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Choose a role, build the skills in order, and solve real SQL and Python problems. LDS connects your roadmap, practice, feedback, recall, and AI news so you always know what to do next.

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1,625graded problemsSQL + Python with instant feedback

17guided coursesFrom foundations to AI agents

556active recall cardsKeep key concepts ready

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LDS / one connected learning system 9 connected tools

Start with your goalYour next useful step is already here.

Choose what you need today. Every tool leads to the next.

ChooseLearnPracticeRememberStay current

Choose your route

Start with the goal that matters now.

Whether you are breaking in, growing on the job, or keeping up with AI, LDS connects the right tools in a clear sequence.

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Build the skills employers expect.

Choose a target role, follow the skill order, and turn each concept into hands-on practice.

16 career paths17 courses1,625 problems

Choose my path

I already work in data

Close gaps before they slow you down.

Practice harder SQL and Python, get targeted Mentor help, and revisit the concepts that do not stick.

1,625 problemsLDS Mentor556 recall cards

Strengthen my skills

I want to stay ahead

Know what changed and why it matters.

Read source-linked AI news, add historical context, and test what you retained with fresh games.

Live AI news433-record archive4 news games

See today's signal

One learning loop

LearnPracticeRememberExplorePlayStay current

Practice the skills used across leading data teams

SQL and Python practice

Solve SQL and Python. Know when your answer works.

Practice 1,625 graded problems across 15 realistic industry datasets. Run your code, inspect the result, and get immediate feedback in the browser.

816 SQL problems·809 Python problems·15 industry datasets

Create a free account to save your progress.

query.sql ACCEPTED

SELECT

c.campaign_name,

SUM(i.cost) AS total_spend,

COUNT(DISTINCT cl.click_id) AS clicks

FROM campaigns c

JOIN impressions i ON c.id = i.campaign_id

LEFT JOIN clicks cl ON i.id = cl.impression_id

WHERE c.status = 'active'

GROUP BY c.campaign_name

ORDER BY total_spend DESC;

3 rows · 6ms

campaign_name	total_spend	clicks
Holiday Push	42,850	1,247
Brand Awareness	38,200	982
Retarget Q4	25,600	654

solve.py ACCEPTED

import pandas as pd

import numpy as np

def solve(campaigns, impressions, clicks):

active = campaigns[campaigns['status'] == 'active']

df = (active

.merge(impressions, on='campaign_id')

.merge(clicks, on='impression_id', how='left'))

return (df

.groupby('campaign_name')

.agg(total_spend=('cost','sum'), clicks=('click_id','nunique'))

.sort_values('total_spend', ascending=False)

.reset_index())

3 rows · 42ms

campaign_name	total_spend	clicks
Holiday Push	42,850	1,247
Brand Awareness	38,200	982
Retarget Q4	25,600	654

Explore the problem library

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Code visualizer

See what your code changes, step by step.

Run each SQL clause or Python operation in sequence and watch the result update. Understand why the code works, not just whether it passes.

SQL, step by step

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Python, step by step

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Try the visualizer on a problem

Active recall

Turn weak concepts into fast recall.

Review 556 cards across six core skill areas, then reinforce SQL with 33 short lessons and 71 live-editor exercises.

Interview recall cards

556 cards · 6 skill areas · Built for active recall

Review cards

SQL

96 cards

JoinsWindow FnsCTEsAggregations

Python & Pandas

111 cards

OOPDataFramesNumPyFile I/O

Statistics

83 cards

HypothesisBayesianA/B TestsProbability

Machine Learning

117 cards

Deep LearningFeature EngMLOpsEvaluation

LLMs & GenAI

89 cards

RAGFine-tuningAgentsPrompting

System Design

60 cards

ScaleReliabilityPipelinesTrade-offs

SQL recall practice

33 short lessons · 71 exercises · Live SQL editor

Practice SQL

Foundations

SELECT, WHERE, ORDER BY

Joins

INNER, LEFT, Self Joins

Aggregations

GROUP BY, HAVING, COUNT

Window Fns

ROW_NUMBER, RANK, LAG

Date Fns, Time Periods

String & Sets

UNION, String Fns

Advanced

Top-N, Pivoting, Series

Optimization

Indexes, Anti-patterns

Learn Arcade

Turn difficult concepts into a practice habit.

Nine short games make you retrieve, connect, and apply AI, machine learning, statistics, and data concepts across 831 levels.

9 focused games831 progressive levels41 earnable badges

The practice floor Cabinets online

Relationship reasoningConcept LinkPlay a level

Technical vocabularyLexiconPlay a level

Vocabulary recallArcade MiniPlay a level

Guided courses

Build from fundamentals to modern AI.

Follow 17 interactive courses across SQL, Python, statistics, machine learning, LLMs, RAG, agents, and evals.

7 courses are completely free. Every Pro course starts with a free first module.

LLM Foundations

Free·8 modules · ~8h

Tokens, attention, transformer blocks, training, inference, post-training, and interpretability.

M1/8

TokensAttentionTransformersInterpretability

Building RAG Systems & Vector Search

Pro·8 modules · ~9h

BM25, embeddings, chunking, hybrid search, ANN indexes, reranking, grounding, and RAG evals.

M1/8

RAGEmbeddingsHybrid SearchReranking

Building AI Agents

Pro·8 modules · ~9h

Agent loops, tools, planning, reflection, memory, multi-agent systems, evaluation, and guardrails.

M1/8

AgentsTool UsePlanningGuardrails

AI Evals: Test, Measure & Ship LLM Apps

Pro·8 modules · ~9h

Analyze funnels, experiments, retention, pricing, and product behavior to improve user outcomes.

SQLA/B testingFunnelsRetention

7 stages · 6-10 monthsOpen roadmap

Compare all 16 career paths

History Archive

See how today's ideas were built.

Trace the papers, people, debates, failures, and breakthroughs behind modern data and AI across 433 researched records.

714 source links connect each timeline to original research and archives.

Researched records: 433
Cited sources: 714
Curated eras: 48
Topic collections: 8

Explore the archive

Research archiveSource-linked edition

08Topic collections

Researched records433Cited sources714Curated eras48

AI-001Artificial intelligence52 records
ML-001Machine learning45 records
LM-001Large language models45 records
RC-001RAG, memory, and context72 records
GM-001Generative and multimodal AI50 records
AG-001AI agents45 records
DB-001Databases and SQL58 records
ST-001Statistics and probability66 records

Follow the breakthroughs

1956Dartmouth1997Deep Blue2012AlexNet2017Transformers2022ChatGPT

AI news and games

Know what changed. Prove what you retained.

Scan relevance-scored AI news with source links, then turn today's stories into a quiz, word game, mini, or weekly crossword.

Live AI news Updating

5.6Google Redesigns Android Voice Search Interface20m ago 5.9Oak Felder and Lucas Keller Sue SoundPatrol Over AI Copyright Tool1h ago 6.5ISBNdb Pitched Pre-LLM Books for AI Training, Then Pivoted Away2h ago 4.6Bayreuth's AI-Assisted Wagner Ring Staging Draws Boos4h ago

Read the latest AI news Relevance scored. Sources included.

Today's AI games4 formats

AI News Quiz

AI Word

AI Mini

Fair competition

Consistency earns a place on the leaderboard.

Server-scored runs. Fair-play review. Clear rules before rewards.

01Daily and monthly rankings02Hints and flagged runs reviewed03Prize rules published before launch

Monthly prizes are plannedDates and rules will be announced firstView current standings

Want the deeper explanation?

Ray's Creators Just Sold for $1.65 Billion. Their 2022 Valuation Was Only 16% Lower.9 min read OpenAI Dropped Luna's Price by 80%. Its Own Model Wrote the Code Behind the Cut.9 min read

Industry datasets

Practice across 15 real-world industry settings.

Work with data models inspired by advertising, banking, healthcare, logistics, payments, SaaS, streaming, telecom, and more.

Start free

Pick one problem. Build from there.

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