Chartered Fintech Professional (CFtP) Level 1B Training Module 3: Artificial Intelligence and Machine Learning

Analytics & Tech
Finance & Investment

Basic
SkillsFuture
Short Courses
This module is part of Chartered Fintech Professional (CFtP) Programme

This module is conducted in-person.

Next course starts on

To be advised

Fee

SGD3,270* (as low as SGD381 after maximum funding) Learn More

Duration

3 days
Weekdays and Saturday (9am - 5pm)

Level

Basic

Who Should Attend

Young graduates or early-career professionals who are exploring a new career in Fintech and would like to undergo a structured and rigorous industry-relevant programme
Professionals who are already working at the intersection of finance and technology and who wish to keep abreast with latest fintech knowledge, applications, and trends
Finance or Tech professionals who are currently leading teams in related industries and would like to plug their knowledge gaps in finance and/ or technology
Industry regulators from central monetary authorities, law enforcers of financial crime etc., who are seeking a systemic perspective on the disruptions to financial services and monetary system

PREREQUISITES

No prerequisites, but participants are strongly encouraged to go through the assigned pre-reading materials and videos, especially if one does not have any prior learning or working knowledge in the subject matter of this Module
If the participant intends to register for the Chartered Fintech Professional examination following the completion of this training course, do note that an undergraduate degree from a recognised university or equivalent professional qualification is a compulsory enrolment requirement

Overview

Module 3 provides an overview of artificial intelligence (AI), machine learning (ML), and deep learning (DL). It begins by defining AI and discussing its brief evolution. It then explains the relationship between AI, ML, and DL, and why AI has seen significant effectiveness and progress over the last decade.

The module will also cover the concepts of probability theory and information theory, which are essential for understanding ML. It then discusses the most important general principles of ML, such as supervised learning, unsupervised learning, and reinforcement learning, as well as applications of association analysis, hierarchical clustering, K-means, and principal component analysis (PCA). These are all ML techniques that can be used to extract patterns and insights from data. The concepts and applications of linear regression and logistic regression are also covered. These are two of the most important machine learning techniques for making predictions. Participants will learn how to construct linear regression and logistic regression models, and how to interpret the results of these models.

Programme Partner

Learning Objectives

At the end of the 3-day module, participants will be able to:

Understand the brief evolution of AI and the relationship between AI, ML, and DL
Understand why AI has seen significant effectiveness and progress over the last decade
Understand the concepts of probability theory and information theory
Understand the concepts and applications of association analysis, Apriori algorithm, hierarchical and K-means clustering, principal component analysis (PCA)
Understand the concepts, interpretation, estimation, and applications of linear regression and logistic regression

Assessment

As part of the requirement for SkillsFuture Singapore, there will be an assessment conducted at the end of the course. The mode of assessment, which is up to the trainer’s discretion, may be an online quiz, a presentation or based on classroom exercises.

Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion issued by Singapore Management University.

Calculate Programme Fee

Fee Table

COMPANY-SPONSORED

PARTICIPANT PROFILE

SELF-SPONSORED

SME

NON-SME

Singapore Citizen < 40 years old

Permanent Resident

LTVP+

$981

(After SSG Funding 70%)

$381

(After SSG Funding 70%
+ ETSS Funding 20%)

$981

(After SSG Funding 70%)

Singapore Citizen ≥ 40 years old

$381

(After SSG Funding 70%
+ MCES Funding 20%)

$381

(After SSG Funding 70%
+ ETSS Funding 20%)

$381

(After SSG Funding 70%
+ MCES Funding 20%)

International Participant

$3,270

(No Funding)

$3,270

(No Funding)

$3,270

(No Funding)

All prices include 9% GST

Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.

Self Sponsored

SkillsFuture Credit: Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.

This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.

Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).
Workfare Skills Support Scheme: From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.

Company Sponsored

Enhanced Training Support for SMEs (ETSS)

Organisation must be registered or incorporated in Singapore
Employment size of not more than 200 or with annual sales turnover of not more than $100 million
Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
Trainees must be Singapore Citizens or Singapore Permanent Residents
Trainees must not be a full-time national serviceman
Trainees will be able to enjoy ETSS funding only if the company's SME's status has been approved. To verify your SME's status, please click here.

Please click here for more information on ETSS.

Absentee Payroll