Course Info

Date: Sep-09-2024

Length: 1 Week

City: Singapore

Fees: 4,590

Type: In Classroom

Available Dates

  • May-13-2024

    Singapore

  • June-10-2024

    Singapore

  • July-08-2024

    Singapore

  • Aug-12-2024

    Singapore

  • Sep-09-2024

    Singapore

  • Oct-14-2024

    Singapore

  • Nov-11-2024

    Singapore

  • Dec-09-2024

    Singapore

Dates in Other Venues

  • May-06-2024

    Kuala Lumpur

  • May-06-2024

    Istanbul

  • May-13-2024

    Paris

  • May-20-2024

    Amsterdam

  • May-20-2024

    London

  • May-27-2024

    Dubai

  • May-27-2024

    Barcelona

  • June-03-2024

    Istanbul

  • June-03-2024

    Kuala Lumpur

  • June-10-2024

    Paris

  • June-17-2024

    Amsterdam

  • June-17-2024

    London

  • June-24-2024

    Barcelona

  • June-24-2024

    Dubai

  • July-01-2024

    Kuala Lumpur

  • July-01-2024

    Istanbul

  • July-08-2024

    Paris

  • July-15-2024

    Amsterdam

  • July-15-2024

    London

  • July-22-2024

    Barcelona

  • July-29-2024

    Dubai

  • Aug-05-2024

    Kuala Lumpur

  • Aug-05-2024

    Istanbul

  • Aug-12-2024

    Paris

  • Aug-19-2024

    Amsterdam

  • Aug-19-2024

    London

  • Aug-26-2024

    Barcelona

  • Aug-26-2024

    Dubai

  • Sep-02-2024

    Kuala Lumpur

  • Sep-02-2024

    Istanbul

  • Sep-09-2024

    Paris

  • Sep-16-2024

    Amsterdam

  • Sep-16-2024

    London

  • Sep-23-2024

    Barcelona

  • Sep-30-2024

    Dubai

  • Oct-07-2024

    Kuala Lumpur

  • Oct-07-2024

    Istanbul

  • Oct-14-2024

    Paris

  • Oct-21-2024

    London

  • Oct-21-2024

    Amsterdam

  • Oct-28-2024

    Dubai

  • Oct-28-2024

    Barcelona

  • Nov-04-2024

    Kuala Lumpur

  • Nov-04-2024

    Istanbul

  • Nov-11-2024

    Paris

  • Nov-18-2024

    London

  • Nov-18-2024

    Amsterdam

  • Nov-25-2024

    Barcelona

  • Nov-25-2024

    Dubai

  • Dec-02-2024

    Istanbul

  • Dec-02-2024

    Kuala Lumpur

  • Dec-09-2024

    Paris

  • Dec-16-2024

    London

  • Dec-16-2024

    Amsterdam

  • Dec-23-2024

    Barcelona

  • Dec-30-2024

    Dubai

Course Details

Course Outline

5 days course

Introduction to Predictive Analytics

 

  • Overview of data analytics and its types:
  •     Descriptive
  •     Diagnostic
  •     Prescriptive
  •     Predictive
  • Understanding predictive analytics and its key concepts
  • The benefits of predictive analytics 
  • Role of machine learning in predictive analysis
  • Preparing data for analysis

Supervised Learning Techniques

 

  • Defining supervised learning
  • Types of supervised learning:

  •      Regression analysis
  •      Classification problems
  • Understanding Regression Analysis algorithms:

  •      Linear regression
  •      Polynomial regression
  •      Logistic regression

  • Understanding Classification problems:
  •      Decision tree and random forests algorithms
  •      Support vector machine (SUM) algorithm 
  • Metrics to evaluate regression and classification models

Unsupervised Learning

 

  • Defining unsupervised learning
  • Types of unsupervised learning

  •      Clustering algorithm
  •      Dimensionality reduction algorithm

  • Understanding Clustering algorithm:

  •      K- means clustering algorithm
  •      Density-based clustering algorithm
  •      Hierarchical clustering algorithm

  • Understanding Dimensionality reduction and its application

  •      Principles component analysis (PCA)
  •      Singular value decomposition (SVD)
  •      t-SNE

  •  Metrics to evaluate unsupervised leaning techniques

Advanced Analytics Techniques

  • Identifying ensemble learning methods:

  •     Bagging
  •     Random forests
  •     Boosting algorithms
  •     Stacking & voting classifiers

  • Utilizing XGBoost and LightGBM for gradient boosting
  • Defining deep learning concepts and the role of artificial neural networks
  • Exploring deep learning framework:

  •     TensorFlow
  •     Keras
  •     PyTorch

  • Building deep learning:
  •     Convolutional neural networks (CNN)
  •     Recurrent neural networks (RNN)

Model Selection & Optimization 

 

  • Determining the importance of selecting the best model
  • Cross-validation technique to select the best model
  • Exploring model bias-variance trade-off

  •        Overfitting
  •        Underfitting

  • Course recap and Q&A
  • Final project presentation