16 hours / 2 days
9:00am to 6:00pm
Mode of Training:
The practice of Data Analytics across industries require data mining, machine learning, and computational modelling skills.
For example, Industries like Telcos use Machine Learning and Computational techniques to identify customer behaviours and offer targeted campaigns and products. Financial services uses Machine Learning and Computational techniques for identification of Fraud and prediction of loan default and Manufacturing industry uses Machine Learning and Computational techniques for Preventive Maintenance and Inventory Optimization. Our aim is to equip participants with the ability to identify and utilise appropriate algorithmic techniques to solve relevant business problems
To equip participants with the ability to identify and utilise appropriate advanced statistical, machine learning, computational algorithms and data models to test hypotheses and derive patterns or solutions.
• Introduction to Computational Modeling
• Hands on exercise on concepts of Computer Modeling
• Pitfalls of Computational Modeling Techniques
• Introduction to Optimisation
• Hands on exercise on simple optimization concepts
• Introduction to Computational Intelligence and Machine Learning algorithms
• Pitfalls of Advanced Analytics, Machine Learning and Computational Modeling Techniques and how to avoid them
• Hands on exercise on Analytics using Computational Intelligence and ML
IT Analysts, Data Analysts, Technical Leads, IT Engineers, Data Engineers, Software Developers
Minimum Entry Requirements / Assumed Skills and Knowledge
1. Knowledge of Introductory Statistics, Analytics, Computational techniques or relevant skill preferred
2. Participants are required to bring their own laptops for this training
3. Basic understanding of a programming language is preferred but not mandatory
Award / Certification / Accreditation
• Certificate of Performance (electronic Certificate will be issued)
A Certificate of Performance will be awarded to participants who pass the assessment and meet at least 75% attendance rate
Eligible for SkillsFuture CreditTerms and Conditions*Please note that once the maximum class size is reached, the online registration will be closed.
You may register your interest, and would be notified if there is new run.
1. All applications must be made via Online Registration at www.pace.sp.edu.sg
Course fees can be paid by the following payment modes:
a) Credit Cards, Internet Banking, NETS (Not Applicable for company sponsored)
For e-payment using Visa/Master cards and Internet Banking, please click on the ‘Make e-Payment’ button on the acknowledgement page to proceed.
b) For NETS payment, you can pay at:
c) For payment via PayNow, please enter the UEN No. T08GB0056ACET and indicate the invoice/registration number.
*With effect from 1 August 2021, cheque payment will not be available.
2. All successful applicants will be notified with a letter of confirmation via email.