About the Course

This course will provide the participants with an overview of classical machine learning (also called shallow learning) in the field of finance. At the end of the course, participants will gain a deeper understanding of the types of problems that can be solved using machine learning.

The various categories of machine learning being supervised, unsupervised and reinforcement learning will be explored. Cases in finance will be discussed and exampled used in the industry will be provided.  

  • Course Outline

    1. Lesson 1 – Getting Started and Regression
    2. Lesson 2- Classification
    3. Lesson 3 – Tree
    4. Lesson 4 – Support Vector Machine
    5. Lesson 5 & 6 – Ensemble
    6. Lesson 7 – k-Nearest Neighbour
    7. Lesson 8 – Dimensionality Reduction
    8. Lesson 9 – Clustering
  • Target Participants

    Suitable for finance professionals, entrepreneurs, investment professional, technologist who are looking to gain deep skills in Artificial Intelligence  


  • Certification

    Certificate of completion
  • Admission Requirements

    No minimum entry requirement  
  • Course schedule (conducting days & time)

    E-Learning (Self-paced)

    Course fee payment provides 180 days of course access. Certificate will be awarded upon successful completion within the 180 days.  

  • What You'll Study

  • Course Fees and Funding

    Please refer to course brochure.

  • Contact for course enquiries

    Ms TEO SHALYNN,, Tel No:65501094
  • Remarks

    NYP reserves the right to reschedule/cancel any prog and amend the fees/info without prior notice.
  • Attachments