Machine Learning for Business Intelligence

2-Day Instructor-Led Course | HRDF CLAIMABLE!

Course Overview

Machine learning is a rapidly-growing field within Artificial Intelligence, which allows machines to learn from data and self-improve. In this course, we introduce the field of machine learning and describe the well-known processes, algorithms, and tools for one to be a successful machine learning practitioner. This course will help to build skills in data acquisition and modeling, classification, and regression. In addition, one will also get to explore very important tasks such as model validation, optimization, scalability, and real-time streaming.

Course objectives include: (1) Introducing the basic concepts and practical applications of Machine Learning algorithms; (2) Providing students with the capability to identify the long-term impact of machine learning to businesses; and (3) Helping students apply machine learning algorithms to their own real-world problems.

Course Outline


Day 1 - Part I: The Machine Learning Workflow

  • How Machines Learn
  • Using Data to Make Decisions
  • The Machine Learning Workflow: from Data to Deployment
  • Boosting Model Performance with Advanced Techniques

  • Data collection
  • Pre-processing data for modeling
  • Using data visualization

  • Basic machine learning modeling
  • Classification
  • Regression

  • Model generalization: evaluating predictive accuracy for new data
  • Evaluation of classification models
  • Evaluation of regression models
  • Model Optimization through Parameter Tuning

  • Why is Feature Engineering Useful?
  • Basic feature engineering process
  • Feature selection

Day 2 - Part II: Practical Applications

  • Data visualization and preparation
  • Modeling

  • Advanced text features
  • Image features
  • Time-series features

  • Exploring data and use case
  • Extracting basic NLP features and building the initial model
  • Advanced algorithms and model deployment considerations

  • Before scaling up
  • Scaling Machine learning modeling pipelines
  • Scaling predictions

  • Digital Advertising
  • Digital Advertising Data
  • Feature Engineering and Modeling Strategy
  • Size and Shape of Data
  • Singular Value Decomposition
  • Resource Estimation and Optimization
  • Modeling
  • K-nearest neighbors
  • Random forests
  • Other Real Word Considerations



You bet it is! Our Certification Body for this course is iTrain Asia Pte Ltd, the region’s top Certifications Tech Provider headquartered in Singapore, with branch offices in Malaysia and Indonesia.

Upon completion of this course, you will be able to:

  • Explain machine learning concepts and describe applications of well-known machine learning algorithms
  • Apply machine learning techniques to a list of practical problems

This is a 2-day course at an instructor-led training centre.

Mac machines are provided for iTrain students. However participants can also use their own computers if they wish to.