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

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🎉 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! 🌟

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

🌟 Course Overview:

The course has received an excellent global rating of 4.46, with all recent reviews being positive. The content is highly recommended, with a few suggestions for improvement. The course is detailed and covers a wide range of AWS Lambda topics in a hands-on manner, suitable for beginners, especially those coming from a database background.

Pros:

• Informative Content: The course provides a comprehensive understanding of AWS Lambda, with a focus on practical application rather than theory. It covers the setup process from the ground up, including environment configuration and various deployment features.
• Detailed Instructions: The instructions are so detailed that they allow learners to complete all tasks without prior experience in the subject matter.
• Zero to Hero Approach: The course offers a zero to hero approach, guiding students through setting up their local environment and applying this knowledge to AWS Lambda.
• Real-World Application: The course includes various ways of interacting with AWS Lambda, making it comparable to top-notch Udemy courses, despite some repetition and lack of 'why' explanations.

Cons:

• Environment Setup Details Missing: The course begins with detailed instructions for setting up a local environment, but fails to mention important details such as using Ubuntu WSL in Visual Studio Code and the installation of AWS Cli within Ubuntu. This can lead to issues for learners attempting to execute Linux syntax commands.
• WSL Version Compatibility: The course does not address the compatibility issues with Docker and WSL version 1, which could affect learners' progress.
• Repetition and Unnecessary Details: There is some repetition of steps from previous lessons and unnecessary reiteration of previously covered topics, which could have been condensed to shorten the course by 20-30%.
• Time Management in Lessons: Some lessons take longer than necessary due to troubleshooting personal issues or explaining simple installations in detail. This can be frustrating and may make learners feel tired early on.
• Pacing and Accent: The instructor's pace is sometimes too fast, and their accent might require learners to adjust the speed of playback (e.g., to 0.75) for better understanding.

Additional Notes:

• It would be beneficial if the course included a brief description of the relationships between virtual environments, Windows Subsystem for Linux (WSL), and Visual Studio Code (VSC). Additionally, explaining options used in Linux commands would enhance comprehension.
• Some lessons could be simplified by providing a visual schema or an overview instead of repeating instructions verbally.
• The course's favorite statement, "this is nothing but…," repeated frequently, may become frustrating over time.
• A more gradual pace from the instructor would likely improve comprehension.
• Some lessons are too long and lack explanations for certain steps, which could be streamlined to save time.

Learner Experiences:

The majority of learners found the course valuable, with some suggesting additional topics such as AWS CDK for automation. Others mentioned adjusting playback speed due to the instructor's rapid speech and strong accent. Some learners encountered issues with their AWS Lambda functions, particularly when using Python versions not aligned with AWS standards.

Recommendation:

The course is informative and provides a solid foundation in AWS Lambda. With a few adjustments for clarity and pacing, it could be an excellent resource for beginners looking to understand AWS Lambda in-depth. The suggestions for improvement would make the course more engaging and less repetitive.