Graph Algorithms, GraphRAG and Causal Graphs, with Graph Guru Amy Hodler

For *years*, I'd been trying to get Amy Hodler on my show. Finally she's here! A graph-network guru, Amy fills us in on graph algorithms and cutting-edge applications like GraphRAG and Causal Graphs. Enjoy!

More on Amy:

• Graph-tech evangelist and co-author of O'Reilly books on Graph Algorithms and Knowledge Graphs.

• Decades of experience in emerging tech at companies like HP, Hitachi, Neo4j, and Cray.

• Founder of GraphGeeks.org, a community for people passionate about graphs and connected data.

Today's episode will probably appeal most to hands-on data/AI practitioners but Amy is such a tremendous communicator that anyone who wants to know the latest on graph networks (and their powerful real-world use-cases!) will enjoy it.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Landing $200k+ AI Roles: Real Cases from the SuperDataScience Community, with Kirill Eremenko

As we approach episode #900, the original SuperDataScience Podcast host Kirill Eremenko returns to reflect on what leads to the highest-paying opportunities in AI. This is a special one; enjoy!

Many of you will already know Kirill:

• Founder and CEO of SuperDataScience.com, the eponymous e-learning platform.

• Founded the SuperDataScience Podcast nine years ago and hosted the show until he passed me the reins five years ago.

• With over 3 million students, he’s the most popular data science and A.I. instructor on Udemy.

• He holds a Master’s from The University of Queensland in Australia and a Bachelor’s in Applied Physics and Mathematics from the Moscow Institute of Physics and Technology.

Today’s episode is ideal for anyone looking to advance their data science or A.I. career — or looking to break into a career in this field for the first time.

In today’s episode, Kirill details:

• Why employers are still testing A.I. engineers on basic machine learning fundamentals — even for LLM-focused roles.

• The surprising reason why staying in data science (as opposed to developing an A.I. specialization) could be the right career move for you.

• How one developer discovered the hidden age bias in tech recruiting — and the simple hack to beat it.

• The two critical skill areas that separate amateur A.I. engineers from the pros commanding huge salaries.

• Why the "back to office" movement could give you a competitive advantage in landing a top A.I. role.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in April 2025

We had a record number of guests on my podcast in April — and they were spectacular! In today's "In Case You Missed It" episode, hear the best parts of my conversations with each of them.

The specific conversation highlights included in today's episode are:

1. Sama Bali from NVIDIA and Logan Lawler from Dell Technologies fill us in on the AI software stack on NVIDIA GPUs, including libraries like CUDA.

2. Continuing on the A.I. hardware topic, Emily Webber details Amazon Web Services (AWS)'s own A.I. accelerator chips.

3. Zerve AI's co-founder Dr. Greg Michaelson describes how data scientists can deploy A.I. models to production without needing to call on an engineering team.

4. Kai Beckmann, CEO of Merck KGaA's semiconductor business, describes intricate details of the semiconductors that make A.I. systems hum.

5. Finally, Shirish Gupta explains his "A-I-P-C" framework for finding out if you should be using edge compute for local A.I. inference instead of relying on cloud compute.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Calling Clinicians: Help Us Build the Future of AI Therapy

I recently began supervising a PhD student in the Auckland robotic-engineering department and we are looking to partner with psychotherapists to develop a companion robot. Do you know anyone relevant/interested?

(I promise that our eventual robotic solution will not be a two-headed monstrosity featuring my face on a kiwi bird's body... but maybe it helped get your attention 😂)

Through several years of upcoming R&D at The University of Auckland (I will mostly be supervising remotely from New York!), our project aims to develop a therapeutic A.I. model (e.g., a multi-modal Large Language Model) to power the conversational, perceptual and (potentially) real-time video-generation capabilities of a companion robot that gives its user (which could be in a clinical or at-home setting) personalized therapy and support when a human therapist is unavailable.

A particularly prominent challenge for us in developing and testing this LLM (and, eventually, robotic embodiment) is access to data from real therapeutic conversations, although there are other immediate and long-term R&D challenges that we would love practicing therapists to help us with as well.

This is an exciting, impactful project that could markedly improve millions of lives around the world in the coming decades. I applaud PhD candidate Maryam Khakpour for tackling it head on! If you're a clinician who's keen to be involved with the A.I. revolution, now's your chance :)

Serverless, Parallel, and AI-Assisted: The Future of Data Science is Here, with Zerve’s Dr. Greg Michaelson

What are "code nodes" and "RAG DAGs"? Listen to today's episode with the highly technical (but also highly hilarious) Dr. Greg Michaelson to get a glimpse into the future of data science and A.I. model development.

Greg:

• Is a Co-Founder of Zerve AI, a super-cool platform for developing and delivering A.I. products that launched to the public on this very podcast a little over a year ago.

• Previously spent 7 years as DataRobot’s Chief Customer Officer and 4 years as Senior Director of Analytics & Research for Travelers.

• Was a baptist pastor while he obtained his PhD in Applied Statistics!

Today’s episode is on the technical side and so will appeal most to hands-on practitioners like data scientists, AI/ML engineers and software developers… but Greg is such an engaging communicator that anyone interested in how the practice of data science is rapidly being revolutionized may enjoy today’s episode.

In it, Greg details:

• How Zerve's collaborative, graph-based coding environment has matured over the past year, including their revolutionary 'Fleet' feature (in beta) that allows massive parallelization of code execution without additional cost.

• How AI assistants are changing the coding experience by helping build, edit, and connect your data science projects.

• Why the rise of LLMs might spell trouble for many SaaS businesses as building in-house solutions becomes increasingly viable.

• The innovative ways companies are using retrieval-augmented generation (RAG) to create more powerful A.I. applications.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in March 2025

We had absolutely killer guests and killer conversations on my podcast in March. This isn't bluster; I learned a ton from Andriy, Richmond, Natalie and Varun... Today's episode features all the best highlights!

The specific conversation highlights included in today's episode are:

1. The mega-bestselling author of "The 100-Page Machine Learning Book" (and now "The 100-Page Language Models Book"!) Dr. Andriy Burkov on the missing piece of AGI: Why LLMs can't plan or self-reflect.

2. Relatedly, the fascinating and exceptionally well-spoken Natalie Monbiot contrasted artificial intelligence with the human variety, detailing what makes us unique.

3. The charismatic software engineer Richmond Alake (of MongoDB) explained his "A.I. Stack" concept and how you can leverage it to build better A.I. applications.

4. Former Google Gemini engineer Varun Godbole provides a helpful overview of guide to neural network design, the (freely available!) "Deep Learning Tuning Playbook".

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in February 2025

February was another insane month on my podcast. In addition to having stunning smiles, all four guests I hosted are fascinating, highly knowledgeable experts. Today's episode features highlights of my convos with them.

The specific conversation highlights included in today's episode are:

1. Professional-athlete-turned-data-engineer Colleen Fotsch on how DBT simplifies data modeling and documentation.

2. Engineer-turned-entrepreneur Vaibhav Gupta on the new programming language, BAML, he created for AI applications. He details how BAML will save you time and a considerable amount of money when calling LLM APIs.

3. Professor Frank Hutter on how TabPFN, the first deep learning approach to become the state of the art for modeling tabular data (i.e., the structured rows and columns of data that, until now, deep learning was feeble at modeling).

4. The ebullient Cal Al-Dhubaib on the keys to scaling (and selling!) a thriving data science consultancy.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in January 2025

Happy Valentine's Day 💘 ! My high-calorie gift to you is today's episode, which features the best highlights from conversations I had with the (absolutely epic!) guests I hosted on my podcast in January.

The specific conversation highlights included in today's episode are:

1. Famed futurist Azeem Azhar on how to break your linear mindset to prepare for the exponential technological change that we are experiencing (and will experience even more rapidly in years to come).

2. Global quantum-computing expert Dr. Florian Neukart on practical, real-world applications of quantum computing today.

3. Kirill Eremenko and Hadelin de Ponteves — who have together taught over 5 million people data science — with their 12-step checklist for selecting an appropriate foundation model (e.g., large language model) for a given application.

4. Brooke Hopkins (former engineer at Waymo, now founder and CEO of Y Combinator-backed startup Coval) on why you should evaluate A.I. agents with reference-free metrics.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

From Pro Athlete to Data Engineer: Colleen Fotsch’s Inspiring Journey

Colleen Fotsch won national swimming championships and was a pro athlete in both CrossFit and bobsledding. Now she's excelling at data analytics and engineering! Today, hear her fun, inspiring and practical story.

More on Colleen:

• As a collegiate swimmer, she won national championships and set an American record in the relay.

• As a pro CrossFit athlete, she twice competed at the “Games”, which is the highest echelon of the sport.

• And then she simultaneously pursued a degree in data analytics while training with the US Bobsled team.

• An injury ended her Olympic Bobsled team dream, but luckily she’d been pursuing that analytics career in parallel!

• She began working full-time as a data analyst four years ago and has now grown into a data-engineering leadership role at a healthcare-staffing firm called CHG Healthcare in Utah, where she serves as Senior Technical Manager of their Data Platform.

• Inspires her 280,000 Instagram followers on a daily basis.

Today’s episode essentially has two separate parts:

• The first half focuses on Colleen’s exciting journey to the highest levels of three sports: swimming, CrossFit and bobsledding. That part should be fascinating to just about anyone.

• The second half covers Colleen’s transition into data analytics and data engineering; that part will appeal to technically-minded listeners, particularly ones considering a career in or early on in a career in analytics or engineering.

In today’s episode, Colleen details:

• The connection between a competitive sports mindset and data-career success.

• Proven strategies for being hired into your first data role later in your career.

• Why being "not smart enough" for coding was a mental block she had to overcome.

• How analytics engineering bridges the gap between data engineering and analysis.

• The huge benefits deskbound professionals can enjoy by including regular exercise in their week, and tips and tricks for developing or growing an exercise habit.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Exponential Views on AI and Humanity’s Greatest Challenges, with Azeem Azhar

Today, the famed futurist Azeem Azhar eloquently details the exponential forces that are overhauling society — and why A.I. is essential for solving humanity's biggest challenges. This is a special episode; don't miss it!

In case you aren't familiar with his legendary name already, Azeem:

• Is creator of the invaluable "Exponential View" newsletter (>100k subscribers).

• Hosts the "Exponential View" podcast (well-known guests include Tony Blair and Andrew Ng).

• Hosted the Bloomberg TV show "Exponentially" (guests include Sam Altman).

• Holds fellowships at Stanford University and Harvard Business School.

• Was Founder & CEO of PeerIndex, a venture capital-backed machine-learning startup that was acquired in 2014.

• He holds an MA in PPE (Politics, Philosophy and Economics) from the University of Oxford.

Today’s episode will appeal to any listener. In it, Azeem details:

• The exponential forces that will overhaul society in the coming decades.

• Why AI is essential for solving humanity's biggest challenges.

• His own cutting-edge, personal use of A.I. agents, LLMs, and automation.

• Why there's no 'solid ground' in the future of work and how we can adapt.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in December 2024

Today's "In Case You Missed it Episode"... is one not to miss! Several of the most fascinating conversations I've ever had on the SuperDataScience Podcast I host happened in December.

The specific conversation highlights included in today's episode are:

1. The legendary Dr. Andrew Ng on why LLM cost doesn't matter for your A.I. proof of concept.

2. Building directly on Andrew's segment, CTO (and my fellow Nebula.io co-founder) Ed Donner on how to choose the right LLM for a given application.

3. Extremely intelligent and clear-spoken Dr. Eiman Ebrahimi (CEO of Protopia AI) on the future of autonomous systems and data security in our Agentic A.I. future.

4. From our 2024 recap episode, Sadie St. Lawrence's three biggest A.I. "wow" moments of the year... as well as the biggest flop of the year. (One company was behind both!)

5. Harvard/MIT humanist chaplain Greg Epstein (and bestselling author on tech in society) on the ethics of accelerating A.I. advancements. Should we, for example, consider slowing A.I. progress down?

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in November 2024

We had a ton of laughs and I had some seriously mind-expanding moments thanks to my guests on the SuperDataScience Podcast last month. ICYMI, today's episode highlights the most riveting moments from November.

The specific conversation highlights included in today's episode are:

1. Deepali Vyas, Global Head of Data and A.I. at executive-search giant Korn Ferry, on how A.I. is transforming recruitment and how job-seekers can stay ahead of the curve.

2. Jess Ramos, data analyst and leading content creator on data careers, on where to start if you yourself are seeking a career in data.

3. Bryan McCann, co-founder and CTO of the rapidly-scaling A.I. platform You.com, on why machines will make much better scientists than humans... and how they will surpass human scientists surprisingly soon.

4. Martin Goodson, CEO of the prestigious British A.I. firm Evolution AI, on how the public figures who are speaking most loudly about A.I. are probably not the people we should be listening to.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Double Your Data Salary in 11 Months, with Jess Ramos

Today's episode features the charismatic and intelligent Jess Ramos. A data analyst, Jess has grown a huge social-media following via her fun content on SQL, data science, tech advances and career growth.

More on Jess:

• Founder of Big Data Energy Analytics⚡️, a company that supports her in-demand courses on SQL and data analytics.

• Senior Data Analyst at Crunchbase.

• Previously worked as a Senior Risk Analyst and as a Data Analytics Manager.

• Her popular social-media content (on SQL, data analytics, data science, tech advancements and maximizing professional growth) has led her to amassing over 300k followers across LinkedIn, Instagram and TikTok.

• She holds a Bachelor's in Math and she also holds a Master's in Business Analytics from The University of Georgia.

Today’s episode will appeal especially to folks who are looking to grow their career or grow into a career in data analytics or data science.

In today’s episode, Jess details:

• How she more than doubled her data analyst salary in less than a year.

• The questionable value of data science bootcamps.

• Her controversial take on "girl math" that made a splash in international mainstream news.

• The unexpected viral post that launched her into social-media fame.

• Essential advice for anyone starting their data career journey

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Career Success in the AI Era, with Deepali Vyas

Rapid A.I. advances can be intimidating: How can you approach your career so you flourish in the coming A.I. era? Find out from Deepali Vyas — a world-leading A.I.-exec headhunter — in today's episode.

Deepali is:

• Senior Partner and Global Head of the Data, A.I. and Financial Technology Practice of Korn Ferry, one of the world’s largest executive-search firms.

• Founder of ProFolios.ai, a video-centric, A.I.-enhanced professional-branding platform.

• Founder of Fearless+, a platform that empowers tens of thousands of young people for career success.

• Holds a Bachelor’s in Financial Mathematics and a Master’s in International Finance from the London School of Economics.

Today’s episode should be interesting to everyone. In it, Deepali details:

• How A.I. has driven a 10x increase in applications per position and how you can compete in this high-volume climate.

• Why technical skills are becoming "table stakes" and what will differentiate the best candidates in the A.I. era.

• An insider's view on the talent flows between Wall Street and Silicon Valley, and how you can capitalize on these flows in your career.

• The "green flags" to look for in potential bosses and employers.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

How to Become Happier, with Dr. Nat Ware

On most metrics, it's never been a better time to be alive. And yet, many of us are unhappy. In today's episode, Dr. Nat Ware explains why we're unhappy... and, mercifully, what we can do about it!

Nat:

• Is a renowned keynote speaker; he has one TEDx talk alone that has over 2 million views on YouTube (it forms the basis of the content in today’s episode).

• Is the social-impact entrepreneur behind 180 Degrees Consulting (the world's largest consultancy for non-profits) as well as Forté (a startup that facilitates cost-free reskilling of workforces).

• Holds both a doctorate in economics and an MBA from the University of Oxford.

Today’s episode should be fascinating to anyone. In it, Nat details:

• Why, despite life on this planet being better than ever before, humans are so unhappy.

• Concrete guidance on what you can do to become happier.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in October 2024

It's unreal to be able to speak to folks like the guests I hosted on the SuperDataScience Podcast last month. ICYMI, today's episode highlights the most riveting moments from October.

The specific conversation highlights included in today's episode are:

1. UC San Diego neuroscience professor Dr. Bradley Voytek on how data science facilitates breakthroughs in our understanding of the brain.

2. Eloquent Natalie Monbiot on how lifelike, digital versions of ourselves can scale up our public-facing work.

3. Lightning AI CTO Dr. Luca Antiga on where he sees generative A.I. being most useful in our professional lives.

4. Gable CEO Chad Sanderson on how, when we work with data, we always need to think about how downstream users might come to interpret our data... which is why he finds data contracts so important that he's writing an O'Reilly book about it.

5. Polars CEO Ritchie Vink on the incredible specs (e.g., efficiency speedups) of his open-source DataFrame-operations library for Python.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

The 10 Reasons AI Projects Fail, with Dr. Martin Goodson

Most A.I. projects fail. In today's episode, the brilliant (and hilarious) Dr. Martin Goodson details the top 10 reasons why A.I. projects fail and how to avoid these common pitfalls.

Martin:

• Is CEO and Chief Scientist at Evolution AI, a firm that uses generative A.I. to extract information from millions of documents a day for their clients.

• Is Founder and Organizer of the London ML Meetup, which (with >15,000 members) is the largest community of AI/ML experts in Europe.

• Previously led data science at startups that apply ML to billions of data points daily.

• Was a statistical geneticist at the University of Oxford (where we shared a small office together)!

Today’s episode will be of interest to anyone even vaguely interested in data science, ML or AI. In today’s episode, Martin details:

• The 10 reasons why data science projects fail and how to avoid these common pitfalls.

• His insights on building A.I. startups that serve large enterprises.

• The importance of open-source A.I. development.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

The Skills You Need to Be an Effective Data Scientist, with Marck Vaisman

Based on extensive research and analytical evaluations, in today's episode Marck Vaisman details all the skills that are essential for today's data professional.

Marck:

• Has been at Microsoft for seven years; for 5+ years, he’s been a Senior Cloud Solutions Architect, specializing in data, data science and AI/ML.

• For nearly a decade he’s also been an adjunct professor at both Georgetown University and The George Washington University, teaching graduate-level courses on math, stats, analytics and decision sciences.

• Co-Founded a non-profit in Washington, DC that runs both the Data Science DC and Statistical Programming DC Meetups.

• Holds a Bachelor's in Mechanical Engineering from Boston University and an MBA from Vanderbilt University.

Today’s episode will be of interest to anyone who is, manages, or aspires to be a data professional.

In today’s episode, Marck details:

• The skills, competencies and personas that data scientists and related professionals (such as analysts, data engineers, ML engineers and A.I. engineers) can have.

• The academic research on why “data scientist” is such a difficult job title to define.

• A comprehensive characterization of the essential skills that every data professional needs to be effective and the skills that allow you to specialize as a particular subtype of data scientist.

• The implications of all of this for both folks hunting for a data role and the companies that are looking to hire them.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in August 2024

We had a slew of eye-opening conversations in August on the SuperDataScience Podcast I host. ICYMI, today's episode highlights the most fascinating moments from my convos with them.

Specifically, conversation highlights include:

1. ChainML's Head of A.I. Education Shingai Manjengwa on how multiple, individual A.I. agents can come together to perform complex actions.

2. Renowned futurist and entrepreneur Dr. Daniel Hulme on how A.I. can help us become better and faster at our jobs by circumventing the traditional corporate hierarchies that today seem only to slow us down.

3. Mathematical-optimization guru Jerome Yurchisin (of Gurobi Optimization) on how continuing education will be vital in our increasingly automated work environment... and how this education will be streamlined by A.I.

4. Nick Elprin, Co-Founder and CEO of the wildly successful Domino Data Lab, on why it's essential for enterprises to clearly define their A.I. infrastructure in order for their A.I. deployments to prosper.

Check out today's episode (#818) to hear all these eye-opening conversations. The "Super Data Science Podcast with Jon Krohn" is available on all major podcasting platforms and a video version is on YouTube.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.