Building AI Applications

NOTE: Hands-On AI Software Training – See Requirements & Prerequisites

Workshop Title: Learn to build AI applications with no code, low code, and using AI powered coding assistant

Presenters:

  • Ashish Vaidya, Principal Engineer, Amazon Alexa
  • Abhai Pratap Singh, Senior Product Manager-Technical, Amazon Alexa
  • Ramakanth Damodaram, Technical Account Manager at Amazon Web Services
  • Neha Shetty, Principal Software Development Engineerr  at Amazon Web Services

Abstract:

Join this immersive hands-on workshop to learn building simple AI applications using PartyRock – a gen AI playground, using Bedrock to compare and use latest and greatest large language models, and using Codewhisperer to further accelerate application development. By the end of the workshop, participants would understand the difference between these AWS AI offerings, and which one to use where.

  • Part1: We will start with PartyRock – an easy-to-use AI playground that allows users to quickly turn their ideas into working prototypes. We will cover key features of PartyRock i.e. creating apps from scratch, remixing existing apps, and leveraging pre-built prompts to get started. This portion does not require any coding.
  • Part2: Next we will dive into Bedrock that enables access to the high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, You would learn to experiment with and evaluate different foundation-models for your usecase, and to access them from your application. This would be a low-code portion where you will create a simple application to access the model programmatically.
  • Part 3: Lastly, we will look into Amazon Q developer  (Codewhisperer), configuring it for your development environment and leveraging its capabilities for quickly building a simple app and also look at some more advanced usecases.

Key Takeaways: 

  1. Learn to build simpler AI apps without writing any code
  2. Learn to build simple to moderately complex AI apps with minimal code
  3. Learn to build more complex AI apps with AI powered coding assistant

Target Audience: Anyone interested in learning to build AI apps.

For Attendees:

Required Equipment: Laptop

Installed software: Visual Studio code

Accounts created:

    • Partyrock account (can be created during the workshop)
    • AWS account for accessing Bedrock and Amazon Q Developer(can be created during the workshop)

Prerequisite Knowledge:

    • AI/ML: none
    • Coding experience: Beginner level or above is helpful for the latter half of the workshop.

The certificate will be mailed to you upon completion of the workshop.

Presenter Bios:

Ashish Vaidya, Principal Engineer for Amazon Alexa

Ashish Vaidya is a Principal Engineer in Amazon and works on continuously improving Alexa-Amazon’s voice AI. He has 16 years of experience in the software engineering industry, with a proven track record of designing, developing and delivering high-quality solutions across diverse technological domains. His expertise spans enterprise operating systems, file transfer protocols, mobile and wearable applications, advertising systems, language translation, cloud technologies, and currently, voice-controlled virtual assistants. He has four patents granted by the USPTO and two more under review. He is also an IEEE Senior member.

See https://www.linkedin.com/in/connect2avaidya/

 

Abhai Pratap Singh, Senior Product Manager-Technical at Amazon Alexa

Abhai Pratap Singh is currently Senior Product Manager-Technical at Amazon’s Alexa division, where he drives strategic initiatives to enhance Alexa’s audio experiences through innovative AI and machine learning capabilities, including generative AI and multimodal interaction.

See https://www.linkedin.com/in/abhaipsingh1

 

Ramakanth Damodaram, Technical Account Manager at Amazon Web Services

Ramakanth Damodaram is currently Technical Account Manager at Amazon Web Services Inc. where he is responsible for leading customers AWS-Cloud Strategy, Enablement, Governance & FinOps practices. He is certified in AWS Partner: Generative AI Essentials.

See https://www.linkedin.com/in/ramdamodaram

 

 

Neha Shetty, Principal Software Development Engineer  at Amazon Web Services

Neha Shetty is a Principal Engineer at Amazon Web Services focusing on  Application Load Balancing. Neha has been a software developer at Amazon since 2013 working in building multiple distributed systems in Amazon S3, AWS ELB and AWS VPC Lattice. She has over 14 years of experience across networking, distributed systems, load-balancing and security.