Build and Deploy ETL Pipelines with Python By Ian Fogelman

[AD-TEAM]

1.85 GB | 00:06:21 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
yxusj.1 Course Introduction.mp4 (13.22 MB)
yxusj.2 Pandas and SQL Alchemy.mp4 (11.09 MB)
yxusj.3 Loading Data from Files and APIs with Pandas.mp4 (17.26 MB)
yxusj.4 Connecting to Databases with SQLAlchemy.mp4 (7.25 MB)
yxusj.1 Common Pandas Transformation Use Cases.mp4 (7.78 MB)
yxusj.2 Handling Null Values in Pandas.mp4 (8.67 MB)
yxusj.3 Demo - Cleaning and Preparing Data with Pandas.mp4 (13.27 MB)
yxusj.4 Demo - Big Data with Dask.mp4 (12.8 MB)
yxusj.1 Understand Data Loading with Pandas.mp4 (11.8 MB)
yxusj.2 Writing Data to Your Cloud Storage.mp4 (9.71 MB)
yxusj.3 High-performance File Formats.mp4 (9.59 MB)
yxusj.1 Scheduling Your Python Pipelines.mp4 (7.32 MB)
yxusj.2 Modularize Your Code.mp4 (6.11 MB)
yxusj.3 Schedule Your Python ETL Pipeline.mp4 (9.17 MB)
yxusj.4 ETL Pipe Best Practices - Environment Variables, Logging, and Validating.mp4 (10.57 MB)]
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