The course
"Integration of AI into Cloud Services" is dedicated to the practical implementation of modern AI models into real applications using cloud infrastructure.
Instead of complicated local model setup, you will learn to work with ready-made AI services available through APIs and automatically scalable. This approach allows for rapid prototyping and bringing solutions to production without the need to manage infrastructure and expensive equipment.
What You Will Learn
The course provides a systematic understanding of how cloud AI integrations are structured:
- Why cloud AI models are often preferable to local solutions
- How the pay-as-you-go model and AI service scaling work
- Overview of the ecosystem of cloud providers and models
- Principles of working with API of language models
- Differences between models (including reasoning models and standard LLM)
- Basics of prompt engineering and model behavior adjustment
Practical Part
The course is practice-oriented for a quick start:
- Working with playground tools for model testing
- Using the GitHub Models platform to compare models
- Analyzing differences in responses from different LLM
- Integrating AI into an application using Python
- Connecting models through APIs (with the ability to adapt to different providers)
You will also learn how to:
- Select an appropriate model for the task
- Test a hypothesis without costs
- Transition from experiment to production solution
Key Idea of the Course
The main focus is on a
vendor-agnostic approach: you will learn to work with AI models regardless of the provider (be it OpenAI, Microsoft Azure, or others), understanding the general principles of integration.
Who This Course is For
- Developers who want to integrate AI into products
- Startups and teams building MVPs using AI
- Engineers working with APIs and cloud infrastructure
- Anyone who wants to quickly move from an idea to a working AI application
Outcome
After completing the course, you will:
- Be able to integrate cloud AI models into your applications
- Learn to test and compare different LLM
- Understand how to choose the appropriate service for the task
- Create a foundation for scalable AI solutions
