Intro Data Engineering Part 2: Data Drive Organizations
Get an in-depth look at the key concepts covered in the AWS Academy's Data Engineering module. We'll analyze: Comparing data analytics vs AI/ML pipelines Layers of a data pipeline: ingestion, storage, processing, analysis Actions on data: cleaning, transformation, etc. Data engineer vs data scientist roles Building and modernizing data infrastructure Unifying data sources and governance Innovation with cloud services and pre-trained AI Useful for anyone going through the AWS Academy program or wanting a primer on data engineering foundations. We explain the module objectives in detail and connect the core ideas that data-driven organizations need to leverage.
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Show Notes
Hey readers 👋, if you enjoyed this content, I wanted to share some of my favorite resources to continue your learning journey in technology!
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- MLOps Tools: MLflow and Hugging Face: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke
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- Scripting with Python and SQL for Data Engineering: https://www.coursera.org/learn/scripting-with-python-sql-for-data-engineering-duke
- Python and Pandas for Data Engineering: https://www.coursera.org/learn/python-and-pandas-for-data-engineering-duke
- Cloud Computing Foundations: https://www.coursera.org/learn/cloud-computing-foundations-duke
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