Postgraduate Certificate in Serverless Data Processing with AWS Lambda & Kinesis

This course is designed for data scientists, engineers, and IT professionals looking to enhance their skills in serverless data processing using AWS services. Participants will learn to implement serverless architectures with AWS Lambda and Kinesis for real-time data processing and analysis. By the end, they will be capable of designing, deploying, and optimizing serverless solutions to handle large-scale data streams efficiently.

Students will gain hands-on experience in building scalable, cost-effective data processing pipelines, automating common data workflows, and leveraging AWS's serverless compute and streaming services to process and analyze real-time data. Practical projects and case studies will ensure participants can apply their knowledge to solve real-world challenges.

1. 1. Introduction to Serverless Data Processing: Learners will understand the foundational concepts of serverless computing, focusing on AWS Lambda and Amazon Kinesis. They will gain an understanding of how to design serverless architectures and the benefits of using serverless technologies for data processing.
2. 2. AWS Lambda Fundamentals: This module covers the core principles of AWS Lambda, including execution models, triggers, and memory management. Learners will develop practical skills in writing and deploying Lambda functions and integrating them with other AWS services.
3. 3. Amazon Kinesis Data Streams: Learners will study the design and implementation of Amazon Kinesis Data Streams, understanding how to ingest, process, and analyze real-time data streams. Practical skills in stream creation, shard management, and data consumer setup will be acquired.
4. 4. AWS Lambda with Kinesis Data Streams: This module delves into the integration of AWS Lambda with Amazon Kinesis Data Streams, focusing on real-time data processing workflows. Learners will gain hands-on experience in setting up Lambda functions as stream processors and building complex data processing pipelines.
5. 5. AWS Lambda and Event-Driven Architectures: This module explores event-driven architectures using AWS Lambda, covering various event sources and triggers. Learners will design and implement event-driven systems, enhancing their ability to build scalable and responsive applications.
6. 6. Security and Compliance in Serverless Data Processing: This module covers security and compliance best practices for serverless applications, focusing on AWS Lambda and Amazon Kinesis. Learners will understand how to secure data at rest and in transit, and will learn about compliance frameworks relevant to serverless data processing.
7. 7. Advanced AWS Lambda Features: This module introduces advanced features of AWS Lambda, such as VPC support, layer functions, and Cold Start optimizations. Learners will deepen their knowledge of Lambda’s capabilities and learn techniques to optimize performance and resource utilization.
8. 8. Monitoring and Managing Serverless Data Processing: This module covers monitoring and managing AWS Lambda and Amazon Kinesis in production environments. Learners will learn to use AWS CloudWatch, X-Ray, and other tools to monitor performance, diagnose issues, and manage costs effectively.
9. 9. Serverless Data Processing Best Practices: This module provides a comprehensive guide to best practices for building and maintaining serverless data processing applications. Learners will understand how to design, implement, and maintain robust, scalable, and cost-effective serverless architectures.
10. 10. Capstone Project: Building a Serverless Data Processing Solution: Learners will apply their knowledge and skills to develop a comprehensive serverless data processing solution using AWS Lambda and Amazon Kinesis. This project will allow learners to integrate multiple components, optimize performance, and demonstrate their understanding of serverless architecture principles.