RRepoGEO

REPOGEO REPORT · LITE

krishnaik06/AI-Engineer-Roadmap-2024

Default branch main · commit 5e9e37b8 · scanned 6/16/2026, 7:33:40 AM

GitHub: 971 stars · 312 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 krishnaik06/AI-Engineer-Roadmap-2024, 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

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

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A comprehensive, structured learning roadmap for aspiring AI Engineers in 2024, covering Python, statistics, machine learning, LLMs, and MLOps with curated resources.
  • mediumreadme#2
    Add an introductory paragraph to the README

    Why:

    CURRENT
    The content immediately following # AI Engineer Roadmap 2024 is ## What Does An AI Engineer Do?
    COPY-PASTE FIX
    Add the following paragraph directly after # AI Engineer Roadmap 2024: "This repository provides a comprehensive and structured learning roadmap for aspiring AI Engineers in 2024. It guides you through the essential skills, technologies, and concepts required to excel in the rapidly evolving field of AI engineering, from foundational programming and statistics to advanced topics like Large Language Models (LLMs) and MLOps."

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 krishnaik06/AI-Engineer-Roadmap-2024
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Automate the Boring Stuff with Python
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Automate the Boring Stuff with Python · recommended 2×
  2. pandas-dev/pandas · recommended 2×
  3. Git · recommended 2×
  4. Python for Everybody (PY4E) by Dr. Charles Severance · recommended 1×
  5. 3Blue1Brown's Essence of Linear Algebra and Essence of Calculus · recommended 1×
  • CATEGORY QUERY
    Looking for a structured learning path to become an AI engineer this year.
    you: not recommended
    AI recommended (in order):
    1. Automate the Boring Stuff with Python
    2. Python for Everybody (PY4E) by Dr. Charles Severance
    3. 3Blue1Brown's Essence of Linear Algebra and Essence of Calculus
    4. Khan Academy's Linear Algebra and Calculus courses
    5. Machine Learning by Andrew Ng
    6. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron
    7. scikit-learn (scikit-learn/scikit-learn)
    8. NumPy (numpy/numpy)
    9. Pandas (pandas-dev/pandas)
    10. TensorFlow (tensorflow/tensorflow)
    11. Keras (keras-team/keras)
    12. PyTorch (pytorch/pytorch)
    13. fast.ai's Practical Deep Learning for Coders
    14. Deep Learning Specialization by Andrew Ng
    15. Hugging Face Transformers library (huggingface/transformers)
    16. Natural Language Processing Specialization by deeplearning.ai
    17. OpenCV (opencv/opencv)
    18. Practical Deep Learning for Coders (fast.ai)
    19. Reinforcement Learning Specialization by University of Alberta
    20. Docker
    21. AWS SageMaker
    22. Google Cloud AI Platform / Vertex AI
    23. Azure Machine Learning
    24. Git
    25. GitHub
    26. Kaggle

    AI recommended 26 alternatives but never named krishnaik06/AI-Engineer-Roadmap-2024. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What foundational programming and statistical knowledge is required for AI engineering?
    you: not recommended
    AI recommended (in order):
    1. Python
    2. Automate the Boring Stuff with Python
    3. Python Crash Course
    4. Python for Data Analysis
    5. Pandas (pandas-dev/pandas)
    6. Cracking the Coding Interview
    7. Introduction to Algorithms
    8. LeetCode
    9. HackerRank
    10. Git
    11. Pro Git
    12. GitHub Docs
    13. Atlassian Git Tutorial
    14. The Linux Command Line
    15. Codecademy
    16. SQL
    17. SQL for Data Analysis
    18. SQL Practice Problems
    19. Mode Analytics
    20. A First Course in Probability
    21. Practical Statistics for Data Scientists
    22. Khan Academy
    23. StatQuest with Josh Starmer
    24. Naked Statistics: Stripping the Dread from the Data
    25. Statistics by James McClave and Terry Sincich
    26. Introduction to Linear Algebra by Gilbert Strang
    27. MIT OpenCourseware
    28. 3Blue1Brown
    29. Calculus: Early Transcendentals by James Stewart
    30. Calculus for Machine Learning by Jason Brownlee
    31. Machine Learning Mastery

    AI recommended 31 alternatives but never named krishnaik06/AI-Engineer-Roadmap-2024. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 krishnaik06/AI-Engineer-Roadmap-2024?
    pass
    AI named krishnaik06/AI-Engineer-Roadmap-2024 explicitly

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

  • If a team adopts krishnaik06/AI-Engineer-Roadmap-2024 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named krishnaik06/AI-Engineer-Roadmap-2024 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 krishnaik06/AI-Engineer-Roadmap-2024 solve, and who is the primary audience?
    pass
    AI did not name krishnaik06/AI-Engineer-Roadmap-2024 — 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?

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
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