RRepoGEO

REPOGEO REPORT · LITE

dswh/ai-engineer-roadmap

Default branch main · commit bb2d7137 · scanned 6/6/2026, 9:43:04 PM

GitHub: 644 stars · 113 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface dswh/ai-engineer-roadmap, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-engineer, roadmap, learning-path, llm, rag, llmops, machine-learning, deep-learning, career-path, skills
  • highreadme#2
    Strengthen the README's opening statement to clarify its purpose as a structured learning roadmap

    Why:

    CURRENT
    The AI Engineering Roadmap categorizes the journey into 3 stages:
    COPY-PASTE FIX
    This repository provides a comprehensive, structured **AI Engineering Roadmap** designed to guide aspiring and current AI engineers through essential skills, learning resources, and practical tools. It categorizes the journey into 3 stages:
  • mediumreadme#3
    Add a sentence highlighting the YouTube-guided execution as a key differentiator

    Why:

    COPY-PASTE FIX
    Unlike many static guides, this roadmap comes alive with a complete, end-to-end execution available on the accompanying YouTube playlist, allowing you to build projects and functional products alongside the creator.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface dswh/ai-engineer-roadmap
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Jupyter Notebooks
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Jupyter Notebooks · recommended 1×
  2. Google Colab · recommended 1×
  3. NumPy · recommended 1×
  4. Pandas · recommended 1×
  5. Scikit-learn · recommended 1×
  • CATEGORY QUERY
    What skills and learning path are essential for becoming a successful AI engineer?
    you: not recommended
    AI recommended (in order):
    1. Jupyter Notebooks
    2. Google Colab
    3. NumPy
    4. Pandas
    5. Scikit-learn
    6. XGBoost
    7. LightGBM
    8. CatBoost
    9. TensorFlow
    10. Keras
    11. PyTorch
    12. Hugging Face Transformers
    13. Git
    14. GitHub
    15. Docker
    16. AWS SageMaker
    17. Google Cloud AI Platform
    18. Azure Machine Learning
    19. MLflow
    20. Kubeflow
    21. NLTK
    22. spaCy
    23. OpenCV
    24. OpenAI Gym
    25. Stable Baselines3
    26. Kaggle

    AI recommended 26 alternatives but never named dswh/ai-engineer-roadmap. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a comprehensive guide to building advanced LLM applications, including RAG and LLMOps.
    you: not recommended
    AI recommended (in order):
    1. Building LLM-Powered Applications by Google Cloud
    2. Generative AI with Large Language Models by DeepLearning.AI
    3. LLMOps: From Prompt to Production by DataCamp
    4. Practical LLM Applications by Full Stack Deep Learning
    5. Designing and Building LLM-Powered Applications by NVIDIA
    6. The LLM Handbook
    7. LLM University by Cohere

    AI recommended 7 alternatives but never named dswh/ai-engineer-roadmap. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of dswh/ai-engineer-roadmap?
    pass
    AI did not name dswh/ai-engineer-roadmap — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts dswh/ai-engineer-roadmap in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dswh/ai-engineer-roadmap explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo dswh/ai-engineer-roadmap solve, and who is the primary audience?
    pass
    AI named dswh/ai-engineer-roadmap explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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