Guided path
Data Science
Build the statistical, computational and experimental skills required to move from exploratory analysis to leakage-safe predictive modelling and interpretation.
48 core steps87 detailed lessons12 modules
01
02
Module 2 · 7 detailed lessons
Python, NumPy & pandas
1
Browse all 7 lessons in this module →NumPy ArraysPython · Workflow
Open →2Dataframe OperationsPython · Workflow
Open →3Missing DataPython · Missing
Open →4Dates and CategoriesPython · Workflow
Open →03
04
05
06
07
Module 7 · 7 detailed lessons
Feature Engineering
1
Browse all 7 lessons in this module →Domain FeaturesPython · Workflow
Open →2Datetime FeaturesPython · Workflow
Open →3Text TF IDF IntuitionPython · Workflow
Open →4PCAPython · Pca
Open →08
Module 8 · 8 detailed lessons
Experimental Design & Validation
1
Browse all 8 lessons in this module →Train Validation TestPython · Split
Open →2StratificationPython · Split
Open →3Nested CvPython · Split
Open →4Leakage Safe PipelinesPython · Split
Open →09
10
Module 10 · 8 detailed lessons
Evaluation & Diagnostics
1
Browse all 8 lessons in this module →Classification MetricsPython · Classification
Open →2Regression MetricsPython · Regression
Open →3ThresholdsPython · Classification
Open →4Subgroup EvaluationPython · Workflow
Open →11
Module 11 · 7 detailed lessons
Interpretation & Communication
1
Browse all 7 lessons in this module →Coefficients and Feature ImportancePython · Workflow
Open →2PDP and ICEPython · Workflow
Open →3Model CardsPython · Workflow
Open →4Decision RecommendationsPython · Workflow
Open →12