PySpak is an open-source distributed set of libraries and frameworks for real-time large-scale data processing. It is Python API for Apache Spark, and students willing to learn PySpark can consider Udemy features more than 700 courses on PySpark.
The article contains the list of the 10 best Udemy PySpark Courses in 2024. In this regard, ‘PySpark Essentials for Data Scientists (Big Data + Python)’ is the best PySpark course on Udemy, with ratings from more than 5,000 students. Also, the ‘Best Hands-on Big Data Practices with PySpark & Spark Tuning’ is another highly rated Udemy PySpark course, and has an average student rating of 4.6/5 based on over 400 reviews. Also Check:
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PySpark End to End Developer Course (Spark with Python)
In the PySpark End-to-End Developer Course Spark with Python course, students will learn about the features and functionalities of PySpark. Also, various topics related to PySpark like components, RDD, Operations, Transformations, Cluster Execution, and more are covered. As an addition, this course also features a small Python and HDFS course.
- Course Rating: 4.0/5
- Duration: 29 hours 6 minutes
- Benefits: Certificate of completion, Mobile and TV access, Lifetime access, 35 downloadable resources, 4 articles
Learning Outcomes
| PySpark Development Functionalities and Features | Spark SQL Architecture |
| Spark Cluster Execution Architecture | Spark Performance and Optimisation |
| Python | HDFS |
PySpark Essentials for Data Scientists (Big Data + Python)
PySpark Essentials for Data Scientists (Big Data + Python) uses data to provide comprehensive training in PySpark. Students will learn about MLib API, building ML models, and how PySpark is used in a job. Also, they will be given theoretical and coding exercises to practice skills.
- Course Rating: 4.7/5
- Duration: 17 hours 16 minutes
- Benefits: Certificate of completion, Mobile and TV access, Lifetime access, 139 downloadable resources, 28 articles
Learning Outcomes
| Python with Big Data on a distributed framework | Spark Structured Streaming for streaming LIVE data from Twitter |
| Natural Language Processing for flagging suspicious job postings | Christmas cooking recipes using Topic Modeling (LDA) |
| Cluster analysis to increase college graduation rates for under-privileged populations | UI to monitor model training with MFLOW |
| Dataframes in Spark with Python | Cross Validation and Hyperparameter Tuning |
| Classification and Regression Techniques | SQL Queries in Spark |
| REAL datasets on consulting projects | An app that classifies songs into genres |
| ML to predict optimal cement strength and affecting factors | Gaussian Mixture Modeling (Clustering) for Customer Segmentation |
| k-means clustering algorithm | Spark’s machine learning techniques on distributed Dataframes |
| Frequent Pattern Mining Techniques | Data Wrangling for Natural Language Processing |
Best Hands-on Big Data Practices with PySpark & Spark Tuning
This course deals with providing students with data from academia and industry to develop their PySpark skills. Students will work with Spark RDD, DF, and SQL for distributed processing challenges like data skewness and spill within big data processing. Besides covering the details, the course also focuses on big data problems. Upon completion of the course, students will be able to use Spark and PySpark easily and will be familiar with big data analytics concepts.
- Course Rating: 4.6/5
- Duration: 13 hours
- Benefits: Certificate of completion, Mobile and TV access, 38 downloadable resources, 2 articles
Learning Outcomes
| Apache Spark’s framework, execution, and programming model | Big Data applications for different types of data |
| Optimization and performance tuning methods to manage data Skewness and prevent Spill | Lazy evaluations and internal working of Spark |
| Spark setup and configuration via free Cloud-based and Desktop machine | PySpark practices on different data types |
| Adaptive Query Execution (AQE) to optimize Spark SQL query execution | Spark SQL applications using JDBC |
Complete PySpark & Google Colab Primer For Data Science
In Complete PySpark & Google Colab Primer For Data Science, students will learn about the PySpark Big Data ecosystem within the Google CoLab framework. Additionally, students will understand the concepts of data reading and cleaning to implement powerful ML and neural network algorithms and evaluate their performance using Pyspark. After completing this course students will become efficient in PySpark concepts and will be able to develop machine learning and neural network models using it.
- Course Rating: 4.6/5
- Duration: 4 hours 19 minutes
- Benefits: Certificate of completion, Mobile and TV access, 1 downloadable resource, 1 article
Learning Outcomes
| Google Colab | PySpark Within the Google Colab Environment |
| Common Statistical Analysis using PySpark | Deep Learning Models Within PySpark |
| PySpark Uses and Functioning | Data Processing Using PySpark |
| Common Machine Learning Techniques | – |
Big Data Analytics with PySpark + Power BI + MongoDB
Big Data Analytics with PySpark + Power BI + MongoDB course will teach students to create big data pipelines using different technologies like PySpark, MLlib, Power BI, and MongoDB. Upon completion of the course, students will develop skills in predictive modeling and visualization.
- Course Rating: 4.6/5
- Duration: 3 hours 54 minutes
- Benefits: Certificate of completion, Mobile and TV access, Lifetime access, 1 downloadable resource, 1 article
Learning Outcomes
| Power BI Data Visualisation | Data Analysis |
| Big Data and Geospatial Machine Learning | PySpark Programming |
| PySpark Programming | Data Transformation and Manipulation |
| ArcMaps for Geo Mapping | Dashboards |
PySpark Developer – Advanced
PySpark Developer – Advanced introduces students to big data and the Hadoop ecosystem. Students will develop skills in Hadoop and analytic concepts in this course. The course also features parallel programming, in-memory computation, and Python. Hence, after this course, students will be able to perform data analysis efficiently using PySpark.
- Course Rating: 4.5/5
- Duration: 1 hour 12 minutes
- Benefits: Certificate of completion, Mobile and TV access, Lifetime access
Learning Outcomes
| Development, big data, and the Hadoop ecosystem skills | Recency Frequency Monetary segmentation (RFM) |
| Parallel programming and in-memory computation | Monte Carlo Simulation for Text Mining |
A Crash Course in PySpark
This course introduces students to the basics of PySpark. Students will learn to perform different tasks like getting hold of data, handling missing data and cleaning data up, filtering, pivoting, and more. Students will develop a base to use Spark on large datasets after completing the course.
- Course Rating: 4.5/5
- Duration: 1 hour 15 minutes
- Benefits: Certificate of completion, Mobile and TV access, 3 downloadable resources, 1 article
Learning Outcomes
| PySpark | Apache Spark |
| Big Data Analytics and Processing | Python |
Spark and Python for Big Data with PySpark
Spark and Python for Big Data with PySpark teaches students to use Spark with Python. In this course, students will learn to use Apache Spark to analyze big data sets, and topics such as Python basics, Spark DataFrames with the latest Spark 2.0 syntax, and MLlib Machine Library with the DataFrame syntax and Spark. Furthermore, Spark technologies like Spark SQL, Spark Streaming, and advanced models like Gradient Boosted Trees are also covered in the course.
- Course Rating: 4.5/5
- Duration: 10 hours 35 minutes
- Benefits: Certificate of completion, Mobile and TV access, 4 downloadable resources, 4 articles
Learning Outcomes
| Analysing Big Data using Spark and Python | Consulting Projects mimicking practical situations |
| Spark with Random Forests for Classification | Spark’s MLlib to create Powerful ML Models |
| AWS EC2 for Big Data Analysis | Linux with a Spark Environment |
| Spark Streaming to Analyse Tweets in Real Time | Spark 2.0 DataFrame Syntax |
| Customer Churn with Logistic Regression | Spark Gradient Boosted Trees |
| DataBricks Platform | AWS Elastic MapReduce Service |
| Spark and Natural Language Processing for Spam Filter | – |
PySpark Project – End to End Real Time Project Implementation
The course teaches students to implement a PySpark real-world project. Students will learn to code in Spark framework and understand topics like the latest technologies, Python, HDFS, creating a data pipeline, and more. Upon completion of the course, students will have the skills to apply for PySpark Developer jobs.
- Course Rating: 4.6/5
- Duration: 14 hours 49 minutes
- Benefits: Certificate of completion, Mobile and TV access, Lifetime access, 121 downloadable resources, 7 articles
Learning Outcomes
| End-to-End PySpark Real-Time Project Implementation | PySpark coding framework |
| Spark as a Standalone in Windows | HDFS and Python |
| Business Model and project flow of a USA Healthcare project | Adding Logging configuration in PySpark Project |
| Transferring files to S3 and Azure Blobs | Single Node Cluster at Google Cloud and integrating with Spark |
| Integrating Spark with a Pycharm IDE | Creating a data pipeline |
| Error handling mechanism in PySpark Project | Persisting data in Hive and PostgreSQL for future use |
50 Hours of Big Data, PySpark, AWS, Scala and Scraping
50 Hours of Big Data, PySpark, AWS, Scala, and Scraping is a beginner-friendly course that helps students understand big data concepts. Students will learn to efficiently use PySpark and Scala to handle big datasets in their projects. The course also introduces students to Python, data scraping, data mining, and MongoDB. After completing this course, students will be able to implement their big data projects and will know related concepts.
- Course Rating: 4.4/5
- Duration: 54 hours 39 minutes
- Benefits: Certificate of completion, Mobile and TV access, Lifetime access, 4 articles
Learning Outcomes
| Python, Scrapy, Scala, PySpark, and MongoDB concepts with examples | Data Scraping and Data Mining with Python |
| Big Data With PySpark and AWS | AI applications |
| Big Data with Scala and Spark | MongoDB for Beginners |
Information Technology Essentials
This Information Systems course is ideal for beginners, covering key topics like hardware, binary numbers, software development, database management, cloud computing, security, and future computing.
- Course Rating: 4.5/5
- Duration: 4.5 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 11 Articles, 21 Downloadable Resources, Assignments
Learning Outcomes
| You will also learn some of the history of computing and some of the emerging technologies. | By the end of the course, you will have a solid understanding of major information systems concepts |
| In this course you will learn how software is developed, the basic operation of a computer, and how networks function | You will also learn the basics of HTML and how websites operate |
VoIP PBX & Call Center on Asterisk 16 Issabel [Master Class]
This course provides an in-depth introduction to Issabel, an open-source IP telephony software based on Asterisk, suitable for beginners and small businesses. It covers telephony concepts, real-world applications, and lab practices, offering valuable VoIP and phone systems knowledge.
- Course Rating: 4.3/5
- Duration: 12.5 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 9 Articles, 21 Downloadable Resources, Assignments
Learning Outcomes
| Build the complete IP Phone System using an open-source platform. | Explore exciting careers in the Telecom Industry. |
| Feel more confident in managing the Issabel Telephony Server. | Offers Open Source IP Telephony services & solutions to your customers. |
Data Modeling and Relational Database Design using ERwin
Data Modeling and Relational Database Design using ERwin teaches data modeling using the ERWIN tool, focusing on definitions, structure, relationships, and integration points. It’s also suitable for data modelers, architects, database administrators, ETL developers, DWH/BI professionals, and business analysts.
- Course Rating: 4.4/5
- Duration: 3.5 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 4 Articles, 8 Downloadable Resources, Assignments
Learning Outcomes
| Normalize the Entity Relationship Diagram to the third Normal form | Develop sound database designs by applying proven data modeling techniques |
| Engineer/Re-engineer the data Models into and from relational database designs | Work with database change requests and maintain existing databases with the help of tools |
Java Web Services
This SOAP and REST web services course is designed for Java developers, JEE developers, and Java students. It has over 40,000 students and 3000+ five-star reviews, and it covers topics like web service advantages, WSDL, design, implementation, standards, testing, and REST concepts.
- Course Rating: 4.6/5
- Duration: 16.5 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 5 Articles, 24 Downloadable Resources
Learning Outcomes
| Use Apache CXF, the Popular WS Stack | Understand why web services are so popular |
| Understand the different types of WS Design | Implement Contract First and Code First Web Services |
| Develop a Web Service for Consumer | Master the REST web service concepts and Implementation |
How To Write User Stories That Deliver Real Business Value
How To Write User Stories That Deliver Real Business Value simplifies user stories for product owners, business analysts, developers, and agile team members, covering structure, importance, communication, role modeling, stakeholder identification, and converting stories into acceptance tests using Gherkin’s GIVEN-WHEN-THEN scenarios.
- Course Rating: 4.6/5
- Duration: 4 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 1 Article, 1 Downloadable Resource
Learning Outcomes
| Understand the power of the 3 C’s of a User Story – The Card, the Conversation, and the Criteria (or Confirmation). | Reduce time to deliver software by giving developers well-formed, actionable User Stories answering the WHO, WHAT, and WHY of a business need. |
| Identify User Story contributors using User Role Modeling, Persona Development, and Stakeholder Identification techniques. | Minimize miscommunication and misunderstandings by checking User Stories at the RIGHT time and to the RIGHT level of detail. |
| Learn 6 techniques to reduce ambiguity, save time in 3-Amigos Conversations, and allow your Agile Team to deliver solutions that delight end-users | Apply 8 ways to split User Stories, Epics, and Features in Preparation for Imminent Sprints or Releases. |
Docker for the Absolute Beginner – Hands On – DevOps
This Docker beginner course is designed for system administrators, offering lectures, demos, and coding exercises. Additionally, it provides real-life assignments and is suitable for beginners in DevOps, including system administrators, cloud infrastructure engineers, and developers. However, it should be noted that it is not affiliated with Docker, Inc.
- Course Rating: 4.6/5
- Duration: 4.5 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 21 Articles, 1 Downloadable Resource
Learning Outcomes
| Beginner level introduction to Docker | Basic Docker Commands with Hands-On Exercises |
| Understand what Docker Compose | Build Application stack using Docker Compose Files with Hands-On Exercises |
Ansible for the Absolute Beginner – Hands-On – DevOps
Ansible for the Absolute Beginner – Hands-On – DevOps course offers a comprehensive introduction to Ansible for beginners in DevOps, covering fundamental concepts and practical exercises. So, this course is suitable for system administrators, cloud infrastructure engineers, and automation engineers.
- Course Rating: 4.5/5
- Duration: 3 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 17 Articles, 1 Downloadable Resource
Learning Outcomes
| Beginner level introduction to Ansible | Introduction to YAML and Hands-on Exercises |
| Build Ansible Inventory Files with Hands-on Exercises | Build Ansible Inventory Files with Hands-on Exercises |
Azure DevOps Fundamentals for Beginners
Microsoft Certified Trainer Brian Culp’s “Azure DevOps Fundamentals for Beginners” is a hands-on course for beginners in DevOps concepts, covering Azure Boards, Repos, Pipelines, and Test Plans, ideal for IT professionals and developers.
- Course Rating: 4.5/5
- Duration: 3.5 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 12 Downloadable Resources
Learning Outcomes
| Create an Azure DevOps organization | Align Azure DevOps work items using Agile, Scrum, or Basic work processes |
| Integrate an Azure DevOps code repository with GitHub | Understand the basic vocabulary of DevOps: what it is and why it matters |
Spring Framework Master Class – Java Spring the Modern Way
The “Spring Framework Master Class – Learn Spring the Modern Way!” course is designed for Java programmers, covering IOC, DI, Application Context, Bean Factory, Spring Boot, AOP, JDBC, and JPA.
- Course Rating: 4.5/5
- Duration: 12.5 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 1 Downloadable Resource, 14 Articles
Learning Outcomes
| You will Learn Spring Framework the MODERN WAY – The way Real Projects use it! | You will Become a COMPLETE Spring Developer – With the ability to write Great Unit Tests |
| You will become the GO TO GUY for Fixing Spring Framework problems in Your Project | You will GO FROM a Total Beginner to an EXPERIENCED Spring Developer |
| You will learn the basics of Eclipse, Maven, JUnit, and Mockito | You will develop a basic Web application step by step using JSP Servlets and Spring MVC |
Introduction to Cloud Computing on AWS for Beginners [2024]
This “Introduction to Cloud Computing on AWS for Beginners” course is designed for beginners, providing a comprehensive understanding of cloud computing concepts, including storage, database, networking, virtualization, containers, and cloud architecture.
- Course Rating: 4.5/5
- Duration: 7 Hours
- Benefits: Access on mobile and TV, Certificate of completion, 2 Articles
Learning Outcomes
| This course covers fundamental concepts of cloud computing and is designed for absolute beginners | Gain an understanding of the fundamental systems on which the cloud is based, including storage, networking, and compute |
| Develop hands-on skills using core Amazon Web Services (AWS) services | Build knowledge from beginner level to advanced concepts |
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Udemy PySpark Courses: FAQs
Ques. What is PySpark?
Ans. PySpark is an open-source Python API used for real-time large-scale data processing. It is built for Apache Spark.
Ques. Who should take Udemy PySpark courses?
Ans. PySpark courses are ideal for individuals who work with big data and its analysis. It generally includes data scientists, data analysts, engineers, and students looking to learn more about PySpark.
Ques. Are there any prerequisites before joining Udemy PySpark courses?
Ans. Before opting for Udemy PySpark courses students are advised to have a basic understanding of Python and data analysis. There are also introductory courses that do not have any prerequisites and teach students about Python and other basics.
Ques. What skills do I get after completing Udemy PySpark courses?
Ans. The ability to easily work on big data, RDD and data frames, ML algorithms, and Spark SQL are some of the major skills that can be learned from Udemy PySpark courses.
Ques. Name some top Udemy PySpark courses.
Ans. Some of the best Udemy PySpark courses are –
- PYSPARK End-to-End Developer Course (Spark with Python).
- PySpark Essentials for Data Scientists (Big Data + Python).
- Best Hands-on Big Data Practices with PySpark & Spark Tuning.
- Complete PySpark & Google Colab Primer For Data Science.
- A Crash Course in PySpark.
Ques. What are the benefits of learning PySpark?
Ans. PySpark enhances analysis by facilitating the integration of local and distributed data transformation operations, thereby reducing computing costs and enabling data scientists to avoid downsampling large data sets.
Ques. What are the core components of PySpark?
Ans. Apache Spark comprises five components: Spark Core Engine, Spark SQL, Spark Streaming, MLlib, GraphX, and Spark R, which can be used alongside each other.
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