Ree Technica

GenAI Foundation + Advanced

Upskill with modern GenAI to learn faster, create better, and build real income-ready outputs — research, content, video, and automations.

For everyone — learn GenAI that helps you create, earn, and ship portfolio‑ready work.

Learn • Create • Automate • Portfolio‑ready outcomes
Explore program
GenAI course visual
Outcomes

What you’ll actually produce — not just “learn”.

Foundation is demo-first. Advanced adds automation depth, open-weight local AI, coding agents, and MCP awareness.

Foundation outcomes
  • Study + productivity system (notes → quizzes → revision plan)
  • Research report with citations + source grounding
  • Creator portfolio: images + short videos + edits
  • AI avatar presenter videos (shareable, multilingual)
  • 3 mini‑projects + 1 capstone demo
Advanced outcomes
  • 3 real automations + one agentic workflow
  • Local/open‑weight model setup + safe usage
  • Coding agents used responsibly (plan → edit → review)
  • Intro to MCP + security awareness
  • One assistant workflow design doc
Curriculum

Modules that build real skills — study, creation, and automation.

Foundation builds daily‑use GenAI skills for learning and creation. Advanced adds automation, local/open models, coding agents, and MCP awareness for serious learners.

Track 1

Foundation (Days 1–30)

Productivity + research + creator stack + starter automation.
What you’ll learn
  • LLM basics: tokens, context window, temperature/top‑p, hallucinations (with demos)
  • LLM vs Search vs RAG: a simple decision framework
  • Prompt injection awareness + safe prompting habits
  • Prompt structure: instruction hierarchy, constraints, examples (few‑shot)
  • Study OS: revision prompts, flashcards, weekly timetable
Tools
  • ChatGPT / Claude / Gemini (mobile + desktop flows)
  • Voice input workflows (phone-first)
  • Quality checklist: verify, cite, and summarize
Deliverable
  • Personal Study OS template (notes → quiz → revision plan)
  • 1 topic: notes + quiz + 60‑sec explanation script
What you’ll learn
  • Role / Task / Context formatting for consistent results
  • Prompt patterns: critique→rewrite, decomposition, verify‑then‑write
  • Rubrics, checklists, tables, and structured outputs
  • Building prompt libraries (reusable templates)
Tools
  • Prompt template packs (student + creator)
  • Output formats: tables, checklists, rubrics
  • Quality controls: constraints + examples
Deliverable
  • Mini‑project #1: one topic → notes + quiz + 60‑sec explainer
  • Reusable prompt pack you can keep using
What you’ll learn
  • Research workflow: compare sources, extract claims, cite properly
  • Grounded writing: outline → report → summary → viva Q&A
  • Mind maps + study guides + “teach me” mode
  • Academic honesty: how to use AI without copying
Tools
  • Perplexity for research + citations
  • NotebookLM for “your documents only” learning
  • Citations + bibliography basics
Deliverable
  • Mini‑project #2: research report + citations
  • 10 viva questions + 1‑page summary
What you’ll learn
  • Image generation: styles, references, consistency
  • Short video creation: prompts, clips, consistency techniques
  • Video enhancement: upscale/denoise/sharpen workflow
  • Editing pipeline: captions, hooks, pacing (CapCut/DaVinci style)
  • Avatar presenter videos: multilingual variants + voice layer
Tools
  • Image: Midjourney / Stability (optional)
  • Video: Runway / Luma / Sora (demo-friendly)
  • Avatars: HeyGen (presenter videos)
Deliverable
  • Mini‑project #3: 1 poster + 1 reel + 1 avatar presenter
  • Creator portfolio starter pack
What you’ll learn
  • Automation basics: triggers/actions, filters, routers
  • Forms → Sheets → AI summary → WhatsApp/Email reply flow
  • Content calendar: ideas → scripts → review → schedule
  • Safety: approvals, privacy, human‑in‑the‑loop
Tools
  • No‑code automation tools (workflow mindset)
  • LLM summaries + response drafting
  • Basic logging + error awareness
Deliverable
  • 2 starter automations you can demo
  • Automation checklist: privacy + approvals
What you’ll learn
  • Capstone planning + rubric
  • Build day + instructor review loop
  • Demo day: storytelling, before/after, outcomes
  • Portfolio packaging: 1‑page PDF + 60‑sec demo video
Tools
  • Templates: capstone rubric + portfolio pack
  • Presentation prompts + demo scripts
  • Asset checklist for GitHub/Drive
Deliverable
  • Choose 1: Student Success Pack / Creator Pack / Local Business Pack
  • Capstone demo + portfolio bundle
Track 2

Advanced (Days 31–40)

Automation depth + local AI + coding agents + MCP awareness.
What you’ll learn
  • Advanced automation patterns: retries, error handling, logging
  • Agents vs automations: when agents help vs when simpler is safer
  • Human approvals + data boundaries
  • Build: lead → qualify → reply draft → CRM → daily report
Tools
  • Automation platforms + agent features (where available)
  • Structured prompts + validation checks
  • Audit trail mindset
Deliverable
  • 3 real automations + 1 agentic workflow design
  • Approvals + safety checklist
What you’ll learn
  • When to use local models (privacy, cost, offline)
  • Local model setup (LM Studio / Ollama) concepts
  • Safety: don’t expose local servers; basic risk awareness
  • Prompting differences: smaller models, smaller context
Tools
  • Open‑weight ecosystem (Hugging Face)
  • Model families (Meta / Mistral / Qwen / DeepSeek)
  • Local runners (LM Studio / Ollama)
Deliverable
  • Local model runbook (setup + safety checklist)
  • One private workflow demo (offline summarizer / Q&A)
What you’ll learn
  • Agent workflow: task plan → file edits → tests → review loop
  • Permissions + “least privilege” for code changes
  • Prompt injection risks in repos + safe review discipline
  • Light API build: simple endpoint + validation
Tools
  • Claude Code / coding assistants (workflow‑first)
  • Git + review checklist
  • Optional sandbox (Replit / local editor)
Deliverable
  • 1 small app upgrade using an agent (with review notes)
  • Repo checklist: permissions + review + tests
What you’ll learn
  • MCP concept: standard connector for tools + data access
  • Where it fits: after automation + agents + local models
  • Security awareness: approvals, scope, misconfig risks
  • Design thinking: what data, what tools, what guardrails
Tools
  • MCP concepts + examples (no deep coding required)
  • Threat model basics (prompt injection + tool abuse)
  • Approval workflows
Deliverable
  • Assistant workflow design doc (data access + tools + approvals)
  • Security checklist for tool-connected assistants
Next step

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