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1
Before we get started
Introduction to the course concept and how it will be structured.
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2
Setting Up Your Platform Prereqs
Developing the framework to iterate on your platforms, selecting a tech & productivity stack.
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3
Prompt Engineering
Learn effective prompt engineering techniques for building AI platforms.
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4
Multilayered Architectures
Explore complex system architectures with multiple layers for building robust AI platforms.
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5
Recap: Modules 1-4
A comprehensive review of the foundational concepts: course introduction, platform prerequisites, prompt engineering, and multilayered architectures.
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6
CRUD, Transformations, & Parsing
Understand data operations, transformations, and parsing techniques essential for AI platform development.
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7
AI-Rep Architecture In-Depth
Deep dive into AI-Rep architecture patterns and how to implement them in your platforms.
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8
Building Your Own Architecture / Compounding Transformations
Learn to design and build custom architectures by compounding transformations for complex AI systems.
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9
Real-World Application: PLATO5 Planning
Apply learned concepts to a real-world case study: planning PLATO5's rebuild.
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10
Recap: Modules 6-10
A comprehensive review of data operations, AI-Rep patterns, custom architectures, and PLATO5 planning.
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11
In-Depth Look: Emstrata's Architecture
Explore the architecture behind Emstrata, a platform for creating immersive narrative experiences using AI to generate emergent storylines.
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12
Architecting Lore Builder System for Emstrata
Learn how to design and build a lore builder system for narrative platforms, using Emstrata as a case study.
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13
Notes on Platform Design & Design Language
Learn about platform design principles and developing a cohesive design language for AI-powered applications.
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14
Considering Use-Cases, Demographics, & Markets
Explore how to identify use-cases, understand target demographics, and evaluate market opportunities for AI platforms.
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15
Messaging About Novel Products/Services
Learn how to effectively communicate and market innovative AI products and services to your target audience.
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16
Recap: Modules 11-16
A comprehensive review of real-world architectures, lore builder systems, platform design, market considerations, and messaging.
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17
Deployment & Distribution - Web, Mobile, & API Hosting & Storage
Learn how to deploy and distribute your platform: hosting APIs, deploying web apps, publishing to app stores, and storing multimedia content.
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18
Integrating Other AI Services
Learn how to integrate additional AI capabilities including TTS, image generation, video generation, and other AI algorithms into your platform.
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19
Securing AI Pipelines Against Hallucination
Strategies and techniques for preventing, detecting, and handling AI hallucinations to ensure reliable and trustworthy outputs.
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20
New Update on PLATO5's Rebuild
Latest progress update on the PLATO5 rebuild, covering recent developments, challenges overcome, and architectural refinements.
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21
Recap: Modules 17-21
A comprehensive review of deployment, AI service integration, security, and PLATO5 rebuild progress.
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22
Ethical AI Usage & Examples of Pitfalls
Learn about ethical considerations in AI development, including privacy concerns, disclosing AI usage, and common pitfalls to avoid when building AI platforms.
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23
Retaining Your AI Outputs for Future Training
Strategies for storing and managing AI-generated outputs to enable future model training, fine-tuning, and continuous improvement of your platform.
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Things that go Unconsidered
Critical but often overlooked aspects of platform development including Terms of Service, session logic, data retention policies, and other essential considerations.
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Building An Audience for your platform
Strategies for growing and engaging an audience for your AI platform, from early adopters to broader market reach.
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Recap: Modules 22-26
A comprehensive review of ethical AI usage, retaining outputs, overlooked considerations, and audience building.
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27
Onboarding Users
Design effective user onboarding experiences that help users understand and successfully use your AI platform's capabilities.
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28
Wrap-Up: Building AI Platforms from Scratch
Final thoughts and key takeaways from the course, summarizing the journey from foundational concepts to building complete AI platforms.