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Deploying Agents: Serverless Python, AWS & Terraform

An intensive specialization to deploy Python conversational agents on AWS using Terraform, covering API Gateway (HTTP/WebSocket), Lambda, and integration with Web, WhatsApp, and Facebook Messenger.

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Description

This specialization course is designed for developers who already have skills in building conversational agents with Python and want to take their projects to the next level: production. Across four intensive sessions, you will explore the essential tools and practices to deploy, manage, and scale your agents on Amazon Web Services (AWS), automating infrastructure with Terraform. We will dive into building robust serverless architectures using AWS Lambda and API Gateway (both HTTP and WebSocket) to expose your agent to multiple channels. You will learn to orchestrate this infrastructure efficiently and reproducibly with Terraform. Then, we focus on hands-on integration, deploying your agent on key platforms such as web, WhatsApp, and Facebook Messenger. By the end of this course, you will be equipped with the knowledge and experience to deploy your text conversational agents professionally and scalably in a real production environment.

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Resume

  • Terraform - 1 hr. 20 mins.

    Terraform is implemented as IaC for use with AWS.

  • AWS - 1 hr. 20 mins.

    Services are deployed via Terraform on AWS, such as API Gateway, DynamoDB, Lambda, SQS, and others.

  • Best Practices - 20 mins.

    CloudWatch is set up to track WA and FB Messenger events, along with integrating Lambda Layers.

  • Front-End WebChat (React) - 1 hr.

    Create a responsive WebChat in React with hooks to send/receive messages, typing indicators, and automatic reconnection. Integrate user authentication and session management.

  • WebSocket - 1 hr.

    Integrate a WebSocket API Gateway that maintains persistent sessions and delivers real-time messaging. Handle connect/disconnect events, route by user ID, and apply exponential backoff retries on failure.

  • Database (Conversations & Memory) - 1 hr.

    Design a DynamoDB or Aurora Serverless schema to store turns, embeddings, and agent state. Add TTL for stale data, GSI by user, and memory versioning to manage extended contexts.

  • Facebook Apps (WA + FBM) - 1 hr.

    Configure your Facebook App: register WhatsApp number, long-lived tokens, and webhook verification. Define permissions, roles, and version control for a secure WA and Messenger environment.

  • WhatsApp Business Cloud API - 3 hrs.

    Send and receive messages with the Cloud API: approved templates, interactive messages, media uploads, and session management. Implement HMAC signatures, throughput control, and automate user opt-in.

  • Facebook Messenger API - 2 hrs.

    Integrate the Messenger Graph API: subscribe to page-message events, quick replies, buttons, and attachments. Manage page tokens, webhook verification, rate limits, and 5xx error recovery.

Important

  • Requirements
    The course requires knowledge of Python, AWS, and Terraform to accelerate learning. However, at least 80% of all code is provided.
  • Methodology
    Classes are held online via Google Meet, and Google Classroom is used to manage class materials. Students will have access for up to six months after course completion.
  • Duration
    12 hrs (4 sessions of 3 hours each)
  • Certification
    To earn the certificate, participants must complete all assignments and submit the final project by the specified deadline. A passing rate of at least 90% across assignments and the final project is required.

Instructor

Patricio Cornejo
Patricio Cornejo
AI Researcher & Software Engineer

Instructor with over 10 years of experience in web and mobile platform development. He has led around 35 AI projects in the last 5 years of his career, including chatbots, voicebots, NLP automation, Speech Analytics, and more.

Reviews

4.7
Rating Curso
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USD$112$150
En 14 días!
  • Start At08 jul 2025
  • Slots20
  • Students14
  • Sessions4
  • LevelIntermediate / Advanced
  • LanguageEnglish
  • CertificateSi
  • Approval Percentage90%
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Deploying Agents: Serverless Python, AWS & Terraform | Inteligencia Artificial Chile