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SkillsFuture Career Transition Programme (SCTP):

DATA ANALYTICS (Advanced)

SCTP in Data Analytics (Advanced)

This is one of the specialisations offered as part of the SCTP Digital Manufacturing and Supply Chain courses, which spans *three-month on a part-time basis.

*The total duration of the SCTP course may slightly vary, being either longer or shorter than 3 months for certain intakes. Please consult the specific course calendar for the intended intake before enrolling.


WHAT IS SCTP?

The SkillsFuture Career Transition Programme (SCTP) is an initiative by the SkillsFuture Singapore (SSG) agency to help individuals in career transition by acquiring industry-relevant core competencies.

This Train-and-Place programme allows the trainees to attend training courses and other immersive learning activities, in addition to access to career advisory services and employment facilitation, while earning recognised certificates.

The SCTP trainees will attend classes, hands-on labs and other immersive learning activities to earn Workforce Skills Qualifications (WSQ) Statement of Attainments (SOAs) or other certificates.

We deliver through

  • Relevant and timely case study-based curriculum
  • Hands-on practical training combined with industry Best Practices insights
  • Access to cutting-edge technology developed by SIMTech experts
  • Regular sessions conducted in our state-of-the-art labs
  • Blended learning options combining expert classroom lectures and e-learning convenience

What we offer for individual trainees

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Career Advisory Services

  • Participate in career talk (workshop, clinic sessions)
  • Job matching and interview facilitation
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part-time training programme

  • Train-and-Place Modality
  • Industry-focused curriculum
  • Can continue to work
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Course Fee Funding Support

  • Up to 95% subsidies for Singapore Citizens, SPRs, LTVP+ Holders
  • SkillsFuture Credit eligible

Application Process

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Stage 1
  • APPLICATION
    • Applicant to submit online application and curriculum vitae (CV) via the APPLY NOW Button.
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Stage 2
  • EVALUATION
    • Applications will be evaluated by a committee.
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Stage 3
  • ACCEPTANCE
    • Shortlisted applicants who are successfully enrolled to the programme to receive a course confirmation and offer email.
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Stage 4
  • INDUCTION
    • SCTP trainees attend a course briefing workshop.

Quick link


Introduction

This specialised SCTP programme is meticulously crafted to cultivate advanced Data Analysts. It offers a unique opportunity to acquire essential adaptive skills and digital leadership competencies crucial in the age of Artificial Intelligence. The programme aims to impart expertise in Data Pre-Processing and Data Mining technologies, enabling individuals not only to remain pertinent in the evolving economy but also to make astute data-driven decisions in enterprise and shopfloor operations. By acquiring these cutting-edge skills, participants will be well-prepared fornew job opportunities or roles that demand these advanced competencies.

Targeted Job Role(s)

  • Data Analyst (Advanced)

List of Modules

Digital Leadership In the Age of Artificial Intelligence (AI) (8 hours)

Introduction

In an era where Artificial Intelligence (AI) and digital technologies are revolutionizing industries, leaders must evolve to navigate the complexities of this digital landscape. The transformation towards Industry 4.0 is not merely a technological shift but a holistic change that encompasses business value, organisational processes, and human capital.

About the Programme

This programme aims to help company leaders understand digital leadership competencies, leading to improvements in productivity, employee motivation and business performance. Enabling leaders to understand digital transformation goes beyond the digital to target the transformation of business value propositions, the organisation process, and its people. This 2 half-day programme equips middle and senior managers with vital skills for leading in the Age of AI. The curriculum covers essential frameworks for digital transformation, helps assess organisational readiness for AI changes, and offers insights into emerging technologies. It also addresses job redesign in the context of AI.

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Course Outline

The programme is delivered through practical applications of Supply Chain, Enterprise & Frontline digital technologies, to enable company leaders to understand the following key topics:

MODULAR TECHNOLOGIES
  • Real-time Planning & Scheduling
  • Digital Workflow Automation
  • Inventory Analytics and Planning System
  • Data-driven Inventory Planning
  • Predictive and Prescriptive Maintenance System
  • Holistic Energy Management
  • Real-time Dashboard
DIGITAL TECHNOLOGIES

  • Generative AI in Business Strategy
  • Prompt Engineering
  • Content and Media Generation
  • Consumer Experience Enhancement
  • Data-Driven Decision Making
  • Gen AI Tools
    • ChatGPT
    • DALL-E
    • Beatoven.ai
    • Runway ML
DIGITAL MATURITY & TRANSFORMATION
  • Digital Business Strategy
  • Digital Competency
  • Supply Chain Integration
  • Enterprise Connectivity
  • Enterprise Intelligence
JOB REDESIGN IN THE AGE OF AI
  • Ethics and Responsible AI
  • Privacy Concerns in the Age of AI
  • AI’s Impact on the Employment Ecosystem
  • Building an AI-Literate Team
  • Emerging Roles in AI-Enabled Industries
  • Adaptive Leadership in a Changing Market
  • Creating an AI Strategy

Find out more

Data Pre-processing for Data Analytics (16 hours)

Introduction

With the advent of Industry 4.0 and an ever-increasing use of the Internet of Things (IoT), data is now generated in numerous forms. That’s why this course is designed to provide the participants with a comprehensive introduction to the fundamentals of data pre-processing, which is a vital aspect of preparing data from various sources and sensors to be analyzed and mined for insightful discoveries.

Throughout the course, participants discover the significance of data pre-processing and its practical applications, as well as how to synchronize data and manage data complexity. They also gain hands-on experience with basic Python programming and Excel skills, working with both categorical and time-series data to normalize and transform it. Furthermore, the participants will also learn about feature engineering and selection with machine learning and artificial intelligence techniques, enabling them to prepare data for further analysis and mining for a wide range of practical applications.

About the Programme

This course is a two-day intensive programme aimed at helping participants master the art of Data Pre-processing for Data Analytics. Starting from foundational concepts to advanced techniques, this course equips learners with the essential skills to handle, clean, and optimise data for machine learning. The programme enhances the participants’ expertise in data normalization, transformation, feature engineering, and selection, thereby unlocking the full potential of their analytical endeavors.

Course Outline

The programme employs the Learn-Practise-Implement™ (LPI™) pedagogy, where fundamental knowledge and principles taught will be reinforced with hands-on practices.

Key focus areas or applications:

  • Introduction to Data Pre-processing
  • Data Normalization and Data Transformation
  • Preprocessing of Data For Machine Learning
  • Feature Engineering and Feature Selection

Find out more

Implement Manufacturing Data Mining Techniques (40 hours)

Introduction

Data mining techniques are increasingly important for data-intensive manufacturing operations as the industry faces a number of challenges such as equipment and material condition variations, trial-and-error in process parameter setting, product quality inconsistencies, low capability of root cause discovery, process performance prediction and process parameters/recipe auto tuning. By applying data mining techniques, a company can improve its product quality and manufacturing productivity.

This WSQ course aims to provide a good understanding of the fundamentals of data analytics and data mining techniques for different manufacturing applications. Participants will learn techniques for advanced clustering methods for product quality management, correlation modelling, and data pattern methods for root cause analyses and neural networks for process performance prediction.

Why This Course

  • Designed specifically to meet Singapore’s industry demand
  • Highly practical and intensive
  • Latest knowledge and up-to-date technology
  • Case studies highlighting industrial applications
  • Expert trainers in the field with industrial experience

What You Will Learn

Fundamentals of Data Mining

  • Introduction to data mining concept and applications in manufacturing
  • Process correlation modelling and data pattern analyses through statistical methods
  • Advanced data clustering technologies for anomaly detection and classification
  • Process performance prediction using artificial intelligence (neural networks, etc)

Case Studies by Grouping Projects Using Real Production Data

  • Data preparation
  • Problem statement
  • Technical challenges
  • Project objectives
  • Data collection and pre-processing
  • Data analysis
  • Major factor identification by correlation coefficient analysis
  • Correlation modeling by multiple regression method and root cause analysis
  • K-means clustering and pattern based regression modeling
  • Correlation modeling by fuzzy neural networks method for quality estimation
  • What-if predictive analysis for process improvement & DOE design
  • Project conclusion
  • Improvement plan
  • Identifying yield improvement areas
  • Production/process improvement plan

Find out more


Certifications

CERTIFICATIONS

There are 3 modules for completion under the SCTP: Data Analytics (Advanced) course.

Participants will be awarded a SIMTech Certificate of Attendance (COA) for passing each of the individual modules listed below:

  • Digital Leadership In the Age of Artificial Intelligence (AI) (8 hours)
  • Data Pre-processing for Data Analytics (16 hours)

Participants will be awarded an electronic WSQ Statement of Attainment issued by SkillsFuture Singapore for passing the individual module listed below:

  • Implement Manufacturing Data Mining Techniques (40 hours)

Note:

Participants will be awarded with a certificate for each individual module, if they meet the following criteria:

  • Achieve at least 75% course attendance;
  • Take all assessments; and
  • Pass the course.

Programme Fees

Programme Fees

 Before GSTAfter GST 9%
Full Course Fee$6,400$6,976
Singapore Citizens aged 39 years and below, Singapore Permanent Residents and LTVP+ Holders aged 21 years and above ¹ $1,920$2,092.80
Singapore Citizens aged 40 years and above ² $640$812.80
Singapore Citizens who are eligible for Additional Funding Support ³ $320$492.80
  • ¹ Eligible Singapore Citizens aged 39 years and below, SPRs and LTVP+ holders aged 21 years and above can enjoy a baseline subsidy of up to 70% funding of the course fee.
  • ² Singapore Citizens aged 40 years and above are eligible for up to 90% course funding under the Mid-career Enhanced Subsidy (MCES).
  • ³ Singapore Citizens who meet at least one of the following eligibility can enjoy up to 95% funding under the Additional Funding Support (AFS):
    a. Long-term unemployed individuals (at least 6 months or more); or
    b. Persons with disabilities;
    c. Individuals in need of financial assistance - ComCare Short-to-Medium Term Assistance (SMTA) recipients or Workfare Income Supplement (WIS) recipients

Additional Information:


  • Long Term Visit Pass Plus (LTVP+) Holders
    The LTVP+ scheme applies to lawful foreign spouses of Singapore Citizens with (i) at least one Singapore Citizen child or are expecting one from the marriage, or at least three years of marriage, and (ii) where the Singapore Citizen sponsor is able to support the family.

    All LTVP+ holders can be identified with their green visit pass cards, with the word ‘PLUS’ printed on the back of the card.
  • Pre-Requisites

    Pre-Requisites

    • Only Singapore Citizens, Singapore Permanent Residents and Long-Term Visit Pass Plus Holder (LTVP+) aged at least 21 years old (based on the year of course commencement) who can commit to the SCTP courses on a part-time basis are eligible to apply.

    • Applicants should possess a degree in any discipline or a diploma with a minimum of 3 years of related working experience.

    • Applicants who do not have the required academic qualifications are still welcome to apply, but shortlisted candidates may be required to attend an interview for special approval.

    WHY CHOOSE SIMTECH's SCTP DIGITAL MANUFACTURING AND SUPPLY CHAIN COURSES

    Pathways to Specialisations

    A*STAR SIMTech offers eight SkillsFuture Career Transition Programmes (SCTP) in Digital Manufacturing and Supply Chain, each representing a unique technical pathway. As advanced manufacturing in Singapore grows, these courses help professionals stay ahead in an evolving industry. With digitalisation advancing, companies must adapt to remain competitive. SIMTech's programmes provide participants with the latest skills and knowledge, preparing them for the demands of a dynamic manufacturing and supply chain landscape.

    Click on the above image to enlarge.

    Browse through other SCTP Digital Manufacturing and Supply Chain courses here.

    Empowering Individual’s Career Transitions with Our Train-and-Place Programme

    John, a 40-year-old Engineer, aspires to pivot to a new job role in the automation sector that demands skills and competency in digital leadership and digital business flow. Seeking support for this mid-career job pivot, John explores the train-and-place programme with SIMTech for training suitability and funding eligibility.

    After a series of consultations and confirmation of training suitability and eligibility, John registers and begins a three-month SCTP on a part-time basis. During this period, SIMTech supports John with job-specific skills trainings, job placement facilitation, including job referrals, interview opportunities, and career coaching to improve his placement prospects.

    Click on the above image to enlarge.


    Contact Us

    • For technical enquiries, please contact:

    Mr MA Bin,
    Email: bma@SIMTech.a-star.edu.sg

    • For general enquiries, please contact:

    Dr LIM Cheng Leong,
    Email: lim_cheng_leong@ARTC.a-star.edu.sg


    Registration

    • Successful applicants will be notified on their batch's commencement date.

    Schedule

    SCTP Specialisation
    Skills Course Reference NumberExpected Commencement DateRegistration Status
    • Data Analytics (Advanced)
    TGS-2024045939Successful applicants will be notified on their batch's commencement date.