Course Outline

  1. Data preprocessing

    1. Data Cleaning
    2. Data integration and transformation
    3. Data reduction
    4. Discretization and concept hierarchy generation
  2. Statistical inference

    1. Probability distributions, Random variables, Central limit theorem
    2. Sampling
    3. Confidence intervals
    4. Statistical Inference
    5. Hypothesis testing
  3. Multivariate linear regression

    1. Specification
    2. Subset selection
    3. Estimation
    4. Validation
    5. Prediction
  4. Classification methods

    1. Logistic regression
    2. Linear discriminant analysis
    3. K-nearest neighbours
    4. Naive Bayes
    5. Comparison of Classification methods
  5. Neural Networks

    1. Fitting neural networks
    2. Training neural networks issues
  6. Decision trees

    1. Regression trees
    2. Classification trees
    3. Trees Versus Linear Models
  7. Bagging, Random Forests, Boosting

    1. Bagging
    2. Random Forests
    3. Boosting
  8. Support Vector Machines and Flexible disct

    1. Maximal Margin classifier
    2. Support vector classifiers
    3. Support vector machines
    4. 2 and more classes SVM’s
    5. Relationship to logistic regression
  9. Principal Components Analysis

  10. Clustering

    1. K-means clustering
    2. K-medoids clustering
    3. Hierarchical clustering
    4. Density based clustering
  11. Model Assesment and Selection

    1. Bias, Variance and Model complexity
    2. In-sample prediction error
    3. The Bayesian approach
    4. Cross-validation
    5. Bootstrap methods
 28 Hours

Delivery Options

Private Group Training

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    • Bespoke outlines
    • Practical hands-on exercises containing data / scenarios recognisable to the learners
  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from €9120 online delivery, based on a group of 2 delegates, €2880 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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