Jiarui Zhou is a 17-year-old student passionate about Computer Science and Engineering. Proficient in Python and other languages like Java, he combines youthful enthusiasm with technical expertise, applying his skills in real-world scenarios.
Why choosing this course?
This course is very hands-on, James has put lots effort to provide you with not only the theory but also real-life examples of developing Spark applications that you can try out on your own laptop.
James has uploaded all the source code to Github and you will be able to follow along with either Windows, MAC OS or Linux.
In the end of this course, James is confident that you will gain in-depth knowledge about Spark and general big data analysis and data manipulation skills. You'll be able to develop Spark application that analyzes Gigabytes scale of data both on your laptop, and in the cloud using Amazon's Elastic MapReduce service!
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.
Students of Level Up Academy Worked at
"It's an excellent course for people trying to get an overall grasp of PySpark. It covers each and every aspect of it with examples and exercises which makes it engaging as well. The last lecture where the instructor connects to Amazon EC2 is simply amazing!"
- Akshay Kher, senior analyst at dunnhumby
"Good explanation with good simple real sample, especially for student who learn spark python first time"
- Muhammad Subair, student of "Learn Kubernetes from a DevOps guru" and "Apache Spark with Python - Big Data with PySpark and Spark" course
"Curso bem completo para quem está iniciando no assunto e com vários exemplos práticos que vão direto ao ponto."
"Very complete course for those who are starting on the subject and with several practical examples that go straight to the point."
- Douglas Leite, data engineer
"Very good. I like the fact that evrything is explained clearly. this course covers a lot of practical knowledge on PySpark. Its a really good course for a beginner in PySpark. The lectures are short and as the course progressed it took me some time to clearly understand the concepts. The instructor is very knowledgeable and quick to respond to your queries. If you are looking for a course to start learning PySpark then I definitely recommend that you enroll for this course."
- Amy Wininger, software developer at Royal Bank Canada
30-Day Money-Back Guarantee
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You can ask for a refund any time during the first 30 days
if you decide the course isn’t for you.
