IEEE New Era AI 2026 workshop " Building AI Applications with Amazon Bedrock" by Amazon Lambda : vTools Events

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IEEE New Era AI 2026 workshop " Building AI Applications with Amazon Bedrock" by Amazon Lambda

#application #chatbots #data-science #defense #image-processing #image-generation, #AI # #Amazon #Lambda,

Early Bird: 50% off before May 1st, In-person maximum 70 Seats, Remote: no limit.

50% off: Student $10, IEEE member: $17, Non-IEEE $30,

Remote $20 Certificate $7

In this hands-on workshop, participants build AI applications using Amazon Bedrock. Through guided
labs, they progress from foundational text generation and chatbots to advanced patterns including RAG,
multimodal image processing, structured data extraction, and security guardrails. Each lab produces a working
prototype that participants can extend. Along the way, participants gain experience with prompt engineering
techniques, learn to work with both text and image APIs, and explore how to secure AI applications with content
filtering, PII masking, and prompt attack prevention. The workshop is designed to be modular — participants can
focus on the tracks most relevant to their interests and move at their own pace.

Who Is This For?
The skills from this workshop apply across industries and roles.
 Healthcare professionals can use image understanding and multimodal capabilities to prototype tools for
analyzing medical imagery like X-rays or pathology slides.
 Data scientists and analysts can apply text extraction and summarization patterns to process research
papers, survey responses, or unstructured datasets at scale.
 Software engineers can integrate RAG-based chatbots into existing applications to surface answers from
internal documentation or knowledge bases.
 Business analysts can use structured data extraction to pull insights from contracts, customer feedback, or
financial reports without writing complex parsing logic.
 Students and Researchers in any field can prototype AI assistants that help with literature review, data
labeling, or experiment documentation.
Whether you write code daily or have never touched Python, the workshop's modular structure lets you engage at
the level that fits your background.

Speakers

Nithin Vommi is an Engineering Manager at Amazon Web Services, where he has spent nearly a decade building
and scaling large-scale distributed systems. He leads AWS Lambda streaming and queueing platforms, focusing on
serverless architectures and event-driven systems. Nithin has published technical articles, holds patents, and
speaks at AWS events including re:Invent. Over his time at AWS, he has launched more than a dozen customer-
facing features on serverless platforms, several highlighted at AWS re:Invent and broadly adopted by enterprises.
His current interests include serverless, generative AI, and event-driven design patterns.

Tejas Ghadge is engineering head for AWS Amplify, AWS Lambda Event Driven Applications and AWS Lambda
Developer Experience where he leads an organization of 100+ engineers/managers across multiple sites in US and
Canada. With over 14 years of experience at AWS, Tejas brings deep operational and architectural experience from
- operating large scale (millions of requests per second) event driven systems, leading and analyzing hundreds of
operational incidents and successfully launching dozens of delightful customer features for AWS Lambda and AWS
Amplify customers.

Technical Requirements

Laptop with a modern web browser (Chrome, Firefox, or Edge)
2. Stable internet connection
3. No local software installation required — labs run in a browser-based IDE and a temporarily provided AWS account
4. No prior machine learning or data science experience required

Key Takeaways for Participants
1. How to use Amazon Bedrock APIs for text generation, embeddings, image generation, and multimodal tasks.
2. Working prototypes across five tracks: text generation, RAG chatbot, document summarizer, image generator/editor, multimodal chatbot, and structured data extractor
3. Practical prompt engineering techniques applicable across models — summarization, content creation, translation, analysis, and code generation
4. Hands-on experience implementing guardrails for content blocking, PII masking, and prompt injection defense