Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 8 Minute(s)
Language
English
Taught by
Vivian Aranha, School of AI
Rating
Course Overview
Master API Integration, GraphQL, Observability & AI-Driven Architecture
Welcome to Vibe Coding and Software 3.0, a cutting-edge course that will redefine how you build, scale, and maintain intelligent systems in the age of AI. This isn’t just another programming tutorial—it’s a deep dive into the future of software engineering, where AI-assisted development, specification-driven architecture, and microservices come together to form the foundation of Software 3.0.
In a world where AI tools like ChatGPT, Copilot, and Claude are reshaping how developers write code, manage APIs, and design infrastructure, it’s no longer enough to just “know how to code.” Today’s top engineers must understand how to collaborate with AI, generate code from prompts, build autonomous systems, and orchestrate microservice architectures that are scalable, secure, and observable.
This course introduces you to the Vibe Coding paradigm—a developer workflow that begins with human intent, uses natural language specifications, and leverages AI to scaffold everything from API contracts to documentation. Whether you’re designing a RESTful service, building a GraphQL backend, or deploying to Kubernetes, Vibe Coding enables you to move faster while maintaining clarity, control, and code quality.
You’ll learn how to:
Use AI prompts to generate and test APIs using OpenAPI and GraphQL schemas
Build secure, scalable microservices with AI-guided code generation
Implement best practices in authentication, including API Keys, OAuth2, and JWTs
Leverage AI to auto-document your services with Swagger and context-aware chatbots
Apply Specification-Driven Development (SDD) in embedded, edge, and cloud systems
Monitor performance, detect anomalies, and visualize observability data with OpenTelemetry
Use distributed tracing, root cause analysis, and explainable dashboards powered by AI
Build your own prompt libraries, knowledge graphs, and developer chatbots for ongoing productivity
Deploy production-grade systems across diverse domains like e-commerce, IoT, healthcare, and gaming
By the end of the course, you’ll complete a Capstone Project where you select a real-world use case, define its spec, prompt AI to generate code, build a full-stack system, and present it with documentation and an architecture map. You’ll not only gain technical skills, but also the ability to communicate your systems like a modern software architect.
This course is perfect for software engineers, DevOps professionals, tech leads, and product-minded developers who want to stay ahead of the curve. Whether you're transitioning into AI-powered development or leveling up your microservice architecture game, this course will equip you with the mindset, tools, and hands-on skills to thrive in the AI-first software era.
Are you ready to code with intent, not syntax? To lead in the age of intelligent systems and developer-AI collaboration?
Then welcome to Vibe Coding and Software 3.0—where your specs become software, and your ideas scale with AI.
Course Content
- 9 section(s)
- 42 lecture(s)
- Section 1 Intro to Building AI-Powered Microservices with Vibe Coding & Software 3.0
- Section 2 Module 1: Introduction to Vibe Coding and Software 3.0
- Section 3 Module 2: REST APIs and GraphQL in the Age of AI
- Section 4 Module 3: Building Microservice Architectures with AI
- Section 5 Module 4: Observability and Monitoring in AI Systems
- Section 6 Module 5: Automating Documentation & Prompt Libraries
- Section 7 Module 6: Specification-Driven Development (SDD)
- Section 8 Module 7: Case Studies and Industry Applications
- Section 9 Module 8: Capstone Project – Build Your Vibe-Coded System
What You’ll Learn
- Learn how to write natural language specifications and prompt AI to generate clean, modular, and testable code across services and components.
- Design, containerize, and deploy microservices with secure APIs using OpenAPI, GraphQL, Docker, and Kubernetes, enhanced by AI-assisted code generation.
- Set up distributed tracing, logging, performance monitoring, and root cause analysis using tools like OpenTelemetry, Prometheus, and Grafana.
- Use AI to auto-generate OpenAPI docs, maintain prompt libraries, build knowledge graphs, and even deploy chatbots to support dev teams in real time.
- Analyze and build systems for domains like e-commerce, IoT, healthcare, and gaming—featuring Redis sharding, HIPAA compliance, gRPC, and anti-corruption layers.
- Communicate your technical decisions with clarity, using visual architecture diagrams, AI-generated docs, and structured walkthroughs.
Skills covered in this course
Reviews
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AAnkit kumar
grate session thank you.
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LLeo
Great content. Thanks.
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AAnkit Jha
It's a great course on learning what AI is capable of when meeting with human intelligence it is like writing the world by mind.Generate a course on real time coding also with AI from docs to build and ship a great system. Having some idea ready to collaborate.
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MMark Pee
I thought it was pratical
