PySpark for Data Engineers and Data Analysts in 1h30
- Development
- Jan 22, 2025

PySpark for Data Engineers and Data Analysts in 1h30, available at $54.99, has an average rating of 3, with 20 lectures, based on 2 reviews, and has 3 subscribers.
You will learn about Gain solid PySpark skills with no prerequisites Avoid beginner pitfalls and master best practices Pass PySpark exams, certifications and technical tests Receive a training certificate at the end of the course Have the necessary PySpark skills to compete for job opportunities Gain a solid understanding of key PySpark concepts Realize professional projects with PySpark Work as a freelance with PySpark. Acquire the skills needed to work with companies that use PySpark Master the essential concepts in PySpark to become a Data Engineer, Data Scientist or Data Analyst This course is ideal for individuals who are People with little or no programming experience who want to learn PySpark or People who want to develop expertise with PySpark or People who want to apply for jobs or freelance positions that require PySpark skills It is particularly useful for People with little or no programming experience who want to learn PySpark or People who want to develop expertise with PySpark or People who want to apply for jobs or freelance positions that require PySpark skills.
Enroll now: PySpark for Data Engineers and Data Analysts in 1h30
Summary
Title: PySpark for Data Engineers and Data Analysts in 1h30
Price: $54.99
Average Rating: 3
Number of Lectures: 20
Number of Published Lectures: 20
Number of Curriculum Items: 20
Number of Published Curriculum Objects: 20
Original Price: 19.99
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
Mastering PySpark to Become a Data Engineer, Data Scientist, or Data Analyst
This course aims to train you in the PySpark framework on Python, which is widely used by Data Engineers, Data Scientists, and Data Analysts to handle large volumes of data.
Acquire Fundamental Skills in PySpark
No more hunting for information on Google; the essence of your learning is concentrated in this course.
Learn Quickly for Effective Skill Development
This course is designed to familiarize you with PySpark quickly and effectively. In just a few hours and through two projects, you will possess the necessary knowledge to stand out.
Recent Course, Regularly Updated
Updated in 2024, this training is in line with the skills currently sought after in PySpark by companies.
Avoid Beginner’s Traps
The course highlights the best practices of an experienced PySpark developer to help you produce professional-quality code.
Succeed in Your Exams, Technical Tests, and PySpark Certifications
The course content is structured to effectively prepare you for your university exams, certifications, and technical tests related to PySpark.
Secure a Position in a Company or Undertake Freelance Assignments
PySpark is among the most coveted frameworks in both corporate and freelance settings. Training in this library opens the door to numerous professional opportunities.
Train for In-Demand Careers
In 2024, the demand for Data Scientists, Data Engineers, Data Analysts, and other Big Data-related professions is on the rise. Now is the perfect time to train for these professions by learning to master PySpark.
Work for Top Companies
Renowned companies such as Uber, Netflix, Airbnb, Amazon, Meta (formerly Facebook), and Microsoft, are currently seeking skilled professionals in PySpark.
Obtain a Completion Certificate
A certificate confirming that you have followed and completed the course will be awarded at the end of the training.
Course Curriculum
Chapter 1: Get Started With PySpark for Data Engineers, Data Scientists, and Data Analysts
Lecture 1: Lets Get Started With PySpark!
Chapter 2: Project Setup
Lecture 1: How to Use Google Colab or Kaggle to Make the Project
Chapter 3: Complete Big Data Project Using PySpark
Lecture 1: Project Overview
Lecture 2: Data Source
Lecture 3: Install PySpark on Google Colab and Create a Spark Session
Lecture 4: Import Data Into a Spark DataFrame
Lecture 5: Store Data Files on Google Drive
Lecture 6: Rename and Delete Columns in a Data Table
Lecture 7: Create and Add New Columns in a Spark DataFrame
Lecture 8: Before Continuing the Course
Lecture 9: Filter a PySpark Dataframe with Conditions
Lecture 10: Group Data and Create New Columns Based on Existing Data
Lecture 11: Join PySpark Dataframes
Lecture 12: Perform Operations With Columns and Delete Unnecessary Data
Lecture 13: Create Statistical Columns
Lecture 14: Use Window Functions
Lecture 15: Create The Final Spark Data Table
Lecture 16: End of The PySpark Project
Chapter 4: Download The Complete Python Code For The PySpark Project
Lecture 1: Download The Code
Chapter 5: End of The PySpark Course
Lecture 1: Conclusion and Tips For Your Career
Instructors

Mikail Altundas
Data Engineer / Scientist
Rating Distribution
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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