Super Data Science: ML & AI Podcast with Jon Krohn YouTube Channel Earnings Report & Research

To answer how much does Super Data Science: ML & AI Podcast with Jon Krohn make, Branzly runs the channel's estimated 161.2K monthly views through the same ad revenue calculator used across the site: a SaaS / Tech RPM of $3.4-$10.2 from 2026 niche benchmarks, with the headline figure taken at the middle of that range ($6.8), the same RPM used in the home page calculator. That puts Super Data Science: ML & AI Podcast with Jon Krohn YouTube ad revenue at roughly $548 to $1,644 per month, or $6,578 to $19,733 per year from AdSense alone.

RPM is what the channel actually keeps per 1,000 views after YouTube's 45% revenue share, unfilled ad inventory and ad blockers, which is why these Super Data Science: ML & AI Podcast with Jon Krohn earnings figures sit far below the advertiser-side CPM quotes you may see elsewhere. Views from Tier 1 countries such as the United States, United Kingdom, Canada and Australia pay the most, while Shorts views pay a fraction of long-form RPM.

On top of ad revenue, we assume one integrated-mention sponsorship per month priced on 2.9K average views per video at a SaaS / B2B cost-per-view rate of $0.02 with a 1.4× niche multiplier — the identical model in our sponsorship calculator. That suggests a Super Data Science: ML & AI Podcast with Jon Krohn sponsored video is worth about $52 to $104, with a fair midpoint near $74.

Sponsorship pricing follows views and engagement, not subscriber count, so a large channel with a quiet video is still only paid for the views that video earns. Brands asking "how much does it cost to sponsor Super Data Science: ML & AI Podcast with Jon Krohn?" should expect dedicated videos to cost two to three times an integrated mention.

Channel-level deals work differently again. A retainer is an ongoing fee for a set of deliverables each month, not the sum of every slot the channel could sell, so pricing follows published size bands. With 267.0K subscribers, Super Data Science: ML & AI Podcast with Jon Krohn sits in the Mid-tier (100K-500K subs) band, where retainers typically run $4,000 to $15,000 a month. Niche demand, engagement, cadence across 55 uploads a month and how much of the audience watches each upload decide where in that band a deal lands. Spread back across uploads, that adds about $176 of value to each video.

Put simply, Super Data Science: ML & AI Podcast with Jon Krohn YouTube earnings are estimated at roughly $7,390 to $15,328 per month when ad revenue, one sponsored integrated mention and a retainer are combined, or about $88,679 to $183.9K per year. Channels that publish more sponsored videos, sell merchandise or courses, run memberships, or earn affiliate commissions typically make more than this range.

Net worth estimates for YouTubers like Super Data Science: ML & AI Podcast with Jon Krohn usually start from several years of this yearly income, minus taxes, team costs and production spend. Treat any Super Data Science: ML & AI Podcast with Jon Krohn net worth figure as a planning range, not a disclosed number.

Super Data Science: ML & AI Podcast with Jon Krohn (@superdatasciencewithjonkrohn) is a technology YouTube channel that has published 2,799 videos and accumulated 8,238,149 lifetime views from an audience of 267,000 subscribers. It continues to publish content for viewers interested in technology topics. In the creator's own words: "The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on Super Data Science, the most listened-to podcast in the industry. In lighthearted conversation with renowned guests, Jon cuts through hype to fuel your professional impact. Whether you're curious about getting started in a data career or you're a deep techni" Branzly analyses Super Data Science: ML & AI Podcast with Jon Krohn using public YouTube data so creators, brands and media buyers can understand the channel's size, output and likely earning power before they reach out, benchmark against it, or plan a collaboration.

Super Data Science: ML & AI Podcast with Jon Krohn currently has 267,000 subscribers, a figure that places the channel in the established mid-tier tier of YouTube creators. Total channel views stand at 8,238,149, and average views per video sit at approximately 2,943. The ratio of lifetime views to subscribers is about 30.9 views for every subscriber, which indicates an audience that is concentrated in the channel's regular, subscribed viewers. Branzly estimates recent activity at roughly 161,220 views per month based on the channel's most recent uploads and publishing history, which is the number our ad revenue calculator uses to model earnings.

The most-watched long-form video currently visible for Super Data Science: ML & AI Podcast with Jon Krohn is "Why Your Agent Evals Are Missing the Real Failures (with Aishwarya Srinivasan)" with 46,111 views. On the Shorts side, "Where A Workflow Ends And An Agent Begins" leads with 3,333 views. Top-performing titles are worth studying because they reveal which hooks, formats and topics the algorithm rewards for this audience. For brands, they also show the realistic ceiling of a sponsored placement: a dedicated integration on a channel of this size will usually land somewhere between the average video performance of 2,943 views and the outliers shown above.

Based on an estimated 161,220 monthly views and typical technology CPM ranges, Super Data Science: ML & AI Podcast with Jon Krohn could earn roughly $548 to $1,644 per month from YouTube ad revenue, or approximately $6,577 to $19,733 per year. These figures reflect the AdSense share only. Most channels of this size also earn from brand sponsorships, affiliate links, memberships, merchandise and product sales, so total creator income is commonly several times the advertising estimate. Sponsorship value is usually priced per view rather than per thousand impressions, and technology audiences typically command above-average rates because of advertiser demand in that vertical.

Branzly classifies Super Data Science: ML & AI Podcast with Jon Krohn under the Technology category using the channel's description, keywords, topic signals and the language of its best-performing uploads. Category matters more than raw subscriber count when estimating revenue: a technology channel attracts a specific set of advertisers, and CPMs vary widely between verticals such as finance, software, education, gaming and entertainment. The channel lists US as its primary country, which further shapes its CPM because advertiser spend differs sharply between geographies. Public channel keywords include Super Data Science, Super Data Science Podcast, Data Science, Jon Krohn, Technology, Data Science Career, Machine Learning, Artificial Intelligence, which supports this classification. Use the Branzly ad revenue, sponsorship and financial freedom calculators to model how a channel like Super Data Science: ML & AI Podcast with Jon Krohn converts views into monthly income, sponsorship pricing and long-term wealth.

Every figure on this page comes from the public YouTube Data API, refreshed each time Super Data Science: ML & AI Podcast with Jon Krohn is searched on Branzly. Subscriber counts, view counts and video counts are reported directly by YouTube. Monthly views are an estimate: YouTube does not publish per-month analytics for channels you do not own, so Branzly reconstructs recent performance from the views of the channel's latest uploads, falling back to lifetime views divided by channel age when recent data is sparse. Revenue ranges are modelled estimates, not disclosed earnings, and actual payouts depend on monetisation status, watch time, ad formats, seasonality, audience geography and YouTube's revenue share. Nothing on this page is financial advice, and Branzly is not affiliated with or endorsed by Super Data Science: ML & AI Podcast with Jon Krohn or YouTube.

Technology channels like Super Data Science: ML & AI Podcast with Jon Krohn sit in the SaaS / Tech RPM bracket. Advertisers pay more for audiences that buy — finance, business and tech pay the highest rates, while entertainment, gaming and music rely on huge view volume. Seasonality matters too: Q4 ad rates commonly run 30–50% higher than January.

Every figure on this Super Data Science: ML & AI Podcast with Jon Krohn channel earnings report comes from public YouTube Data API statistics — subscribers, lifetime views, video count and recent upload performance — refreshed when the report is opened. Estimates are modelled, not disclosed income, and not financial advice. Want to test your own assumptions? Open the YouTube money calculator or browse brands that already sponsor similar creators in the sponsors directory.