Code for Data Science ✓
Subscribers
27
🔥 Buzz rank
#75,101 ▼33795
Total Views
796
Videos
44
Channel age
2 yrs
💰 Suggested sponsorship rate
$40 – $65 / integration
Estimated from audience size & typical reach — every deal is negotiable and held in SocialDB escrow.
~18
views / video
Known for
76 views
Contingency Tables | Full Course On Statistics for Data Science with Python.
49 views
Probability Density Function | Full Course On Statistics for Data Science with Python.
46 views
Prediction: Categorical Variables | Full Course On Statistics for Data Science with Python.
41 views
Why Data Science? | Full Course On Statistics for Data Science with Python.
▶️ Featured Video
76 views📈 Performance
Typical video
9–21 views
Median 12 — the reliable floor a brand can expect, not just the headline average.
Upload rhythm
0.5× / week
Most active on Saturdays — consistent output keeps an engaged, sponsor-ready audience.
18
Avg views / video
1
Avg likes
0
Avg comments
7.79%
Engagement rate
0.5
Uploads / week
18
Lifetime avg / video
29
Views / subscriber
0%
Shorts (recent views)
Engagement rate = (likes + comments) ÷ views across recent videos.
💡 Did you know?
🗓️Joined YouTube in 2024 — 2 years ago.
🏆Ranked #24,694 among all influencers on SocialDB.
🎯Top Technology influencer — #5,671 in the niche.
👁️Averages 18 views per video.
📤Posts about 0.5× per week.
💬7.79% engagement rate.
🚀Gained 1 subscribers in the last 7 days.
🛡️ Audience credibility
90/100
Excellent
- Est. 93% real, active audience · Low fake-follower risk.
- Healthy view-through — roughly 67% of subscribers watch each video.
- 7.79% engagement — above the ~5% typical for this size.
Est. authentic audience
93%
Fake-follower risk
Low
Heuristic estimate from view-through, engagement vs size and recent growth — a screening signal, not a guarantee.
👥 Audience demographics
EstimatedModeled from this creator's niche, platform & region — a planning estimate, not connected analytics.
Gender split
Male 76% Female 24%
Age · peak 25-34
13-179%
18-2428%
25-3432%
35-4417%
45+14%
Top geographies
- United States34%
- India11%
- United Kingdom8%
- Brazil6%
- Indonesia5%
Likely interests
TechnologyGadgetsSoftwareGaming
💚 Brand affinity
EstimatedBrands Code for Data Science's audience is most likely to respond to — from detected sponsorships in this niche.
Amazon Affiliate
Shopify
About
This channel belongs to the "Statistics for Data Scientists" course on Udemy.
Here I will upload all of the coding videos where I explain each line of Python code in detail.
For more information and context about the code discussed here, visit the course webpage:
Happy Learning! :)
Here I will upload all of the coding videos where I explain each line of Python code in detail.
For more information and context about the code discussed here, visit the course webpage:
Happy Learning! :)
📸 Gallery
Recent videos
Prediction: Categorical Variables | Full Course On Statistics for Data Science with Python.
46 views · 1 year ago
Prediction: Continuous Variables | Full Course On Statistics for Data Science with Python.
31 views · 1 year ago
Contingency Tables | Full Course On Statistics for Data Science with Python.
76 views · 1 year ago
Categorical Correlation | Full Course On Statistics for Data Science with Python.
12 views · 1 year ago
Quantifying Correlation: 3 Scenarios | Full Course On Statistics for Data Science with Python.
7 views · 1 year ago
The Correlation Playground | Full Course On Statistics for Data Science with Python.
9 views · 1 year ago
Continuous Variables: Linear Correlation | Full Course On Statistics for Data Science with Python.
9 views · 1 year ago
Correlation: The Biggest Trap! | Full Course On Statistics for Data Science with Python.
9 views · 1 year ago
A/B testing in Python: Step-by-Step | Full Course On Statistics for Data Science with Python.
29 views · 1 year ago
Application: Coin Flipping Conclusion | Full Course On Statistics for Data Science with Python.
6 views · 1 year ago
Application: Full Blown Simulation | Full Course On Statistics for Data Science with Python.
12 views · 1 year ago
Application: Is A Coin Biased? | Full Course On Statistics for Data Science with Python.
6 views · 1 year ago
🔀 Audience overlap
EstimatedEstimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.
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48%
Cybersecurity On Air
46%
Akshat Verma
45%
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44%
codewithaman
44%
Programming
40%
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