AI School Curriculum
A comprehensive learning journey from AI fundamentals to advanced concepts
Featured Courses
Course Modules:
Course Modules:
Course Modules
Foundations of AI Ethics
Understand the fundamental ethical principles in AI.
Bias and Fairness in AI Systems
Learn to identify and mitigate bias in AI systems.
Responsible AI Development Practices
Implement responsible practices in AI development.
Course Modules
AI Business Strategy
Develop strategies for integrating AI into business operations.
AI for Customer Experience
Enhance customer experience using AI technologies.
AI for Process Optimization
Optimize business processes with AI automation.
AI for Decision Making
Leverage AI for data-driven decision making.
Building an AI-Ready Organization
Prepare your organization for AI adoption.
AI Implementation and ROI
Measure the impact and return on investment of AI initiatives.
Course Modules
Introduction to AI and Essential Tools
This chapter introduces fundamental AI concepts and explores key resources like Hugging Face, OpenAI, and Claude. You'll learn how to navigate these platforms and understand their capabilities for no-code development. We will also cover basic computer and browser usage relevant to AI tools.
Practical Applications and Automation
This chapter delves into practical AI applications, including content creation, task automation, and building simple AI-powered tools using platforms like Together AI, LiteLLM, and others. We will cover examples and exercises to solidify your understanding.
No-Code Full-Stack App Development with AI
In this chapter, you'll learn how to leverage no-code platforms and AI tools to build basic full-stack applications. We'll explore resources like Open Router, Ollama, Cursor, DataButton, and others, focusing on practical examples and projects. We'll also touch on AI-assisted coding tools like Copilot and Roo Code.
Course Modules
Mastering AI APIs: Hugging Face, OpenAI, and Beyond
This chapter dives into the world of AI APIs, focusing on practical applications and integration into real-world scenarios. We'll explore leading AI platforms like Hugging Face, OpenAI, and Claude, and develop a solid practice for utilization. Mastering AI APIs is crucial for building sophisticated AI-powered applications without needing to understand complex algorithms.
No-Code AI Application Development
Discover how to build functional AI applications without writing code. We'll cover tools and techniques for creating prototypes and production-ready applications using no-code platforms and AI APIs.
AI-Powered Content Creation and Automation
Learn to leverage AI for content creation, automating tasks such as writing, image generation, and data analysis. Explore ethical considerations and best practices for AI-generated content.
Advanced AI Tool Integration: Combining Services
This chapter delves into integrating various AI services (e.g., Together AI, LiteLLM, Open Router, Ollama, Cursor, DataButton, MCP servers, Copilot, Roo Code) to create powerful and sophisticated AI workflows.
Building Your Own AI Company Infrastructure
Learn how to set up your own Virtual Private Server using Ollama, Open Router, and LiteLLM. Manage and run your models, integrate multiple API keys (over 100), and build your own AI company interface for complete control.
Course Modules
Designing and Architecting No-Code AI Systems
Learn strategic planning and architecture of full-stack AI applications using a no-code approach.
Integrating AI Services and APIs
Learn to integrate various AI services like OpenAI, Hugging Face, and Gemini AI Studio into your no-code applications.
Building the Frontend and Backend with No-Code Tools
Learn to create user interfaces, handle data flow, and connect frontend and backend components.
Deployment, Monitoring, and Monetization
Learn about deploying your completed AI application, monitoring its performance, and strategies for monetization.
Course Modules
Advanced Deployment with Google AI Platform & Firebase
This chapter details the process of deploying a full-stack AI application using Google AI Studio and Vertex AI for model training and hosting. We integrate Firebase Realtime Database and Storage for data persistence and user content management. We'll cover setting up database schemas and security rules.
Firebase Authentication & Security Rules
This chapter focuses on user authentication using Firebase Authentication. We'll implement secure authentication flows and configure Firebase Security Rules to protect the database and storage from unauthorized access. This will also include detailed error handling and best practice implementation.
Debugging and Testing AI Applications
This chapter addresses common deployment and runtime errors encountered while integrating AI models and Firebase services. We'll discuss effective debugging strategies, including testing methodologies and tools for identifying and resolving issues. This will also include discussion of monitoring AI models and integrating logging.
Learning Path Progression
Advanced Student plan required
Advanced Student plan required