For data scientists

Skip the intro. Learn from the people who wrote the book.

You're fed up of yet another 'Intro to Pandas' course. Get the cookbooks and deep dives from the authors already on your desk, from $10 a month.

Free for 7 days. Valid card required. Cancel anytime.

Oluleye
Cover image for Exploratory Data Analysis with Python Cookbook
Deka
Cover image for XGBoost for Regression Predictive Modeling and Time Series Analysis
Ayd
Cover image for Pandas Cookbook
Chadha
Cover image for Data Engineering with Databricks Cookbook
Aranha
Cover image for Algorithm Alchemy - Unlocking the Secrets of Machine Learning

Sound familiar?

You've taken this course before

You've done the one with the clean CSV and the fill-in-the-blank cell. Here's the same lesson, the way our authors teach it.

The course you've taken

Intro to Machine Learning · Lesson 4 · recorded 2016

import pandas as pd
from sklearn.cross_validation import train_test_split1
df = pd.read_csv("iris.csv")2
X, y = df.drop(columns="species"), df["species"]
model = ____(n_estimators=100)3
model.fit(X, y)
The same lesson on ExpertEdge

Cookbook recipe · current edition

from sklearn.model_selection import train_test_split1
orders = pd.read_parquet("orders.parquet")
df = orders.merge(customers, on="customer_id")2
df["spend"] = df["spend"].fillna(df["spend"].median())
X_train, X_test, y_train, y_test = train_test_split(
X, y, stratify=y
)
model = RandomForestClassifier(class_weight="balanced")3
model.fit(X_train, y_train)
  1. 1

    A module removed in 2018

    Everybody else

    The video still teaches sklearn.cross_validation, years after it was dropped.

    ExpertEdge

    The library tracks new editions. Every title shows when it was published.

  2. 2

    Data that cleaned itself

    Everybody else

    150 rows, no nulls, no joins. Nothing like the tables you get at work.

    ExpertEdge

    Cookbooks start where real data does, with joins, gaps and types to fix.

  3. 3

    One blank to fill in

    Everybody else

    You type one word, the cell turns green, and you still can't start from an empty notebook.

    ExpertEdge

    Every recipe is written out in full, by someone who does this for a living.

Where does the code run?

No training wheels. You run it on your own machine.

Browser labs set everything up for you, then vanish when the course ends. Here you install, run and version your own work, the way you do at your job.

Everybody else
labs.course-site.com/session/4821

Session ends in 00:59:32

  • pandas 1.1 preinstalled
  • Files reset when you close the tab
  • No git, no terminal
ExpertEdge

~/work/churn · zsh

$ python -m venv .venv && source .venv/bin/activate
$ pip install -r requirements.txt
$ jupyter lab
$ git commit -am "Churn model, v2"

Your laptop, your versions, your git history. Everything you build is still there next week.

Why does this keep happening?

Most courses are made for beginners

Marketplaces earn per enrolment. Beginners are the biggest market, so that's what gets made. Most of the ExpertEdge library is written for people past the basics.

Best data science courses of 2026

Class Central

67%
20%
13%

ExpertEdge data science, ML and AI titles

31%
60%
9%
  • Beginner
  • Intermediate
  • Advanced
Most courses are made for beginners
SourceBeginnerIntermediateAdvanced
Best data science courses of 20261032
ExpertEdge data science, ML and AI titles17633750

Who's teaching?

Learn from the authors already on your desk

Cookbooks and deep dives, written by the people who built the tools or use them every day.

  • Cover image for Pandas Cookbook
    William Ayd, author of Pandas Cookbook

    William Ayd

    Pandas recipes from one of the core maintainers of pandas.

  • Cover image for XGBoost for Regression Predictive Modeling and Time Series Analysis
    Joyce Weiner, author of XGBoost for Regression Predictive Modeling and Time Series Analysis

    Joyce Weiner

    XGBoost from first model to deployment, by a principal engineer at Intel.

  • Cover image for Algorithm Alchemy - Unlocking the Secrets of Machine Learning
    Vivian Aranha, author of Algorithm Alchemy - Unlocking the Secrets of Machine Learning

    Vivian Aranha

    Each machine learning algorithm built from scratch in Python.

    21 titlesProfile
  • Cover image for Ultimate AWS Data Engineering Bootcamp - 15 Real-World Labs
    Siddharth Raghunath, author of Ultimate AWS Data Engineering Bootcamp - 15 Real-World Labs

    Siddharth Raghunath

    Fifteen labs that build working data pipelines on AWS.

    5 titlesProfile

Where do I go next?

Pick a target and we'll put the skills in order

No more 47 bookmarked tutorials. Set Data Scientist as your target and ExpertEdge lays out the skills it asks for, one at a time.

  1. The basics

    Where you are

  2. Data Analysis Workflows & Tools

  3. Data Ingestion & Transformation (ETL)

  4. Data Visualization Tools & Techniques

  5. Data Warehousing & Big Data

  6. Database Technologies & Administration

  7. Statistical Analysis & Predictive Modeling

  8. Supervised & Unsupervised Learning

  9. Data Scientist

    The goal

What about AI?

The job ad changed. You don't have to.

You've got the stats, the SQL and the models. Now every posting asks for AI as well. Learn the new stuff without starting over.

The posting you saw this week

jobs.example.com/senior-data-scientist

Senior Data Scientist

Posted this week

  • Python and SQL
  • Statistics and experiments
  • Machine learning
  • AI-assisted analytics1
  • Models on Kubernetes2
  • Explainable models3

323

AI titles in the same subscription

  1. 1

    AI-assisted analytics

    Everybody else

    A demo of the AI button on a sample workbook.

    ExpertEdge

    Learning Tableau 2025 gives Tableau Agent and Pulse a full chapter.

  2. 2

    Models on Kubernetes

    Everybody else

    Recorded before the framework changed again.

    ExpertEdge

    Big Data on Kubernetes has a chapter on running AI and ML workloads.

  3. 3

    Explainable models

    Everybody else

    Shows the accuracy score, then skips the why.

    ExpertEdge

    The XGBoost course shows how to explain a prediction with SHAP and LIME.

By design

What we left out on purpose

  • Your own pace

    Learn from the people who wrote the standard texts, for far less than a bootcamp.

  • Your own projects

    Every technique lands on your own data the same day. That's where it sticks.

  • Past the basics

    We assume you know the basics. The library starts where most courses stop.

Keep your real projects. We'll make sure the next thing you learn is worth your time.

And the price?

One price, everything included

Monthly

Billed monthly

$15per month

Everything, month to month. Cancel anytime.

What's included

  • Every data science, ML and AI title
  • The whole course library
  • Skills and a passport that stay yours
Start Free Trial

Annual

Billed yearly ($120)

$10per month

Everything for a third less, paid once a year.

What's included

  • Every data science, ML and AI title
  • The whole course library
  • Skills and a passport that stay yours
Start Free Trial

No setup fees, no minimum seats. Invoicing available on plans of 20+ seats or more.

Comparing options? Read how ExpertEdge stacks up against Udemy Business, LinkedIn Learning, Coursera and edX in our comparisons

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Still not convinced ExpertEdge is the right fit for you? Review some of our thinking on enterprise learning, content strategy and more. See if we align via the full blog.

Content Strategy

The B2B learning content stack most enterprises miss

Enterprise L&D teams have approached content procurement the wrong way for a decade. What a mature B2B learning content stack looks like, and the layers most enterprises are missing.

Oli Huggins

Oli Huggins

CEO and Founder

Comparisons

ExpertEdge vs Coursera and edX for B2B learning

A side-by-side of Coursera, edX and ExpertEdge for enterprise learning content: what each does well, where each falls short, and how to choose.

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Oli Huggins

CEO and Founder