Course Details

This is an introductory, hands-on course, equipping participants with the following skills:

1. Knowledge of core concepts underpinning Maintenance Predictive Analytics; Generative Artificial Intelligence
2. (GenAI) usage to translate these fundamental concepts into clear, executable Python codes;
3. Application and execution of Python workflows in Predictive Maintenance Problems;
4. Interpretation and communication of results produced by maintenance decisions analyses.

1. Upload data and create data models.
2. Use DAX functions to enhance dashboards.
3. Associate links between visual and descriptive analytics variables.
4. Find dashboard hindsights and insights.

• Statistical Foundation
  
• Failure Time Analysis
  
• Anomaly Detection
  
• Reliability Modelling and Analysis

1. Recognise and apply simple statistical concepts used in Predictive Maintenance Analysis
2. Apply simple statistical Process Monitoring techniques to monitor process outputs
3. Use simple Regression Analysis to model degradation data predicting expected failure time
4. Model failure time of product / system to better manage maintenance activities

• Basic Statistical Concepts and Distributions
  
• Statistical Process Monitoring of Measurements
  
• Correlation and Simple Regression Analysis of Degradation Data
  
• Failure Time Modelling

1. For self-sponsored applicant, please click on the “Register” button to apply for the course. You will be directed to STEP portal to manage all your course activities. Please note that you will be prompted to sign in with Singpass/Student ID.
 
2. For company-sponsored applicant, please approach your company's Human Resource (HR) team to put in the application through the company portal using CorpPass.  You may only apply after receiving the registration link from your company's HR.
 
3. Your application does not guarantee acceptance into the course. Your acceptance into the course is dependent on meeting the course requirements and course vacancy.
 
4. All successful applicants will be notified with a letter of confirmation via email.
 
6. PACE Academy course schedules, including course trainer, course fees and course availability are subject to change.

7. PACE Academy reserves the right to cancel or postpone any course at short notice; & at its absolute discretion without assigning any reason for such cancellation/postponements. In the event that the applicant’s chosen course is cancelled prior to its commencement, PACE Academy will make a full refund of course fees already paid by the applicant.

8. The data provided to Singapore Polytechnic will be kept strictly confidential and will be used for the purpose of course administration. The data may be passed on to the relevant organisations that require the information related to the course.