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Video course · 15 chapters · 168 min · certificate

End-to-End Machine Learning Project – AI, MLOps

Ayushi Singh's freeCodeCamp end-to-end ML project: a house-price predictor built with clean, scalable code using factory, strategy and template design patterns, deep exploratory analysis, ingestion, missing values, feature engineering, outliers, model building, MLflow tracking, ZenML pipelines, deployment and inference.

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What you'll learn

  • Structure an ML project with factory, strategy and template patterns
  • Ingest and inspect data cleanly
  • Run univariate, bivariate and multivariate analysis
  • Build a pipeline for missing values, features and outliers
  • Train and evaluate a regression model
  • Track with MLflow and deploy with ZenML

Chapters

15 chapters · 168:13
  1. 3:22 01Intro Members Project introduction Core ML plus MLOps.
  2. 10:26 02Roadmap Members Project roadmap Differentiate a simple project.
  3. 8:34 03Patterns Members Factory design pattern Create objects cleanly.
  4. 10:09 04Ingestion Members Data ingestion implementation From ZIP to DataFrame.
  5. 9:37 05EDA Members Julius AI and the strategy pattern Think before plotting.
  6. 13:45 06Inspection Members Basic data inspection Know your data.
  7. 12:37 07Missing data Members Template pattern and missing values Plan, then implement.
  8. 9:36 08Univariate Members Univariate analysis One variable at a time.
  9. 9:17 09Bivariate Members Bivariate analysis Relationships.
  10. 10:40 10Multivariate Members Multivariate analysis Correlations.
  11. 14:25 11Pipeline Members Data pipeline setup Ingest and handle gaps.
  12. 8:13 12Features Members Feature engineering and cleaning Fix skew.
  13. 7:10 13Prep Members Outliers and data splitting Clean and split.
  14. 20:12 14Model Members Model building and MLflow Train and track.
  15. 20:10 15Deploy Members Deployment and inference Serve predictions.

Jobs this course suits

Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.

Machine Learning EngineersAI EngineersData Scientists