RRepoGEO

REPOGEO REPORT · LITE

krishnaik06/The-Grand-Complete-Data-Science-Materials

Default branch main · commit 13c51daa · scanned 5/26/2026, 2:47:52 PM

GitHub: 8,797 stars · 4,437 forks

AI VISIBILITY SCORE
17 /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
1 / 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/The-Grand-Complete-Data-Science-Materials, 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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A comprehensive, free data science learning roadmap with video tutorials and materials covering Python, SQL, Statistics, Machine Learning, and Git for aspiring data scientists.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    data-science, machine-learning, python, sql, statistics, data-analytics, video-tutorials, learning-roadmap, free-course, education
  • mediumreadme#3
    Add an introductory paragraph to the README

    Why:

    CURRENT
    # The Grand Complete Data Science Guide With Videos And Materials
    COPY-PASTE FIX
    # The Grand Complete Data Science Guide With Videos And Materials

This repository provides a complete, free learning roadmap for data science, featuring curated video playlists and materials for Python, SQL, Statistics, Machine Learning, EDA, Feature Engineering, and Git/GitHub. Designed for aspiring data scientists, it centralizes comprehensive resources to guide learners from scratch.

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/The-Grand-Complete-Data-Science-Materials
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DataCamp
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. DataCamp · recommended 2×
  2. Krish Naik · recommended 2×
  3. Coursera · recommended 1×
  4. IBM Data Science Professional Certificate · recommended 1×
  5. Applied Data Science with Python Specialization · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive video tutorials to learn data science from scratch?
    you: not recommended
    AI recommended (in order):
    1. Coursera
    2. IBM Data Science Professional Certificate
    3. Applied Data Science with Python Specialization
    4. edX
    5. Microsoft Professional Program for Data Science
    6. HarvardX Professional Certificate in Data Science
    7. DataCamp
    8. Data Scientist with Python
    9. Data Scientist with R
    10. Udemy
    11. The Complete Python Bootcamp From Zero to Hero in Python
    12. Python for Data Science and Machine Learning Bootcamp
    13. freeCodeCamp.org (freeCodeCamp/freeCodeCamp)
    14. Scientific Computing with Python
    15. Data Analysis with Python
    16. StatQuest with Josh Starmer
    17. Krish Naik
    18. freeCodeCamp.org's YouTube Channel

    AI recommended 18 alternatives but never named krishnaik06/The-Grand-Complete-Data-Science-Materials. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best free resources to master Python and SQL for data analytics?
    you: not recommended
    AI recommended (in order):
    1. DataCamp
    2. Kaggle Learn
    3. Pandas
    4. freeCodeCamp.org
    5. PostgreSQL
    6. SQLZoo
    7. W3Schools
    8. Mode Analytics
    9. Krish Naik

    AI recommended 9 alternatives but never named krishnaik06/The-Grand-Complete-Data-Science-Materials. 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/The-Grand-Complete-Data-Science-Materials?
    pass
    AI did not name krishnaik06/The-Grand-Complete-Data-Science-Materials — 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 krishnaik06/The-Grand-Complete-Data-Science-Materials in production, what risks or prerequisites should they evaluate first?
    pass
    AI named krishnaik06/The-Grand-Complete-Data-Science-Materials 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/The-Grand-Complete-Data-Science-Materials solve, and who is the primary audience?
    pass
    AI did not name krishnaik06/The-Grand-Complete-Data-Science-Materials — 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
  • Prioritized action items8 vs 3 in Lite