Course modules

Planning

Planning
Module completed Module in progress Module locked
Planning 109213  
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    Plan for the course Plan for the course
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Projects

Projects
Module completed Module in progress Module locked
Projects 109215  
  • Page
    Updated: General instructions for projects Updated: General instructions for projects
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  • Context Module Subheader

    Project 1

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  • Attachment
    project1R.ipynb project1R.ipynb
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  • Attachment
    project1Py.ipynb project1Py.ipynb
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  • Attachment
    mnist_large.zip mnist_large.zip
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  • Attachment
    A-survey-on-addressing-high‑class-imbalance.pdf A-survey-on-addressing-high‑class-imbalance.pdf
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  • Context Module Subheader

    Project 2

    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   Score at least  % Must score at least  % to complete this module item Scored at least  % Module item has been completed by scoring at least  % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Context Module Subheader

    Project 3

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Additional Material

Additional Material
Module completed Module in progress Module locked
Additional Material 109216  
  • Attachment
    [Python] Programming tips and common mistakes [Python] Programming tips and common mistakes
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  • Attachment
    [Python, Jupyter Notebook] Programming tips and common mistakes [Python, Jupyter Notebook] Programming tips and common mistakes
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  • Attachment
    [R] Programming tips and common mistakes [R] Programming tips and common mistakes
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   Score at least  % Must score at least  % to complete this module item Scored at least  % Module item has been completed by scoring at least  % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    [R, Jupyter Notebook] Programming tips and common mistakes [R, Jupyter Notebook] Programming tips and common mistakes
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   Score at least  % Must score at least  % to complete this module item Scored at least  % Module item has been completed by scoring at least  % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete

Week 1, Introduction: classification, dimension reduction, performance evaluation.

Week 1, Introduction: classification, dimension reduction, performance evaluation.
Module completed Module in progress Module locked
Week 1, Introduction: classification, dimension reduction, performance evaluation. 109217  
  • Page
    Lecture 1 - Recommended Reading Lecture 1 - Recommended Reading
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  • Page
    Lecture 2&3 - Recommended Reading Lecture 2&3 - Recommended Reading
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  • Attachment
    Intro2026.pdf Intro2026.pdf
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  • Attachment
    Lecture1-2026.pdf Lecture1-2026.pdf
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  • Context Module Subheader

    Lecture 2

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  • Attachment
    Lecture2a-2026.pdf Lecture2a-2026.pdf
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   Score at least  % Must score at least  % to complete this module item Scored at least  % Module item has been completed by scoring at least  % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    Lecture2b-2026.pdf Lecture2b-2026.pdf
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  • Context Module Subheader

    Demo 1

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  • Context Module Subheader

    Updated Demo1 code for better visualization

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  • Attachment
    Demo1-2026.ipynb Demo1-2026.ipynb
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  • Attachment
    Demo1-2026 (2).html Demo1-2026 (2).html
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  • Attachment
    Demo1-2026-Python.ipynb Demo1-2026-Python.ipynb
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  • Attachment
    Demo1-2026-Python (2).html Demo1-2026-Python (2).html
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  • Context Module Subheader

    Lecture 3

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  • Attachment
    Lecture2b-update.pdf Lecture2b-update.pdf
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  • Attachment
    Lecture3-2026.pdf Lecture3-2026.pdf
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  • Context Module Subheader

    Demo 2

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  • Attachment
    DimensionReduction-2026.ipynb DimensionReduction-2026.ipynb
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   Score at least  % Must score at least  % to complete this module item Scored at least  % Module item has been completed by scoring at least  % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    DimensionReduction-2026-Python (1).ipynb DimensionReduction-2026-Python (1).ipynb
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Week 2: Dimension reduction, filtering, Analysis pipeline

Week 2: Dimension reduction, filtering, Analysis pipeline
Module completed Module in progress Module locked
Week 2: Dimension reduction, filtering, Analysis pipeline 109218  
  • Page
    Recommended reading - dimension reduction Recommended reading - dimension reduction
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  • Attachment
    SVMs.ipynb SVMs.ipynb
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  • Attachment
    ConstrainedOptimization.pdf ConstrainedOptimization.pdf
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  • Attachment
    Lecture4-2026.pdf Lecture4-2026.pdf
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  • Attachment
    IntroLocalDimRedR.ipynb IntroLocalDimRedR.ipynb
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  • Attachment
    IntroLocalDimRedPy.ipynb IntroLocalDimRedPy.ipynb
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  • Attachment
    kPCAdemoR-2026.ipynb kPCAdemoR-2026.ipynb
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  • Attachment
    kPCAdemoPy-2026.ipynb kPCAdemoPy-2026.ipynb
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  • Page
    TSNE-UMAP TSNE-UMAP
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  • Attachment
    tsnevsumap.ipynb tsnevsumap.ipynb
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Week 3: Trees, Boosting, SVMs

Week 3: Trees, Boosting, SVMs
Module completed Module in progress Module locked
Week 3: Trees, Boosting, SVMs 109219  
  • Page
    Recommended Reading - Tree-based methods Recommended Reading - Tree-based methods
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  • Context Module Subheader

    Extra reading (not compulsory): Paper on why bagging improves unstable estimators

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  • Attachment
    AnalyzingBagging.pdf Talks about how you bootstrap aggregating "smooths" hard decisions/unstable estimators, AnalyzingBagging.pdf Talks about how you bootstrap aggregating "smooths" hard decisions/unstable estimators,
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  • Attachment
    SVMs.ipynb SVMs.ipynb
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  • Attachment
    NNfromscratch.ipynb NNfromscratch.ipynb
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  • Attachment
    CARTandRandomForest.pdf CARTandRandomForest.pdf
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  • Attachment
    CARTBaggingRF.ipynb CARTBaggingRF.ipynb
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  • Attachment
    CARTBaggingRF_Python.ipynb CARTBaggingRF_Python.ipynb
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  • Page
    Recommended reading - kernels etc Recommended reading - kernels etc
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  • Attachment
    KernelMethods.pdf KernelMethods.pdf
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  • Context Module Subheader

    Optimal reading: paper on highdimensional regression

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  • Attachment
    SURPRISES IN HIGH-DIMENSIONAL RIDGELESS LEAST SQUARES INTERPOLATION SURPRISES IN HIGH-DIMENSIONAL RIDGELESS LEAST SQUARES INTERPOLATION
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  • Context Module Subheader

    Demos

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  • Attachment
    kRR_demoPy.ipynb kRR_demoPy.ipynb
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  • Attachment
    kRR_demoR.ipynb kRR_demoR.ipynb
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  • Attachment
    KRRGDdemoPy.ipynb KRRGDdemoPy.ipynb
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  • Attachment
    KRRGDdemoR.ipynb KRRGDdemoR.ipynb
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  • Attachment
    RegressionGDstartingfrom0Python.ipynb RegressionGDstartingfrom0Python.ipynb
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  • Attachment
    RegressionGDstartingfrom0R.ipynb RegressionGDstartingfrom0R.ipynb
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  • Page
    Recommended reading - Boosting, SVMs Recommended reading - Boosting, SVMs
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  • Attachment
    Boosting1.pdf Boosting1.pdf
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  • Attachment
    GBMdemoPy.ipynb GBMdemoPy.ipynb
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  • Attachment
    GBMdemoR.ipynb GBMdemoR.ipynb
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  • Attachment
    BoostingSVMandFLDA.pdf BoostingSVMandFLDA.pdf
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  • Attachment
    ConstrainedOptimization.pdf ConstrainedOptimization.pdf
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  • Attachment
    BoostingComparison_MNIST.ipynb BoostingComparison_MNIST.ipynb
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  • Attachment
    SVMs.ipynb SVMs.ipynb
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  • Attachment
    SVMs_Python.ipynb SVMs_Python.ipynb
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Week 4: NNs, Feature Selection

Week 4: NNs, Feature Selection
Module completed Module in progress Module locked
Week 4: NNs, Feature Selection 109220  
  • Page
    Recommended reading Neural networks Recommended reading Neural networks
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  • Attachment
    NN2026.pdf NN2026.pdf
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  • Context Module Subheader

    Demos - for illustration - use other NN packages in your pipelines

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  • Attachment
    NNfromscratch.ipynb NNfromscratch.ipynb
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  • Attachment
    NNfromscratch_Python.ipynb NNfromscratch_Python.ipynb
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Week 5: Feature selection, continued

Week 5: Feature selection, continued
Module completed Module in progress Module locked
Week 5: Feature selection, continued 109221  

Week 6: Conformal predictions, UQ

Week 6: Conformal predictions, UQ
Module completed Module in progress Module locked
Week 6: Conformal predictions, UQ 109222  

Week 7: Project 2 - no lectures

Week 7: Project 2 - no lectures
Module completed Module in progress Module locked
Week 7: Project 2 - no lectures 109223  

Week 8: Conformal predictions, local explanations and Clustering

Week 8: Conformal predictions, local explanations and Clustering
Module completed Module in progress Module locked
Week 8: Conformal predictions, local explanations and Clustering 109224  

Week 9: More on clustering, Review

Week 9: More on clustering, Review
Module completed Module in progress Module locked
Week 9: More on clustering, Review 109225  
 
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