Скачать или смотреть FULL COURSE 🔥 Apache PySpark Master Data Transformation and Visualization

In this comprehensive course, you will enhance your PySpark skills by engaging in a project challenge centered around your chosen dataset. We will guide you through crucial steps, including loading data into a DataFrame for initial exploration. You'll learn how to conduct exploratory data analysis, clean datasets for accuracy, and apply essential data transformations for deeper insights. We put a significant emphasis on visualizing your findings effectively, helping you communicate results clearly. Finally, the course underscores the importance of documenting methodologies and insights in a professional report, allowing you to showcase your data analysis skills confidently. Join us to master the art of data manipulation and visualization using PySpark!
GitHub Repository: https://github.com/martinyanev94/pysp...


0:00:00 - 0 Introduction to the Course
0:00:35 - 1 Introduction To Spark
0:12:52 - 2 Setting Up The Environment
0:22:14 - 3 Data Processing With Spark
0:33:10 - 4 Advanced Spark Applications
0:46:59 - 5 Spark Configuration Essentials
0:55:31 - 6 Advanced Data Processing Techniques
1:03:52 - 7 Building And Managing Spark Applications
1:14:15 - 8 Optimizing Spark Performance Strategies
1:23:43 - 9 Real World Case Studies
1:30:42 - 10 Advanced Spark Features And Capabilities
1:41:13 - 11 Best Practices For Spark Performance Tuning
1:52:37 - 12 Conclusion And Future Directions
2:00:13 - 13 Understanding Spark Python Requirements
2:09:24 - 14 Running Spark Applications With Cloudera
2:17:17 - 15 Interacting With Spark Using Pyspark
2:26:33 - 16 Leveraging Spark For Data Processing Efficiencies
2:36:13 - 17 Spark Configuration Management
2:42:45 - 18 Spark Session Initialization
2:48:09 - 19 Spark Environmental Settings
2:57:27 - 20 Spark Package Management And Installation
3:04:06 - 21 Spark Performance Monitoring
3:13:51 - 22 Effective Data Management Strategies
3:23:03 - 23 Integration Of Spark With Other Frameworks
3:33:00 - 24 Future Trends In Spark Development
3:40:51 - 25 Spark Application Deployment Strategies
3:48:58 - 26 Advanced Error Handling Techniques In Spark
3:57:57 - 27 Integrating Spark With External Data Sources
4:07:06 - 28 Advanced Machine Learning Techniques
4:13:46 - 29 Optimizing Spark Deployment Models
4:23:32 - 30 Integrating Spark With External Tools
4:32:41 - 31 Streamlining Data Processing With Spark


Business contact: [email protected]