| 1. Introduction 1430K.mp4 | 41.6 MB | ||
| 10. Lazy Processing 1276K.mp4 | 10.1 MB | ||
| 11. [Exercise] Basic Functions 706K.mp4 | 6.2 MB | ||
| 12. [Exercise] Basic Functions - Solution 464K.mp4 | 21.4 MB | ||
| 13. Aggregating Data 1349K.mp4 | 17.8 MB | ||
| 14. Joining Data 1264K.mp4 | 19.7 MB | ||
| 15. Aggregations and Joins with Spark 477K.mp4 | 16.5 MB | ||
| 16. Complex Data Types 1356K.mp4 | 23.3 MB | ||
| 17. [Exercise] Aggregate Functions 654K.mp4 | 3.3 MB | ||
| 18. [Exercise] Aggregate Functions - Solution 434K.mp4 | 16.9 MB | ||
| 19. User Defined Functions 1328K.mp4 | 14.7 MB | ||
| 2. [Optional] What Is a Virtualenv_ 523K.mp4 | 18.4 MB | ||
| 20. Data Shuffle 1156K.mp4 | 24.4 MB | ||
| 21. Data Accumulators 1302K.mp4 | 16 MB | ||
| 22. Optimizing Spark Jobs 1191K.mp4 | 29.8 MB | ||
| 23. Submitting Spark Jobs 1011K.mp4 | 28.9 MB | ||
| 24. Other Spark APIs 1246K.mp4 | 21 MB | ||
| 25. Spark SQL 1058K.mp4 | 17.8 MB | ||
| 26. [Exercise] Advanced Spark 669K.mp4 | 8.8 MB | ||
| 27. [Exercise] Advanced Spark - Solution 552K.mp4 | 18.4 MB | ||
| 28. Summary 1277K.mp4 | 14.1 MB | ||
| 29. Let's Keep Learning Together! 1508K.mp4 | 6.5 MB | ||
| 3. Apache Spark 1277K.mp4 | 16.2 MB | ||
| 4. How Spark Works 1190K.mp4 | 17.2 MB | ||
| 5. Spark Application 1334K.mp4 | 34.2 MB | ||
| 6. DataFrames 1282K.mp4 | 27.6 MB | ||
| 7. Installing Spark 534K.mp4 | 25.2 MB | ||
| 8. Inside Airbnb Data 982K.mp4 | 34.2 MB | ||
| 9. Writing Your First Spark Job 524K.mp4 | 20.1 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 31 total files | |||
ZerotoMastery - Fundamentals of Apache Spark and PySpark
https://WebToolTip.com
Released 11/2025
Taught by Ivan Mushketyk
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 29 Lessons ( 2h 20m ) | Size: 571 MB
Get hands-on with Apache Spark and PySpark by learning how to build scalable, high-performance data pipelines using the DataFrame API, Spark jobs, joins, aggregations, and more.
What you'll learn
Learn the skills and real-world tools used by Data Engineers and become top 10% in your field
Set up Apache Spark and configure your local or cloud environment for big data processing
Write efficient PySpark code to handle, transform, and analyze large-scale datasets
Use DataFrames to manipulate data in a distributed computing environment
Build scalable data pipelines that integrate multiple transformation and aggregation steps
Create a strong foundation for a career in Data Engineering, Data Science, and AI/ML
Apache Spark is a must-know tool for any aspiring Data Engineer or Data Scientist. And PySpark? It’s your Python-powered key to unlocking Spark’s full potential.
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