Statistics is the foundation of every AI model. This course teaches the concepts that actually matter — not proofs, but intuition and application. With Python code for every idea.
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from scipy import stats # Day 3: Did this feature improve conversion? control = [0.042, 0.039, 0.044, 0.041] treatment = [0.051, 0.049, 0.055, 0.053] t_stat, p_value = stats.ttest_ind(control, treatment) print(f"p-value: {p_value:.4f}") if p_value < 0.05: print("Significant — ship the feature") else: print("Not significant — need more data")
Most stats textbooks bury the intuition under notation. This course starts with the question you're trying to answer, then shows you the math that helps answer it.
Before every formula, we explain what question it answers. You'll understand what a p-value means and why it's so frequently misused — without memorizing a single proof.
Every concept has working Python code using numpy, scipy, and statsmodels. You're not just learning theory — you're running calculations and seeing the output.
Day 5 connects statistics to AI: when to trust model outputs, what evaluation metrics mean, how to detect data drift, and why sample size matters more than accuracy.
Summarize data with measures of center and spread. Understand mean vs. median. Calculate variance and standard deviation. Visualize distributions with histograms.
Understand probability basics, conditional probability, independence. Learn the normal, binomial, and Poisson distributions. Why the central limit theorem is the most important theorem in statistics.
Set up and run a t-test. Understand null and alternative hypotheses. Calculate p-values correctly. Build confidence intervals. Detect when A/B test results are real.
Fit a linear regression model and interpret coefficients. Build a logistic regression model for classification. Understand R-squared, residuals, and when regression breaks down.
Connect statistics to AI evaluation. Understand accuracy vs. precision vs. recall. Detect overfitting. Handle class imbalance. Know when your model is lying to you.
All 5 days free. Forever. No paywall.
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Three days of intensive, hands-on AI training. Build production systems with real data, real APIs, and a cohort of peers. $1,490 all-in. Coming to 5 cities in October 2026.