AI learning guide

Best AI resources for data teams

Connect data, ML, retrieval, observability, and production workflows.

Best production ML habits: Made With ML. Free course covering production ML workflows. Start here if your data team needs engineering habits that transfer to AI systems.

Best structured ML engineering path: DataTalks.Club ML Zoomcamp. Free cohort course for machine learning engineering. Use it when data engineers need a clear bridge into ML and AI engineering.

Best observability path: Phoenix by Arize. Open-source tracing and eval tooling for LLM applications. Use it when data teams own quality measurement and debugging.

Data teams already own many AI foundations

Data teams understand pipelines, quality checks, schemas, dashboards, experiments, and production data. Those skills transfer directly into RAG, evals, observability, and AI product measurement.

Made With ML and DataTalks.Club are good bridges into ML engineering. Phoenix is useful when the team needs to inspect LLM traces and evaluate workflow quality.

Move from data access to AI quality

A data team supporting AI should think about source freshness, permissions, feature stores, retrieval quality, eval datasets, and monitoring. The model is only one part of the system.

Good resources should connect data engineering habits to AI workflows: reproducibility, lineage, test sets, observability, and clear ownership of failure modes.

Recommended courses and resources

Warp agent-log breach response guide

AI developer-tool security analysis · Warp · Intermediate

Assess Warp's vendor breach, identify exposed agent data and decide which logs, credentials and integrations need review.
OpenAI Signals work dataset explained

AI work data analysis · OpenAI · Beginner to intermediate

You want to interpret OpenAI's October 26 dataset on consumer ChatGPT work use without treating message shares as employment, productivity or job-displacement evidence.
Meta $95B AI equity financing explained

AI infrastructure financing analysis · Meta · Intermediate

You want to separate Meta's launched $35 billion offerings from its proposed $60 billion program and understand what the financing means for AI infrastructure buyers.
How to Cost Your AI-Powered Filters

Technical article · FS Data Lab · Advanced

FS Data Lab published this guide on October 1, 2026. Use it when you want a rigorous way to estimate GPU latency and inference cost for AI-powered SQL filters, compare filter orderings, and understand how compute, memory bandwidth, selectivity, batching, and KV-cache reuse affect a query plan.
Ragas

RAG and AI-application evaluation library · Vibrant Labs · Intermediate to advanced

Evaluating retrieval quality, grounded generation, agent tool use, and production-aligned test data for RAG applications.

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About this guide

Author: Learnetto Editorial Team. Learnetto maintains this AI learning directory by organizing public course pages, official documentation, educator material, and practical learning resources.

How it is made: Learnetto uses public course pages, official documentation, educator material, and directory data to compile these recommendations. AI may help draft and organize the page, but recommendations are checked against the listed sources, page topic, and learner intent.

Review policy: We only add a named personal reviewer when that person has substantially reviewed the page. Until then, the page is attributed to Learnetto rather than a founder, editor, or individual expert.

Last updated: October 7, 2026. Suggest a correction if a course, doc, or recommendation is outdated.

Videos to watch

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Scaling Inference-Time Compute with Teams of Agents for Software Engineering

Open Data Science and AI Conference

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AI Cut Our Research Time From 7 Days to 15 Minutes — Gareth Yoder, Vanguard

AI Engineer

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Insurance Claims Are AI's Messiest Data Problem — Denys Linkov, Wisedocs

AI Engineer

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Building AI Agents with Real-Time Web Data — Yohan Raju, Bright Data

AI Engineer

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Why Learn Machine Learning When AI Can Do It All?

Machine Learning Pills

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The Lethal Trifecta Is Already on Your Laptops — Michael Patterson, Coder

AI Engineer

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From 15% to 90% GPU Utilization: Fix the Data Pipeline, Not the Model

AI Engineer

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Why Your Company Needs a Context Graph (and How to Build It) — Gil Feig, Merge

AI Engineer

Educators and sources

Educator / source	Best for	Skills	Start with
Rachel Thomas fast.ai	Developers, data scientists	Practical ML, Ethics, Education	Use fast.ai essays and course material alongside hands-on notebooks.
Jason Liu Instructor	Developers building LLM apps	Structured outputs, Extraction, RAG	Try the Instructor examples for extraction and validation.
Eugene Yan Eugene Yan	ML engineers, data teams	Applied ML, Recommenders, LLM systems	Read the applied ML and LLM systems posts.
Christopher Penn Trust Insights	Marketers, analysts, business leaders	AI marketing analytics, Prompting, Data strategy, Measurement	Find a generative AI or analytics workflow and run it on your own marketing data.
Rand Fishkin SparkToro	Marketers, founders, audience researchers	AI search, Audience research, Marketing strategy, Content quality	Use AI as an analysis assistant after gathering audience data, not as a substitute for research.
Chase Dimond Email marketing and AI workflows	Ecommerce marketers, email marketers, founders	AI email marketing, Lifecycle campaigns, Copywriting, Ecommerce	Use AI to draft variants for one email campaign, then edit with performance data in mind.
Jerry Liu LlamaIndex	Developers building RAG and document agents	RAG, Agents, Document workflows, Context augmentation	Read the LlamaIndex introduction, then build a small document Q&A app.
Ben Lorica The Data Exchange	Data and AI practitioners	Data systems, ML engineering, AI trends	Search episodes by topic: RAG, evaluation, agents, MLOps.
Greg Kamradt Data Independent AI tutorials	Developers learning RAG and LLM apps	RAG, LLM apps, Prompting, Evaluation	Search the channel for the RAG or LangChain workflow you are building.
Connor Shorten Weaviate education videos	Developers learning retrieval	Vector search, RAG, Hybrid search, Agents	Use Weaviate videos on hybrid search and RAG basics.
Tina Huang Tina Huang AI and data career videos	Beginners and career switchers	AI literacy, Data skills, Career learning, Prompting	Use beginner learning-roadmap videos to choose a first path.
Krish Naik Krish Naik AI tutorials	Developers and data science learners	Machine learning, Deep learning, LLM apps, MLOps	Pick a playlist that matches your current level and follow the code.
Sean Grove OpenAI and AI engineering talks	AI engineers and product builders	AI engineering, Developer tools, Agents, Structured data	Watch talks on AI-native interfaces and structured workflows.

Resources

Warp agent-log breach response guide

AI developer-tool security analysis · Warp · Intermediate

Assess Warp's vendor breach, identify exposed agent data and decide which logs, credentials and integrations need review.

OpenAI Signals work dataset explained

AI work data analysis · OpenAI · Beginner to intermediate

You want to interpret OpenAI's October 26 dataset on consumer ChatGPT work use without treating message shares as employment, productivity or job-displacement evidence.

Meta $95B AI equity financing explained

AI infrastructure financing analysis · Meta · Intermediate

You want to separate Meta's launched $35 billion offerings from its proposed $60 billion program and understand what the financing means for AI infrastructure buyers.

How to Cost Your AI-Powered Filters

Technical article · FS Data Lab · Advanced

FS Data Lab published this guide on October 1, 2026. Use it when you want a rigorous way to estimate GPU latency and inference cost for AI-powered SQL filters, compare filter orderings, and understand how compute, memory bandwidth, selectivity, batching, and KV-cache reuse affect a query plan.

Ragas

RAG and AI-application evaluation library · Vibrant Labs · Intermediate to advanced

Evaluating retrieval quality, grounded generation, agent tool use, and production-aligned test data for RAG applications.

Arize Phoenix

AI observability and evaluation platform · Arize AI · Intermediate to advanced

Teams that want evaluation connected to OpenTelemetry traces, datasets, experiments, prompt iterations, and production troubleshooting.

Braintrust

AI evaluation and observability platform · Braintrust Data · Intermediate to advanced

Teams that want a feedback loop from production traces and failures into datasets, regression experiments, CI gates, and continuous scoring.

LangSmith

Agent evaluation and observability platform · LangChain · Intermediate to advanced

Agent teams, especially LangChain and LangGraph users, that need tracing, datasets, experiments, human review, and production feedback in one system.

Langfuse

Open-source evals and observability platform · ClickHouse · Intermediate to advanced

Teams prioritizing open-source data control and one workflow across tracing, prompts, datasets, experiments, annotation, and evaluation.

W&B Weave

LLM and agent evaluation platform · Weights & Biases · Intermediate to advanced

Teams already using Weights & Biases or wanting versioned datasets, scorers, traces, and evaluation comparisons in an experiment-oriented workflow.

OpenAI Evals

Hosted LLM and agent evaluation API · OpenAI · Intermediate to advanced

Existing OpenAI API teams maintaining dataset-based prompt or model regression tests during the remaining service window.

Anthropic evaluation guide

Evaluation methodology guide · Anthropic · Intermediate to advanced

Teams designing task-specific evaluation suites for Claude applications that need criteria, datasets, edge cases, grading patterns, and code examples.

Patronus AI

AI research lab · Patronus AI · All levels

Patronus AI is a research lab developing training data and simulated environments for frontier AI. Its work spans reinforcement learning environments and digital world models for agents operating in software.

Introduction to Security in the World of AI

Course · Google Cloud · Beginner

Use this one-hour course when security and data-protection leaders need a framework for identifying AI-specific risks, protecting sensitive data, and applying Google's Secure AI Framework.

Google Data Analytics Certificate

Professional certificate · Google · Beginner

Use this foundational certificate program to build job-ready data analytics skills and learn how AI can support analysis, visualization, and workflow productivity.

ChatGPT Finances privacy and accuracy guide

Connected-finance safety guide · OpenAI · Beginner

OpenAI announced on October 2, 2026 that ChatGPT Finances is rolling out to Free and Go users in the United States. Use this guide to understand the connected-account workflow, check the source data behind answers, and review privacy controls before linking an account.