🚀 𝐈 𝐚𝐝𝐯𝐢𝐬𝐞 𝐅𝐨𝐮𝐧𝐝𝐞𝐫𝐬, 𝐂𝐄𝐎𝐬, & 𝐈𝐧𝐯𝐞𝐬𝐭𝐨𝐫𝐬 𝐨𝐧 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 & 𝐒𝐜𝐚𝐥𝐢𝐧𝐠 𝐭𝐡𝐞𝐢𝐫 𝐀𝐈 𝐆𝐫𝐨𝐰𝐭𝐡 𝐄𝐧𝐠𝐢𝐧𝐞𝐬 𝐭𝐨 $𝟏𝟎𝟎𝐌+ | 𝐂𝐡𝐢𝐞𝐟 𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐎𝐟𝐟𝐢𝐜𝐞𝐫, 𝐂𝐡𝐢𝐞𝐟 𝐆𝐫𝐨𝐰𝐭𝐡 𝐎𝐟𝐟𝐢𝐜𝐞𝐫, & 𝐂𝐡𝐢𝐞𝐟 𝐂𝐨𝐦𝐦𝐞𝐫𝐜𝐢𝐚𝐥 𝐎𝐟𝐟𝐢𝐜𝐞𝐫 | 𝐊𝐞𝐲𝐧𝐨𝐭𝐞 𝐒𝐩𝐞𝐚𝐤𝐞𝐫 | 𝐋𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩 𝐌𝐞𝐧𝐭𝐨𝐫

I am the Founder & CEO @ Aetheris Ventures: building AI-powered growth engines that turn early stage potential into market leaders. I've architected revenue strategies that have scaled companies from pre-seed to IPO, including one unicorn exit! 🦄 

🔗 𝐀𝐝𝐯𝐢𝐬𝐨𝐫𝐲: https://angeleymullins.org/advisory
🔗 𝐒𝐩𝐞𝐚𝐤𝐢𝐧𝐠 : https://angeleymullins.org/speaking
🔗 𝐌𝐞𝐧𝐭𝐨𝐫𝐢𝐧𝐠 : https://angeleymullins.org/mentoring

I have been a Chief Commercial Officer, Chief Marketing Officer, and Chief Growth Officer building 4X scale ups in addition to leading revenue-generating engines for some of the world's most successful technology brands, including Amazon, Intuit, and GoDaddy. I was recognised by Crunchbase, as one of the most influential women in sales, highlighting my ability to use an inbound demand generation engine to scale digital revenue growth. My revenue strategies are perfect for: 

✅ B2B SaaS and E-Commerce Founders & CEOs scaling GTM & Revenue from $0 to $50M ARR
✅ Companies looking to build a brand or grow brand awareness to generate revenue
✅ CEO's who want to increase pipeline conversion out of existing revenue engines to $100M+ ARR

I have a passion for Brand & Content to drive revenue and have been featured in Forbes, VentureBeat, The Drum, and other leading media and publications. I am also a frequent keynote speaker and podcaster with communities including: SaaStock, Turing Fest, SaaSiest, ARRtist, SheCanCode, CMO Alliance, Cognism, and many others.

I am passionate about scaling purpose- driven tech, using technology to give back to the community and mentoring the next generation of leaders. I hold multiple board and advisory roles including: World Bicycle Relief, The Female Factor, Coders Beyond Borders, and The Revenue Marketing Alliance among many others. I have a special interest for advancing the conversation around women in leadership and diversity at the executive level.

✅ Follow me for actionable insights on: 

➡️ GTM & AI Growth Strategy in both B2B SaaS & D2C
➡️ Commercial Leadership & Revenue Scaling
➡️ Marketing & Brand Positioning
➡️ AI in Marketing & Content Engines 
➡️ Women in Leadership & Women in Tech
➡️ Pitch Decks & Winning Investment

Angeley Mullins

This week I had the pleasure of attending the Women of SaaS Berlin New Year's Reception hosted at EY alongside some of the most inspiring women in the SaaS ecosystem! 🚀 

We tackled a question that's on everyone's mind: Is AI spelling the end of implementation partners, or the beginning of something new? The panel with voices from EY, Snowflake, and DeepL brought sharp, honest perspectives that sparked so many questions and insights. 

However it was the conversations between the conversations that stayed with me most. The energy in that room was a reminder of why community matters... especially in an industry moving as fast as ours. 

This year is all about building stronger networks, asking harder questions, and making 2026 the year we lead with intention.🔥 

Thanks to Julia Goelles for building such a wonderful community and to Stefania Guglielmetto, ✨Ananya Chattaraj, & Cindy Fiorella Rojas on the Women of SaaS Berlin Team for hosting such a great event! ❤️ 

Here's to all the amazing women from the event: w/Adriana Carmona Beltran, Busayomi Omotosho, Tatjana Pohl, Janina Schütz, Sina Landorff, Victoria Scholz, Sofia Lenkova, Ksenia Nuykina, Tannya Gaxiola, Viktoria Pap, Lisumi Dogo, Farah Zehra, Elena Gilbert, Edina Seibel, Paola A. Villegas E. , MBA, Angelina Lesnikova, PhD, Katrin Daller, and so many others!

Founder & CEO @ Aetheris Ventures: I help CEOs build and scale their growth engines to $100M+ | Keynote Speaker, AI GTM & Marketing Strategist, Board Member, Empowering Female Leaders, Crunchbase Most Influential Women

I am honored to be named a CMO to Watch in 2026 by CMO Alliance 🔥 

But more than the recognition, this one feels meaningful because of what it represents. Leadership that drives real results looks like: 

✅ Clarity on the mission, so everyone knows why the work matters
✅ Compassion in the hard moments, not just the wins 
✅ Trust that empowers people to take creative risks 
✅ A culture where feedback flows both ways

Revenue is the outcome. People are the engine. ❤️ 

In my career I have been a multiple time, CMO, CGO, CCO, etc, however I have learned one important thing: the CMOs and marketing leaders making the biggest impact right now are not just brilliant strategists, they are human first leaders who understand that motivation is not manufactured, it's earned.

You can see the full list of CMOs here: https://lnkd.in/dzj6JS5U

Proud to be part of a generation of marketers redefining what leadership looks like and what it's capable of driving. w/ Cecilia T., Emma Buitendag, Jacqui Morgan, Bryony Pearce, Aisha Lawlor, Rose Johnstone, Martha Harris, Richard King, Islam Gouda, Liza Adams , Toni Allen FCIM , Carolyn Bao, Ro Bocking-Wood , Aviv Canaani, Karen Chalmers, Kelly Cheng, Shelley Diamond , Jamie Domenici , Carlota Feliu Argila , Adrian Fulle, ALM, Rosie Guest, Bonnie Habyan , Steve Keifer, Kae Kronthaler-Williams, Jamie Labov, Jean Lawrence, Anders Lindstrom, Sonal Mane,  and everyone else on the list! 

Also a shout out to some of the fabulous marketing leaders who are making waves this year: w/ Jennifer Hoffman, ✨Ananya Chattaraj, Stefania Guglielmetto, Michal Lasman, Cindy Fiorella Rojas, Monika Vo, Joy Corkery, Merve Alsan, Elodie LABROUSSE, Mayuri Reddy, Franziska Heyde, and so many others! 

What does compassionate, revenue-focused leadership look like on your team? Let me know in the comments! 👇

Great startups & scale-ups always talk about expanding to global markets. But getting there takes more than ambition... it takes the right go-to-market strategy (GTM) to match. 🚀

That's why I'm excited to be joining the jury of the Next Market Accelerator hosted by ﻿Weglot!! The first edition drew nearly 200 qualified applications. The expansions that followed were real, measurable transformation inside the program. This time I will be helping select the 5 established B2C companies that join this year's cohort. 🔥

I am proud to judge this year's cohort alongside a POWERHOUSE group of advisors, mentors, and operators including: 
1️⃣ Blaise Matuidi : FIFA World Cup Winner & Founder Origins
2️⃣ Frédéric Mazzella : Founder & President at BlaBlaCar
3️⃣ Lisanne Dorn Bota : SVP Commercial at Sony Music Entertainment
4️⃣ Charlie Perreau : Head of Tech/Media Startups at Les Echos
5️⃣ Guillaume Rostand: CMO at Liligo
6️⃣ Joe Glover: Co-Founder at The Marketing Meetup
7️⃣ Andrea Vaugan : Founder at Wyngs.co - 🇫🇷  + 🇩🇪 🇦🇹🇨🇭
8️⃣ Melanie Krause: Founder at Haus of Growth.

The program is being sponsored by Weglot in partnership with Mollie & BOLD. 

What this program offers isn't hype. It's rigor:
✅ Intensive working sessions. 
✅ Direct access to experienced operators. 
✅ Expert support across growth, payments, legal, and strategy. 
✅ Up to €10,000 in funded expert resources. 
✅ Three months to turn international ambition into a structured, executable market entry plan.

It’s designed for companies that already have strong domestic traction and are ready to approach international growth with structure, clarity, and discipline.

𝐄𝐱𝐩𝐚𝐧𝐬𝐢𝐨𝐧 𝐝𝐨𝐞𝐬𝐧'𝐭 𝐫𝐞𝐰𝐚𝐫𝐝 𝐭𝐡𝐞 𝐛𝐨𝐥𝐝. 𝐈𝐭 𝐫𝐞𝐰𝐚𝐫𝐝𝐬 𝐭𝐡𝐞 𝐩𝐫𝐞𝐩𝐚𝐫𝐞𝐝. 💪 
If international growth is your next lever , this is the room worth being in. 🔥 

If you are a Founder or CEO looking to scale internationally you can apply here: https://lnkd.in/dSc-s79Q

Thanks to the amazing team at Weglot for hosting this program: w/ Elodie LABROUSSE, Augustin P., Eugene Ernoult, Elizabeth P., Pierre FERTOUT, Merve Alsan, Rayne A., Thomas Fanchin, Noemie R., Marie Terrou, and so many others on the Weglot team! 

Here's a shout out to some of the amazing Founders & CEOs who are building the future of tech: w/ Vera Matisovits, Tanja Danner, Aykut Atli, Jennifer Baum-Minkus, Audrey Vincent, Tian Yao, Ale Wiecek Rojo, Katie Payne, and so many others! For all the investors and accelerators out there, please pass this onto your founder community 🔥 Nina Wöss, Glory Eromosele, and more!

Germany is one of the fastest growing tech markets in Europe, however there are still so many people asking about how to come here and succeed 🇩🇪

I recently had the privilege of being featured in a video by Johanna Rüdiger, one of my favourite journalists at Deutsche Welle all about how to find a job in Germany. It's one of those conversations I wish I'd had when I was starting out here 🔥 

Whether you are a developer, data scientist, marketer, designer, or product manager looking to make your move to Germany, this one's for you! I had the pleasure of giving this interview with the fabulous Diana Abdrakhmanova and here is what we cover: 

✅ What the German tech job market actually looks like
✅ How to position yourself as an international candidate
✅ The mistakes most people make (and how to avoid them)
✅ Practical steps to land your first role

Germany is one of Europe's most exciting tech hubs right now: Berlin, Munich, & Hamburg are growing fast. Last week we also talked about the tech industry specifically in Berlin and its capacity to dominate the European Tech scene at an event at The Delta, called, " Berlin auf die Eins" sponsored by BAD1. To all the international talent out there... we need your skills! To everyone who is already in Germany, thank you for your support of the fabulous international talent coming here. ❤️ 

This is an opportunity to give a shout out to all the organisations, groups, and people who are supporting this amazing ecosystem: w/ 2hearts, Elnura Ashimova, Min-Sung Sean Kim, International Women in Berlin, Bruna Silva, Grace - Accelerate Female Entrepreneurship, Leonie Moos, Flämingo Startup Hub, Merantix AI Campus, HubSpot For Startups, Fabian Hartmann, Fernanda Bosmediano, Strong&Proud, Amela, Anais Cisneros, Busayomi Omotosho, ProductDive, Mayuri Reddy, Chiedza M., Alexandra Buys, Kave Bulambo (She/Her), Veronica Louis, Jana-Josephine Chowdhury, EWOR, Sina Landorff, Avomind Connect: Founders & Friends Berlin Meetup, and so many others!! 

A huge thank you to Johanna Rüdiger for having me. She's doing incredible work helping international professionals navigate their careers and lives in Germany. 🇩🇪

My missions
→ Lead & ship production-grade AI/ML systems - including AI Agents & RAG that actually move business metrics.
→ Educate AI/ML practitioners on how real-world production AI/ML systems are designed, deployed, and maintained (the parts most people skip).

My portfolio
→ Senior Data Scientist / AI Engineer (8+ years)
→ Built an AI Agent–powered FAQ chatbot (LangChain/LangGraph, AWS) used by thousands; significantly reduced customer support load.
→ Built end-to-end RAG: ingestion, semantic/recursive chunking, retrieval strategies, GDPR-first data flows
→ Built CLV forecasting, recommendation systems, marketing optimization, and scalable MLOps systems with significant business impact

My newsletter
→ JAM with AI - read by 26,000+ AI/ML builders
→ jamwithai.substack.com

Work with me
→ Collaborations, talks, and mentoring.

Shirin Jam

𝗧𝗵𝗲 "𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁" 𝗺𝗲𝗺𝗲 𝘄𝗮𝘀 𝗺𝗶𝘀𝘀𝗶𝗻𝗴 𝗮 𝗰𝗵𝗮𝗽𝘁𝗲𝗿.

So I made the sequel.

The original:
Statistics + Computer Science
= Data Scientist 

My update:
Data Scientist + LLMs & Agents
= AI Engineer 

I've lived this evolution!

As a Senior Data Scientist,
my work started with the classics:
→ Regression, classification, recommenders
→ Feature engineering, experiment design
→ Statistical modeling & evaluation

That foundation hasn't gone anywhere.
But the role has expanded.

Today I also build RAG pipelines,
work with LLMs and embeddings,
and build AI Agents in production

Here's what I've learned
about this evolution:

𝗪𝗵𝗮𝘁 𝘀𝘁𝗮𝘆𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 🦕 𝗽𝗵𝗮𝘀𝗲:
↳ Statistical thinking & probability
↳ Data wrangling & cleaning
↳ Asking the right questions before modeling
↳ Translating insights into business impact

𝗪𝗵𝗮𝘁 𝘁𝗵𝗲 🐉 𝗽𝗵𝗮𝘀𝗲 𝗮𝗱𝗱𝘀:
↳ LLM orchestration & prompt design
↳ RAG systems & vector search
↳ Agent architectures
↳ Deployment & production thinking
↳ Evaluation beyond accuracy metrics
↳ System design & architecture

The dinosaur didn't go extinct.
It grew wings.

But here's my honest take:
Is possible, don't skip the dinosaur phase.

Data Science fundamentals are what make
AI Engineers very effective.

Do you see such evolution? 😅 

---
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Shirin Khosravi Jam

Sr. Data Scientist/ AI Engineer | Data Science, RAG, AI Agents, & MLOps | Germany’s Top Female Voice in AI (Favikon) 🇩🇪

12 Github repositories every AI Engineer should know! 
(Covering ML, RAG, PyTorch, MLOps, Agents)
Bookmark them! 👇 

1️⃣ Machine Learning for Beginners by Microsoft
→ Start here if you’re brand new to ML.
Covers basic ML concepts in Jupyter notebooks beginner-friendly and visual.
🔗 https://lnkd.in/gGithBVP

2️⃣ Learn PyTorch for Deep Learning
→ A great repo to learn PyTorch - could be a bit outdated but the concepts still applies.
🔗 https://lnkd.in/d4ptSuUY

3️⃣ Hands-on Large Language Models
→ This repo supports the Hands-On LLM book.
Learn everything from basic language models to finetuning with real notebooks.
🔗 https://lnkd.in/gpvPemeG

4️⃣ AI Agents for Beginners
→ A fantastic beginner-friendly course to get started with AI agents.
Free 11-lesson hands-on curriculum - no fluff, just code.
🔗 https://lnkd.in/gVm5gmv7

5️⃣ Prompt Engineering Guide
→ One-stop-shop for prompt engineering.
Guides, papers, lectures, and tons of curated examples.
🔗 https://lnkd.in/gDt3Sknr

6️⃣ LLM Course
→ Hands-on course covering the entire LLM lifecycle — design to deployment.
Includes roadmaps + Colab notebooks.
🔗 https://lnkd.in/gUPJmWNM

6️⃣ GenAI Agents
→ Great tutorials + code for building agent-based LLM systems.
Covers everything from simple tool-using agents to advanced workflows.
🔗 https://lnkd.in/gaiZgzpA

7️⃣ RAG Techniques
→ One of the most comprehensive and dynamic collections of Retrieval-Augmented Generation (RAG) tutorials available
🔗 https://lnkd.in/dcGtjFgY

8️⃣ Agents towards production
→ It is your hands-on guide to every building block of a GenAI agent stack.
🔗 https://lnkd.in/dnnkrJbE

9️⃣ Awesome Generative AI
→ Massive curated list of GenAI tools, papers, interviews, repos, and more. Use it as your personal R&D knowledge base.
🔗 https://lnkd.in/gsTk5nXx

🔟 Made With ML
→ Covers full ML product lifecycle: from design to CI/CD and monitoring. If you’re serious about building production-grade ML systems, this is gold.
🔗 https://lnkd.in/gn2RhT_m

1️⃣1️⃣ Designing Machine Learning Systems
→ Summaries + code + diagrams from the popular O’Reilly book.
A must-read if you want to architect real-world ML pipelines.
🔗 https://lnkd.in/g26KNXfb

1️⃣2️⃣ Jam With AI
→ Hands on RAG and AI Agent projects
🔗 https://lnkd.in/dkphZt25

♻️ Repost & save if you found it insightful 💚

Sr. Data Scientist/ AI Engineer | Data Science, RAG, AI Agents, & MLOps | Germany’s Top Female Voice in AI (Favikon) 🇩🇪 | 215k+ AI/ML Community 🤯 | Opinions are my own!

2017: Started my DS journey on Kaggle.

And I wish I had this book back then.

Still remember those days:
Spent nights optimizing XGBoost hyperparameters.
Obsessed over leaderboard rankings.
Celebrated my first bronze medal
like I won a Nobel Prize 😂 

Kaggle taught me more than any course ever did.
But it took massive trial and error.
Countless failed submissions.
And hours of reading forums.

The learnings from Kaggle are HUGE.

I've personally applied so many of them
in real-life production systems:
→ Validation design saved me from bad deployments
→ Feature engineering tricks that still work in production
→ Ensembling strategies I use to this day
→ Debugging instincts you only build by competing

This book would have saved me years ↓

𝗧𝗵𝗲 𝗞𝗮𝗴𝗴𝗹𝗲 𝗕𝗼𝗼𝗸 (𝟮𝗻𝗱 𝗘𝗱𝗶𝘁𝗶𝗼𝗻)
by Luca Massaron, Bojan Tunguz, Ph.D. & Konrad Banachewicz

3 Kaggle Grandmasters sharing what took them years to learn.

Here's what it covers:
1️⃣ Kaggle Notebooks, Datasets & Models
2️⃣ Competition Tasks & Metrics
3️⃣ Designing Good Validation
4️⃣ Modeling for Tabular Competitions
5️⃣ Hyperparameter Optimization
6️⃣ Ensembling with Blending & Stacking
7️⃣ Modeling for Computer Vision
8️⃣ Modeling for NLP
9️⃣ GenAI Competitions (NEW)
🔟 Time Series (NEW)

Whether you're just starting on Kaggle
or a seasoned competitor 
this is the playbook I wish existed in 2017.

🔗 Link - https://lnkd.in/dbAERJAy
🔗 Code - https://lnkd.in/dKUDihC9

I strongly feel Kaggle is still very relevant today!

And you just need more structured guide to approach it 
and learn from others' competitions!
This book provides that!

Do you agree?

---
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I work on RAG + AI Agents in production
(for a year - its not a 1 week thing)
and this is the AI Engineer roadmap I’d give my younger self.

How to use this roadmap
1️⃣ Months marked (non-negotiable) = baseline skills for AI engineering
2️⃣ Others = good to have as RAG/Agents mature and integrate with broader ML/MLOps stacks

Here’s a 6-month plan I wish I had 👇

1️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟭 - 𝗣𝘆𝘁𝗵𝗼𝗻 (𝗻𝗼𝗻-𝗻𝗲𝗴𝗼𝘁𝗶𝗮𝗯𝗹𝗲)
→ Python is your base. Clean code pays off 10× later.
↳ Add Clean Code / Pragmatic Programmer if ambitious.
Resources:
🔗 100 Days of Code - Python (Udemy): https://lnkd.in/dja5meSA
🔗 CS50P - Harvard Intro to Python: https://lnkd.in/dDqpF4iy

2️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟮 - 𝗠𝗟 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀
→ Core ML, then PyTorch + basic neural nets.
↳ Keep it hands-on; build tiny projects.
Resources:
🔗 Hands-On ML (A. Géron): https://lnkd.in/dxMCK2rT
🔗 Neural Networks: Zero to Hero (YouTube): https://lnkd.in/dv5bkczy

3️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟯 - 𝗡𝗟𝗣 + 𝗟𝗟𝗠𝘀 (𝗻𝗼𝗻-𝗻𝗲𝗴𝗼𝘁𝗶𝗮𝗯𝗹𝗲)
→ Learn NLP fundamentals first; then embeddings, tokenization, RAG.
↳ Understand evals before prompt tricks.
Resources:
🔗 NLP with Transformers: https://lnkd.in/d5CzV5ZY
🔗 Hands-On Large Language Models: https://lnkd.in/dkCVtYy4

4️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟰 - 𝗠𝗟𝗢𝗽𝘀
→ Deployment, CI/CD, experiment tracking, observability.
↳ Treat data/contracts like code; version everything.
Resources:
🔗 Designing Machine Learning Systems: https://lnkd.in/d63J5cR3
🔗 Made With ML (repo): https://lnkd.in/duifMXRw

5️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟱 - 𝗥𝗔𝗚 + 𝗔𝗴𝗲𝗻𝘁𝘀 (𝗻𝗼𝗻-𝗻𝗲𝗴𝗼𝘁𝗶𝗮𝗯𝗹𝗲)
→ Start with LangChain/LangGraph; then design your own orchestration.
↳ Retrieval quality > prompt cleverness.
Resources:
🔗 Nir Diamant - RAG/agents repo: https://lnkd.in/dxmzwhJM
🔗 Generative AI with LangChain: https://lnkd.in/dNjqeeaw

6️⃣ 𝗠𝗼𝗻𝘁𝗵 𝟲 - 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 (𝗻𝗼𝗻-𝗻𝗲𝗴𝗼𝘁𝗶𝗮𝗯𝗹𝗲)
→ Think systems: infra, eval gates, feedback loops, cost/latency.
↳ Read real postmortems from production teams.
Resources:
🔗 AI Engineering (Chip Huyen): https://lnkd.in/d776CtFQ
🔗 Production AI blogs (AWS, Anthropic, Pinecone, OpenAI, etc.)

PS: It’s okay if this takes longer than 6 months.
Be consistent. Ship small, ship often.

What would you add or swap?
Drop one resource or habit that helped you 👇 

--
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10 YouTube channels can teach you 
everything you need to break into AI in 2026 - for free.👇

(I didn't come from CS background)
I learnt everything myself.
I know how valuable these resources 
could be for someone on the same journey!

🔹 Foundations & Beyond:
1️⃣ StatQuest with Joshua Starmer PhD
→ Makes scary topics like statistics & ML feel joyful and simple
→ Start here if math makes you nervous 

2️⃣ 3Blue1Brown
→ The most intuitive explanations of linear algebra, calculus, and neural nets
→ Especially powerful for building visual understanding of complex math

3️⃣ sentdex
→ Massive Python playlist library (ML, NLP, deep learning, and more)
→ Great if you prefer code-driven, project-based tutorials

4️⃣ Stanford Online
→ Classic university lectures made public
→ The playlist keeps getting updated with more and more latest content around AI.

🔹 LLMs & Beyond:
5️⃣ Andrej Karpathy
→ Deep dives on how LLMs and neural networks actually work
→ His “zero-to-hero” coding series is gold for understanding transformers

6️⃣ Sebastian Raschka, PhD
→ Practical, well-explained content on ML, deep learning, and LLMs
→ Often goes beyond theory into real-world training/debugging insights

🔹 Hands-on Content
7️⃣ Krish Naik
→ Consistent tutorials on applied ML, deep learning, and real-world deployments
→ Perfect for job-seekers and early-career practitioners

8️⃣ Patrick Löber (aka Python Engineer)
→ Clean, concise Python + ML tutorials
→ Fast way to build portfolio-ready projects from scratch

9️⃣ freeCodeCamp .org
→ Full 10-hour+ courses on ML, Python, data science - for free
→ Great for anyone who wants deep structure without cost

🔟 Dave Ebbelaar
→ Focus on MLOps, real-world data workflows, and AI pipelines
→ Super relevant if you want to learn how production systems actually work

Any other youtube channel you would recommend?
Comment below and let's help the community 👇

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Angeley Mullins

Shirin Jam

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The Battle

Angeley Mullins

Shirin Jam

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Angeley Mullins's LinkedIn Performance

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