What you’ll learn
- Build a personal, neural-search-enabled Knowledge Management (PKM) system using AI-driven toolsets (e.g., Notion AI, Obsidian, NotebookLM).
- Automate content ingestion, tagging, cross-referencing, and semantic retrieval across personal archives.
- Synthesize years of accumulated project documentation into actionable strategic insights within seconds.
How the course runs
Before the session
Pre-session prep · about 30 minutes
Audit and organize personal local drive archives, notes, and research repositories.
Live session
Instructor-led · 2 hours
2-hour technical integration session configuring local/cloud neural search engines.
After the session
Practice & reinforcement
Query personal knowledge engine to draft a retrospective strategy paper based on legacy project files.
Course modules
Principles of Semantic & Neural Search
Vector embeddings vs. keyword searching.
PKM System Architecture
Indexing local files, cloud folders, and web clips into a unified AI-accessible vault.
Retrieval Augmented Generation (RAG) for Individuals
Combining personal knowledge vaults with enterprise LLMs.
Continuous Knowledge Maintenance
Automated tagging, periodic summary routines, and dead-link pruning.
What you’ll take away
Deliverable: A fully configured personal AI Knowledge Base indexing key professional archives.
How your learning is checked: Live demonstration of instant semantic retrieval across complex historical project datasets.