Event 2

Summary Report: Data Science on AWS - Workshop

Event Objectives

• Introduce students and participants to modern data science workflows using AWS Cloud.
• Demonstrate how cloud services support data processing, model training, deployment, and scaling.
• Provide practical exposure through a hands-on machine learning project using real datasets.

Speakers

• Van Hoang Kha – AWS Community Builder
• Bach Doan Vuong – Cloud Develops Engineer, AWS Community Builder

Key Highlights

• Industry experts delivered sessions on data processing, data pipelines, and ML model deployment using cloud platforms.
• Overview of AWS Generative AI services and how they support various real-world applications.
• End-to-end walkthrough of building a sentiment analysis model using AWS-powered ML tools.

Key Takeaways

• Data science on cloud requires understanding pipelines, infrastructure, and deployment workflows.
• Cloud services provide clear benefits in scalability, performance, and ease of experimentation, but come with cost considerations.
• Machine learning becomes more accessible when tied to hands-on, real-world demos rather than abstract theory.
• Exposure to industry practice helps bridge the gap between university learning and real engineering expectations.

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