• views: 137
• date: 1 October 2025
• posted by: 0nelove

Learn REST APIs, AI Integrations, Agentic Workflows & Real Use Cases — Hands-On with Flask, FastAPI, Hugging Face, Rasa
What you'll learn
Build and test REST APIs with Python (Flask & FastAPI)
Integrate AI models (Hugging Face, SpaCy, BERT) into real applications
Design AI-to-AI (A2A) protocols and workflows that connect multiple AI services
Automate customer feedback handling with sentiment analysis + CRM + Slack
Classify and route emails using AI email pipelines (Gmail/SendGrid APIs)
Power chatbots & voice assistants with intent detection (Rasa, Dialogflow)
Implement event-driven AI workflows using Kafka or Redis
Apply best practices for error handling, resilience, and scalability
Understand Agentic AI and how to simulate decision-making agents
Build end-to-end mini projects to showcase your skills in real-world use cases
Requirements
Basic knowledge of Python programming (variables, functions, loops)
Familiarity with using the command line / terminal
Curiosity to learn how APIs and AI systems connect
No prior AI or API experience is required — we'll build everything step by step
A computer with internet access (Windows/Mac/Linux)
Description
Are you ready to move beyond toy AI projects and build real systems where Artificial Intelligence communicates with other systems, services, and even other AIs? If so, this course is designed for you.This is a hands-on, project-driven journey into the world of AI-to-AI (A2A) protocols, REST APIs, and event-driven workflows that form the backbone of modern intelligent applications. Instead of just theory, you'll gain practical coding experience by building APIs, integrating machine learning models, and designing workflows that can operate in real-world business environments.We'll begin by mastering the fundamentals of REST APIs — understanding HTTP methods, JSON data exchange, and building your first API with Flask or FastAPI. From there, we'll bring APIs to life by integrating Hugging Face models for sentiment analysis, testing endpoints with Postman or Curl, and deploying them for practical use.Next, you'll dive into real-world use cases:Automating customer feedback escalation by detecting negative sentiment, creating CRM tickets, and sending Slack alerts.Classifying and routing emails using SpaCy or BERT, then forwarding them with Gmail or SendGrid.Powering chatbots and voice assistants with intent detection using Rasa or Dialogflow, and triggering external APIs in response.We'll also explore the exciting frontier of Agentic AI and event-driven architectures, where AI agents can make decisions, trigger tasks, and coordinate across systems using tools like Kafka or Redis.Each section includes hands-on labs, mini-projects, and quizzes to reinforce learning. Videos are concise (≤10 minutes), making it easy to progress in focused sprints.By the end, you'll have the confidence to design, build, and deploy scalable AI-powered systems that go beyond experiments — into production-ready reality.
Who this course is for
Developers who want to integrate AI into real-world workflows
Data scientists & ML engineers who want to deploy their models via APIs
AI/ML enthusiasts curious about how AI systems talk to each other
Backend engineers exploring AI-powered microservices and event-driven systems
Students & professionals preparing for careers in AI systems engineering, MLOps, or AI product development
Anyone who prefers hands-on, project-based learning rather than just theory




   
   
   

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