Data Engineering Design Principles from AWS-Part 3
4Here is a suggested title, tags, and description for your AWS Academy Data Engineering video:\nTitle:\nAWS Academy: Data Engineering Module Deep Dive\nTags:\naws academy, data engineering, data pipelines, analytics vs ai/ml, data wrangling, infrastructure, roles, modernization\nDescription:\nGet an in-depth look at the key topics covered in the AWS Academy's Data Engineering module including:\nComparing analytics vs AI/ML pipelines\nLayers of a data pipeline\nData transformation actions\nData engineer vs data scientist roles\nBuilding & modernizing data infrastructure\nBreaking down data silos\nInnovation opportunities\nUseful for anyone going through the AWS Academy program or wanting an overview of fundamental data engineering concepts. We explain the core curriculum objectives in detail and connect the foundational ideas organizations need to leverage to become data-driven.\n\n\nHands-On Courses for Rust, Data, Cloud, AI and LLMs π\n\nRust Programming Specialization: https://www.coursera.org/specializations/rust-programming\nRust for DevOps: https://www.coursera.org/learn/rust-for-devops?specialization=rust-programming\nRust LLMOps: https://www.coursera.org/learn/rust-llmops?specialization=rust-programming\nRust Fundamentals: https://www.coursera.org/learn/rust-fundamentals\nData Engineering with Rust: https://www.coursera.org/programs/duke-university-on-coursera-obsio/learn/data-engineering-rust\nPython and Rust with Linux Command Line Tools: https://www.coursera.org/learn/python-rust-linux\nVirtualization, Docker, and Kubernetes for Data Engineering: https://www.coursera.org/learn/virtualization-docker-kubernetes-data-engineering\nCloud Machine Learning Engineering and MLOps: https://www.coursera.org/learn/cloud-machine-learning-engineering-mlops-duke\nMLOps Tools: MLflow and Hugging Face: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke\nData Visualization with Python: https://www.coursera.org/learn/data-visualization-python\nLinux and Bash for Data Engineering: https://www.coursera.org/learn/linux-and-bash-for-data-engineering-duke\nSpark, Hadoop, and Snowflake for Data Engineering: https://www.coursera.org/learn/spark-hadoop-snowflake-data-engineering\nCloud Virtualization, Containers and APIs: https://www.coursera.org/learn/cloud-virtualization-containers-api-duke\nCloud Data Engineering: https://www.coursera.org/learn/cloud-data-engineering-duke\nPython Essentials for MLOps: https://www.coursera.org/learn/python-mlops-duke\nDevOps, DataOps, MLOps: https://www.coursera.org/learn/devops-dataops-mlops-duke\nWeb Applications and Command-Line Tools for Data Engineering: https://www.coursera.org/learn/web-app-command-line-tools-for-data-engineering-duke\nMLOps Platforms: Amazon SageMaker and Azure ML: https://www.coursera.org/learn/mlops-aws-azure-duke\nScripting with Python and SQL for Data Engineering: https://www.coursera.org/learn/scripting-with-python-sql-for-data-engineering-duke\nPython and Pandas for Data Engineering: https://www.coursera.org/learn/python-and-pandas-for-data-engineering-duke\nCloud Computing Foundations: https://www.coursera.org/learn/cloud-computing-foundations-duke