DATA ANALYTICS

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.

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

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:

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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

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Introduction

Data mining is a technique used to extract useful information from a large number of datasets. A good understanding of the updated data mining techniques and the ability to use effectively is increasingly important for data-intensive manufacturing operations. This training is targeted towards manufacturing companies and companies in other industries which are data rich but information poor. It aims to provide the trainees understanding of up-to-date data mining technologies, build a fundamental about data analytics and data mining techniques for various applications such as process optimisation, correlation analysis for major factor identification, product quality improvement and many more.

about the programme

This course aims to provide participants with up-to-date technologies in data mining. Through extensive hands-on and sharing of successful case studies, it allows the participants to have the confidence and ability to use data mining techniques to help them in their daily work.

The course will provide the participants with a set of methodology for conducting problem-solving using data mining. From the basics of methodologies in data collection, pre-process data from multiple sources, cleaning of the data, to finally using data mining techniques to analyse the data and solve actual industrial problems.

At the end of the course, the participants can:

• Understand the fundamentals of data mining technologies
• Gain knowledge of actual industry case studies of how data mining can be used to solve actual industrial problems
• Understand data collection and pre-process methodologies
• Understand the K-means clustering method and its application
• Able to apply correlation analysis to identify the major factors for root cause analysis
• Understand and apply predictive modelling by multiple regression and neural networks
• Apply smart design of experiment with What-If analysis through predictive models

Course Outline

The programme consists of 4 learning stages.

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CERTIFICATIONS

There are 3 modules for completion under the SCTP: Data Analytics 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)
• Data Mining for Correlation Analysis (DM-Lite) (16 hours)

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.
  

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.

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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.

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