Master AWS Lambda Functions for Data Engineers using Python

🚀 Course Title: Master AWS Lambda Functions for Data Engineers using Python

🎓 Course Headline: Build Lambda Functions using Python, Lambda Triggers, Deploy using layers and Docker, Validate using Glue and Athena

🎉 Course Description:

Are you eager to master the art of AWS Lambda Functions with a focus on Data Engineering using Python? This comprehensive course is designed to take you through an end-to-end data pipeline using key AWS Services. By the end of this course, you'll be well-versed in developing, deploying, and managing Python-based applications that interact with AWS services like Boto3, S3, Dynamodb, ECR, Cloudwatch, Glue Catalog, and Athena.

What You Will Learn:

👨‍💻 Development Environment Setup:

• Configuring Ubuntu with WSL (Windows Subsystem for Linux), Docker Desktop, and Visual Studio Code along with the Remote Development Extension Kit on Windows and Mac.

📊 Project & AWS Account Configuration:

• Setting up an AWS account and configuring the AWS CLI.
• Reviewing the datasets that will be used throughout the course.

🧬 Python Core Logic for Data Ingestion:

• Using Boto3 to ingest data from various sources into AWS S3.
• Employing Pandas and requests to handle data arithmetic and source file retrieval via REST API.

⚡ AWS Lambda Mastery:

• Getting hands-on with AWS Lambda using Python 3.9.
• Capturing bookmarks and job run details in Dynamodb, complete with an overview of the service.

📦 Lambda Deployment with Zip Files:

• Refactoring applications to be deployable as AWS Lambda functions within a zip file.

🚀 Custom Docker Images & ECR:

• Building and pushing custom docker images to AWS ECR.

🔄 S3 Event Notifications:

• Understanding and utilizing s3 event notifications or triggers for your lambda functions.

🛠️ Orchestrated Pipeline Creation:

• Developing a Python application to transform data into Parquet format and write it back to S3.

⏲️ Lambda Function Scheduling with EventsBridge:

• Scheduling lambda functions and validating their execution.

🗄️ Data Validation & Querying:

• Creating an AWS Glue Catalog table on your S3 location, running SQL queries with Athena, and understanding the lifecycle of AWS Glue.

✨ Layers for Lambda Functions:

• Exploring how to use AWS Lambda layers to optimize your functions' performance and maintainability.

Key Takeaways:

• Develop Python applications that can be deployed as AWS Lambda functions, either via zip files or using custom docker images.
• Utilize Cloudwatch for monitoring and troubleshooting your Lambda functions.
• Gain hands-on experience with Boto3, S3, Dynamodb, ECR, Cloudwatch, Glue Catalog, Athena, and more.
• Receive the complete code used for the demonstration and an accompanying Jupyter notebook to guide you through the core logic development.

🎓 Who Should Take This Course:

• Data Engineers who want to leverage AWS Lambda for their data processing tasks.
• Developers looking to expand their skillset with AWS services and Python application deployment.
• Anyone interested in exploring the potential of serverless architectures within data engineering contexts.

Join us on this journey to become an AWS Lambda Function expert for Data Engineering! 🌟

Enroll now to unlock a world of possibilities with AWS Lambda and Python for your data engineering projects! 🚀✨