Advanced Diploma in Data Analytics and Machine Learning
- Artificial Intelligence
- Finance & Investment
Please refer to respective modules for dates.
Part 1: Certified Data Analytics (R) Specialist
Weeknights (7pm - 10:30pm)
Saturday (9am - 6pm)
Part 2: Professional Certificate in Machine Learning (Python)
Weeknights (7pm - 10.30pm)
Saturdays (9am - 6pm)
Who Should Attend
- Data science professionals and Data Scientists who are familiar with basics in R programming and would want to learn how to perform web scraping from multiple webpages using packages in R
- Professionals interested in data science programming, machine learning and artificial intelligence
- Managers looking into costs and performance hurdles in predictive modelling
- Managers, Data Analysts, Professionals, Executives involved in the analysis, interpretation and presentation of data for decision making across various business functions such as marketing, customer service, corporate communications
PREREQUISITES
- A Bachelor's Degree; or
- A Diploma with at least 3 years of working experience
- Functional Laptop: (1) CPU must be of at least intel core I3, (2) GPU must have an integrated graphics card and (3) RAM must be of at least 4GB
- International students who hold a valid Employment Pass (EP) or Dependent Pass (DP)
Overview
R and Python are the two most popular open-source programming languages used by data analysts and data scientists, particularly with the increase in data availability, more powerful computing, and emphasis on analytics-driven decision in business. In addition, Machine Learning and Artificial Intelligence are gathering momentum to be one of the key pillars of the next Industry Revolution due to the anticipated growth in the machine learning market.
Learning Objectives
Participants will learn to analyse and visualise data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist statistical inference and modelling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualise data with R packages for data analysis.
Participants will also develop relevant skill sets to build data-driven Machine Learning/ AI applications, and cognitive products using Python.
Topic/Structure
Part 1: Certified Data Analytics (R) Specialist
- Introduction To Data Analytics (using R programming)
- Introduction To Data Visualisation (using R programming)
- Web Scraping and Data Insights (using R programming)
- Statistical Inference for Managerial Insights (using R programming)
- A First Look at Visual Analytics (using ggplot2 packages in R)
- Advancing Skillsets Of Visual Analytics (Using Ggplot2 Packages In R)
Part 2: Professional Certificate in Machine Learning (Python)
- Introduction to Python Programming
- Statistical Thinking and Exploratory Analysis
- Basic Concepts of Data Modelling
- Advanced Concepts of Data Modelling
- Practical Concepts in Supervised Machine Learning
- Practical Concepts in Unsupervised Machine Learning
Assessment
Graduation Requirement
The Advanced Diploma qualification will be conferred to participants who successfully complete both Certification programmes within 3 years of commencing the first certificate.
Calculate Programme Fee
Fee Table
| COMPANY-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$6,278.40 (After SSG Funding 70%) |
$2,438.40 (After SSG Funding 70% |
$6,278.40 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$2,438.40 (After SSG Funding 70% |
$2,438.40 (After SSG Funding 70% |
$2,438.40 (After SSG Funding 70% |
|
International Participant |
$20,928 (No Funding) |
$20,928 (No Funding) |
$20,928 (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
Companies who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:
AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)
Intake Information
Part 1: Certified Data Analytics (R) Specialist
| Modules | Intake 27 | Intake 28 |
|---|---|---|
| Introduction to Data Analytics (using R Programming) | 31 Jan, 1 & 3 Feb 2024 [Registration Closed] | 26, 27 & 29 Jun 2024 [Registration Closed] |
| Introduction to Data Visualisation (using R programming) | 28, 29 Feb & 2 Mar 2024 [Registration Closed] | 24, 25 & 27 Jul 2024 [Registration Closed] |
| Web Scraping and Data Insights (using R programming) | 20, 21 & 23 Mar 2024 [Registration Closed] | 14, 15 & 17 Aug 2024 [Registration Closed] |
| Statistical Inference for Managerial Insights (using R programming) | 8, 11 & 13 Apr 2024 [Registration Closed] | 4, 5 & 7 Sep 2024 [Registration Closed] |
| A First Look at Visual Analytics (using ggplot2 packages in R) | 8, 9 & 11 May 2024 [Registration Closed] | 25, 26 & 28 Sep 2024 [Registration Closed] |
| Advancing Skillsets Of Visual Analytics (Using ggplot2 Packages In R) | 5, 6 & 8 Jun 2024 [Registration Closed] | 28, 30 Oct & 2 Nov 2024 [Registration Closed] |
Part 2: Professional Certificate in Machine Learning (Python)
| Modules | Intake 22 | Intake 23 |
|---|---|---|
| Introduction to Python Programming | 9, 11 & 13 Jul 2024 [Registration Closed] | 5, 7 & 9 Nov 2024 [Registration Closed] |
| Statistical Thinking and Exploratory Analysis | 30 Jul, 1 & 3 Aug 2024 [Registration Closed] | 26, 28 & 30 Nov 2024 [Open for Registration] |
| Basic Concepts of Data Modelling | 20, 22 & 24 Aug 2024 [Registration Closed] | 17, 19 & 21 Dec 2024 [Open for Registration] |
| Advanced Concepts of Data Modelling | 10, 12 & 14 Sep 2024 [Registration Closed] | 7, 9 & 11 Jan 2025 [Open for Registration] |
| Practical Concepts in Supervised Machine Learning | 1, 3 & 5 Oct 2024 [Registration Closed] | 4, 6 & 8 Feb 2025 [Open for Registration] |
| Practical Concepts in Unsupervised Machine Learning | 22, 24 & 26 Oct 2024 [Registration Closed] | 25, 27 & 1 Mar 2025 [Open for Registration] |
Trainers
