コース

Creating scalable AI-powered products and services that generate recurring revenue. Covers productized service design, AI-powered SaaS concepts, building repeatable delivery frameworks, automating fulfillment, pricing models for AI products, customer onboarding automation, quality assurance at scale, and transitioning from custom work to standardized offerings.

Systematically building a personal brand using AI tools for positioning, content creation, and audience growth. Covers brand identity development, AI-assisted content creation across platforms, personal brand architecture, online presence optimization, networking automation, thought leadership content systems, reputation management, and measuring brand equity.

A comprehensive step-by-step system for creating, building, and launching a professional online course using AI tools in just one week. Covers course planning, content creation with AI, video scripting, quiz generation, platform setup, marketing launch, and post-launch optimization. Students will build a real course during the program.

A comprehensive step-by-step system for creating, building, and launching a professional online course using AI tools in just one week. Covers course planning, content creation with AI, video scripting, quiz generation, platform setup, marketing launch, and post-launch optimization. Students will build a real course during the program.

Building a complete AI-powered content production pipeline that transforms a single idea into 50+ content assets across multiple platforms. Covers content strategy architecture, AI prompt engineering for content, batch production workflows, content repurposing systems, quality control processes, and publishing automation. Includes real templates and SOPs.

Replacing messy, manual business processes with structured AI-powered workflow systems. Covers process mapping and audit, identifying automation opportunities, designing AI workflow architectures, implementing with no-code/low-code tools, building feedback loops, measuring ROI, and scaling across departments. Uses real business case studies.

Building a practical, usable AI-powered knowledge management system — not theoretical fluff but an actual working system. Covers personal knowledge architecture, AI-assisted note-taking and tagging, automated knowledge synthesis, retrieval-augmented generation (RAG) basics, building searchable knowledge bases, connecting disparate information sources, and maintaining knowledge freshness.

A comprehensive guide to properly rolling out AI workflows across an enterprise organization. Covers organizational readiness assessment, stakeholder alignment, pilot program design, change management strategies, security and compliance frameworks, integration with existing enterprise systems (ERP, CRM, HRIS), training programs, ROI measurement, and scaling from pilot to full deployment.

Practical AI implementation for operations teams focused on immediate ROI through manual work reduction. Covers identifying high-impact automation targets, document processing automation, reporting and analytics automation, customer communication workflows, inventory and supply chain optimization, HR process automation, and building the business case for each automation.

Repeatable frameworks for automating business processes with AI across organizations of all sizes. Covers the process automation maturity model, AI-ready process identification, automation design patterns, integration architecture, error handling and fallback strategies, compliance and audit trails, cost-benefit analysis, and building an internal automation center of excellence.

Building AI-powered documentation systems that capture, maintain, and distribute organizational knowledge at scale. Covers documentation architecture design, AI-assisted technical writing, automated documentation generation from code and processes, knowledge base management, version control for docs, multi-team documentation standards, search and discovery optimization, and measuring documentation effectiveness.

A practical playbook for implementing AI across a company without chaos, resistance, or wasted investment. Covers AI literacy programs, use case prioritization frameworks, vendor evaluation criteria, pilot-to-production pathways, organizational change management, skills gap analysis, building internal AI champions, governance frameworks, ethical AI guidelines, and measuring adoption success.