Advanced Certificate in Applied Data Analytics
- Analytics & Tech
- Innovation & Business Improvement
This programme is conducted online.
Please refer to respective modules for dates.
Who Should Attend
- Data analysts and engineers who want to gain insights in end-to-end data pipelines
- Software developers and engineers looking to expand their knowledge of data processing workflows
- Cloud practitioners planning to use Cloud services for data pipelines and analytics
- Project managers or team leads who need an understanding of data pipeline to better communicate with technical teams and stakeholders
- Aspiring data professions seeking a foundational understanding of modern data pipelines and cloud technologies
PREREQUISITES
- Experience in Python programming (equivalent to that attained in Professional Certificate in Python Programming programme)
SYSTEM REQUIREMENTS
- 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
Overview
It provides a comprehensive introduction to the tools and techniques used in modern data analysis, covering essential topics such as Python programming, SQL for managing relational databases, and cloud-based enterprise databases such as Google BigQuery and AWS Redshift for large-scale data handling. Participants will explore advanced techniques in predictive analytics, textual analysis using Natural Language Processing (NLP), and web scraping. The course also covers tools for business intelligence and storytelling, equipping participants with the ability to present data insights through compelling visualisations.
The course concludes with a capstone project, allowing participants to apply their skills to a real-world data problem while being introduced to additional tools and techniques. By the end of the programme, participants will be equipped with a well-rounded set of skills in applied data analytics, preparing them to effectively analyse, interpret, and present data in various professional contexts.
Learning Objectives
- Master fundamental Python programming and data analytics libraries to effectively process and analyse structured data
- Develop proficiency in relational databases using SQL and cloud-based platforms like Google BigQuery for managing, querying, and deriving insights from large datasets
- Build and optimise predictive models through techniques like linear and logistic regression, data preprocessing, feature engineering, and hyperparameter tuning
- Extract, preprocess, and analyse unstructured text data using web scraping and Natural Language Processing (NLP) techniques, including an introduction to Large Language Models (LLMs)
- Create compelling data visualisations and interactive dashboards using Python libraries to effectively communicate insights and build end-to-end data applications
Topic/Structure
Assessment
- Classroom exercises
- Project presentations
CERTIFICATION
Upon completion of all 6 modules within a maximum duration of 3 years, participants will be awarded a digital Advanced Certificate in Applied Data Analytics.
Calculate Programme Fee
Fee Table
| COMPANY-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$4,708.80 (After SSG Funding 70%) |
$1,828.80 (After SSG Funding 70% |
$4,708.80 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$1,828.80 (After SSG Funding 70% |
$1,828.80 (After SSG Funding 70% |
$1,828.80 (After SSG Funding 70% |
|
International Participant |
$15,696 (No Funding) |
$15,696 (No Funding) |
$15,696 (No Funding) |
All prices include 9% GST
Please note that the programme fees are subject to change without prior notice.
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.
Employer 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 are eligible for ETSS funding only if their company's SME status is approved prior to the course commencement date. To verify your SME's status, please click here.
Please click here for more information on ETSS.
Absentee Payroll
Employers 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)
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