01
Curated roadmap
What to learn first, what to postpone, and which materials fit business, builder and engineering goals.
AI IMPLEMENTATION NAVIGATOR
From AI basics to RAG, agents and production — in the right order
A curated learning and implementation system for people who do not want 100 random bookmarks. You get three learning tracks, a 9-module roadmap, original implementation templates, practical assignments and a verified catalogue of external resources.
WHAT YOU BUY
The external courses stay free. You pay for the system around them
02
Implementation workbook
Use-case scoring, prompt canvas, RAG canvas, agent design, evaluation scorecard, security checklist, pilot plan and ROI framework.
03
Bilingual package
Russian and English Navigator editions plus an editable implementation workbook for practical use.
This product does not sell access to Microsoft, OpenAI, Hugging Face, Anthropic, Google, LangChain or independent authors' courses. Those resources remain on their original websites. The $39 price is for Denis Mironov's curation, sequencing, original explanations, exercises, templates and update framework.
CHOOSE YOUR DEPTH
One Navigator, three routes
01
Business / no-code
4-week recommended path
AI literacy, prompting, workflow design, use-case selection, governance and pilot planning. Coding is optional.
02
Builder
8-week recommended path
APIs, RAG, tools, agent patterns, LangGraph, evaluations and two working prototypes. Basic Python or TypeScript helps.
03
Engineer
12+ week deep path
Transformers, datasets, fine-tuning, reasoning models, observability, deployment and production agent architecture.
THE ROADMAP
9 modules from understanding to implementation
01
AI foundations
Understand LLMs, model selection, responsible AI, token/context basics and where generative AI actually creates business value.
02
Prompt & context engineering
Move from ad-hoc prompts to repeatable prompt structures, context design, structured outputs and evaluation criteria.
03
APIs, tools & structured workflows
Build workflows that call models, tools and APIs predictably instead of relying on a single chat window.
04
RAG & business knowledge
Design retrieval pipelines, chunking, embeddings, vector search, grounding, citations and document-quality controls.
05
AI agents
Learn tool use, memory, planning, multi-agent patterns, human approval and when an agent is actually justified.
06
Build real projects
Use open-source examples as references to build your own support, research, operations or internal productivity systems.
07
Evaluation & observability
Test quality before launch, trace failures, create datasets, measure regressions and monitor production behaviour.
08
Production & deployment
Security, permissions, cost control, Docker/API deployment, monitoring, fallback logic and change management.
09
Business implementation
Score use cases, estimate ROI, define owners, set approval rules, launch a pilot and convert it into a repeatable operating process.
ORIGINAL TOOLS INCLUDED
Turn learning into an implementation plan
A
AI Use-Case Scorecard
Score impact, frequency, data readiness, risk, integration effort and time-to-value before you build.
B
Prompt & Context Canvas
Define role, task, context, constraints, tools, output schema and evaluation criteria.
C
RAG Design Canvas
Map source data, ingestion, chunking, retrieval, grounding, permissions and freshness.
D
Agent Design Canvas
Goal, tools, memory, permissions, human approval, failure states, budget and stop conditions.
E
Evaluation Scorecard
Quality, groundedness, task completion, latency, cost, safety and regression checks.
F
Pilot → Production Checklist
Owner, scope, baseline, launch criteria, access controls, monitoring, fallback and rollout plan.
CORE VERIFIED RESOURCES
Start here — official and high-value learning sources
The Navigator gives you the order and assignments. These links remain external and are periodically re-checked.
01
Microsoft — Generative AI for Beginners
21-lesson foundation course with Python/TypeScript examples.
Open original source ↗02
Microsoft — AI Agents for Beginners
18 lessons focused on building AI agents.
Open original source ↗03
Hugging Face — Agents Course
Free four-unit agents course with practical assignments.
Open original source ↗04
Hugging Face — LLM Course
Free LLM/NLP course covering Transformers, datasets, fine-tuning and reasoning-model topics.
Open original source ↗05
Anthropic — Courses
Five educational tracks: API fundamentals, prompting, real-world prompting, evaluations and tool use.
Open original source ↗06
DAIR.AI — Prompt Engineering Guide
Reference guide for prompting techniques, RAG, agents and related research.
Open original source ↗07
OpenAI Academy — Courses
Practical learning paths for applying AI, building with AI and leading AI adoption.
Open original source ↗08
Google Skills — Introduction to Generative AI
Short introductory course on generative AI concepts and Google tooling.
Open original source ↗09
LangChain Academy — Introduction to LangGraph
Free foundation course on graph-based agent workflows, state, memory and human-in-the-loop.
Open original source ↗10
LangChain Academy — LangSmith Essentials
Free course on tracing, evaluation, deployment and production monitoring.
Open original source ↗11
Maxime Labonne — LLM Course
Free roadmap across LLM fundamentals, LLM Scientist and LLM Engineer tracks.
Open original source ↗12
Awesome LLM Apps
100+ open-source AI agents, agent skills and RAG applications for implementation references.
Open original source ↗13
500+ AI Agents Projects
Large catalogue of AI-agent use cases and working implementation references.
Open original source ↗REFERENCE-ONLY SOURCES
Useful, but not bundled into the paid product
R1
E2B — Awesome AI Agents
Useful landscape reference. Its repository uses a Creative Commons NonCommercial license, so this Navigator links to it but does not redistribute or package its content.
Open external reference ↗R2
Nir Diamant — GenAI Agents
Useful external tutorial library. The repository states a custom non-commercial license; materials are not copied into this paid product.
Open external reference ↗R3
Nir Diamant — Agents Towards Production
Production-oriented external reference. The repository states a custom non-commercial license; materials are not redistributed here.
Open external reference ↗DELIVERABLE
What arrives after payment
$39
- AI Implementation Navigator — Russian edition
- AI Implementation Navigator — English edition
- Editable AI Implementation Workbook — RU/EN
- Three study tracks: Business / Builder / Engineer
- Original assignments and implementation templates
- Source and licence notes with direct links
- Version date so you can see when the external catalogue was last reviewed
IMPORTANT
Transparent boundaries
Is this an original video course?
No. It is a paid learning-and-implementation Navigator built around original curation, sequencing, explanations, exercises and templates, with links to external courses and repositories.
Do I need to know how to code?
No for the Business route. The Builder and Engineer routes increasingly use Python, TypeScript, APIs and developer tooling.
Are all linked courses guaranteed to remain free forever?
No. External owners can change pricing, access rules, content, licences or URLs. The package records a verification date and links to the original source so changes can be checked directly.
Can I use the linked repositories commercially?
That depends on each repository's current licence and your intended use. The Navigator does not grant third-party rights. Always check the original licence before copying, modifying or distributing third-party code or materials.