Executive Development Programme in Data Processing at Scale with AWS Lambda and S3

This course is tailored for mid-to-senior level executives and data processing professionals seeking to leverage AWS Lambda and S3 for efficient, scalable data processing solutions. Participants will gain a deep understanding of AWS's serverless computing and storage services, enabling them to architect, implement, and optimize scalable data processing pipelines.

Upon completion, attendees will be able to design and manage serverless architectures that enhance operational efficiency, reduce costs, and improve data processing speed. They will also learn to integrate AWS Lambda and S3 with other AWS services to build robust, scalable applications, and gain insights into best practices for security and governance in cloud-based data processing environments.

1. 1. Introduction to Data Processing at Scale: Learners will understand the challenges of processing large volumes of data and the importance of scalable solutions. They will gain foundational knowledge in data processing concepts and the need for distributed computing.
2. 2. AWS Fundamentals: Learners will familiarize themselves with AWS services, focusing on S3 and Lambda, understanding their roles in data storage and processing, respectively. Practical skills include setting up an AWS account and creating basic S3 and Lambda functions.
3. 3. Introduction to AWS S3: Learners will delve into the features and capabilities of Amazon S3, including object storage, lifecycle management, and versioning. Practical skills include uploading, managing, and securing data using S3 buckets.
4. 4. Introduction to AWS Lambda: Learners will explore serverless computing with AWS Lambda, understanding how it works, its benefits, and limitations. Practical skills include deploying and testing Lambda functions, writing event-driven functions, and using triggers.
5. 5. Building Scalable Data Processing Pipelines with S3 and Lambda: Learners will learn how to design and implement scalable data processing pipelines using S3 for storage and Lambda for processing tasks. Practical skills include creating workflows, handling data transformations, and implementing error handling.
6. 6. Advanced S3 Features and Use Cases: Learners will expand their knowledge by exploring advanced S3 features like S3 Select, cross-region replication, and S3 Transfer Acceleration. Practical skills include optimizing data storage, improving performance, and securing data across regions.
7. 7. Advanced AWS Lambda Use Cases: Learners will learn about more complex use cases and best practices for AWS Lambda, including concurrency management, cold start optimization, and integration with other AWS services. Practical skills include debugging Lambda functions, optimizing performance, and implementing advanced deployment strategies.
8. 8. Security and Compliance in Data Processing: Learners will understand the importance of security and compliance in data processing and learn how AWS S3 and Lambda support security and compliance objectives. Practical skills include implementing access controls, encryption, and auditing mechanisms.
9. 9. Monitoring and Logging for Data Processing: Learners will learn how to monitor and log data processing activities using AWS services like CloudWatch and CloudTrail. Practical skills include setting up monitoring, analyzing logs, and responding to alerts.
10. 10. Optimizing Costs for Data Processing with AWS: Learners will explore strategies for optimizing the cost of data processing on AWS, including cost estimation, budgeting, and optimizing resource usage. Practical skills include creating cost-effective architectures, managing resources efficiently, and tracking expenses.