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Course Details
Course Details
What You'll Learn
Topic 1 Overview of Machine Learning Methodology
Introduction to Machine Learning
Machine Learning vs Deep Learning
Supervised vs Unsupervised Learning
Machine Learning Implementation Steps
Target and Features
Model Training and Prediction
Metrics to Evaluate Machine Learning Models
Topic 2 Supervised Learning Models and Applications
The Linear Regression Model
Logistics Regression Model
Naïve Bayes Model
Decision Tree Model
Random Forest Model
XGBoost Model
Neural Network Model
Topic 3 Unsupervised Learning Models and Applications
K-Means Clustering Model
Hierarchical Clustering Model
Principal Component Analysis
Assessment
- Written Exam
- Practical Exam
Course Info
Promotion Code
Promo or discount cannot be applied to IBF-STS courses
Minimum Entry Requirement
Knowledge and Skills
- Able to operate using computer functions
- Basic Python Programming Knowledge
- Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
- Positive Learning Attitude
- Enthusiastic Learner
Experience
- Minimum of 1 year of working experience.
Target Age Group: 21-65 years old
Minimum Software/Hardware Requirement
Softtware: Windows / Mac
Hardware: Laptop
Self-Sponsored Individuals
- Up to 70% subsidy is available for Singapore Citizens and Permanent Residents of Singapore, physically based in Singapore. GST funding support will no longer be applicable for all courses.
Company-Sponsored Individuals
- Up to 70% subsidy is available for Singapore Citizens and Permanent Residents of Singapore, physically based in Singapore. Please note:
- The company must be a Financial Institution regulated by MAS or a FinTech firm certified by Singapore FinTech Association (SFA)
- To register, please email your company name and your name to reachus@knowledgehut.com.sg.
- For more information on the IBF subsidies and eligibility, please visit: https://www.ibf.org.sg/home/for-individuals/skills-and-jobs-development/training-support/IBF-STS
Steps to Apply Skills Future Claim
- The staff will send you an invoice with the fee breakdown.
- Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
- Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
- Upload your invoice and click ‘Submit’
Get Additional Course Fee Support Up to $500 under UTAP
The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).
For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)
Steps to Apply UTAP
- Log in to your U Portal account to submit your UTAP application upon completion of the course.
Note
- SWDA (formerly SSG) subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
- All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
- An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
- UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
- UTAP support amount will be paid to training provider first and claimed after end of class by learner.
Job Roles
Job Roles
- Data Scientist
- Machine Learning Engineer
- Data Analyst
- Research Scientist
- Business Intelligence Specialist
- Data Engineer
- Software Developer (interested in ML)
- Statistician
- Predictive Modeler
- AI Solutions Architect
- Quantitative Researcher
- Data Visualization Specialist
- Analytics Consultant
- Product Manager (focused on AI/ML products)
- Innovation Specialist
Trainers
Trainers
Dr. Alvin Ang is a data science and AI expert with a PhD in Operations Research from Nanyang Technological University, specializing in optimization, predictive modeling, and financial analytics. He has taught extensively at institutions such as SUSS, Curtin University, and SP Jain School of Global Management, covering subjects including machine learning, R, Python for finance, and quantitative methods. Professionally, he has served as a data science trainer with IBM and Tertiary Infotech, delivering courses in AI, big data, and applied machine learning.
With multiple IBM and Kaggle certifications in Python, R, data science, and deep learning, Dr. Ang combines technical mastery with applied research experience. His training approach is highly practical, guiding learners through the process of building, testing, and evaluating machine learning models for trading applications. By focusing on real-world case studies, financial datasets, and algorithmic trading workflows, he equips participants with the skills to apply machine learning techniques effectively in the financial services industry.
Teh Siew Yee is an experienced adult educator and corporate trainer specializing in business communication, workplace effectiveness, and professional development. With years of experience across both corporate and training environments, she has helped learners enhance their skills in problem-solving, collaboration, and interpersonal communication. Her ability to translate complex concepts into clear, practical strategies ensures that participants can immediately apply their learning in the workplace.
As an ACLP-certified trainer, Siew Yee delivers WSQ courses with a strong focus on learner engagement and workplace application. She integrates case studies, role-plays, and reflective exercises into her sessions, ensuring participants develop not only knowledge but also confidence in real-world contexts. By combining her corporate experience with adult education expertise, she empowers learners to improve workplace efficiency, strengthen teamwork, and achieve personal and organizational success.
Tan Woei Ming is an accomplished data scientist and AI engineer with over 15 years of experience in artificial intelligence, machine learning, and data-driven innovation. Holding a Master’s in Intelligent Systems from the National University of Singapore (NUS) and a First-Class Honours in Electrical and Electronic Engineering from NTU, he has led AI initiatives in predictive analytics, automation, and process optimization across the semiconductor and manufacturing industries. His expertise lies in translating complex AI technologies into practical business applications, enabling organizations to innovate through data insights and intelligent automation.
Dwight Nuwan Fonseka is Head of Data Science at Plano Pte. Ltd. and an ACLP-certified trainer with deep expertise in data analytics, machine learning, and AI applications. He has extensive hands-on experience developing predictive models, RShiny dashboards, and deep learning solutions using R, Python, TensorFlow, and Keras. With a strong professional background in healthcare, finance, and customer analytics, Dwight brings an applied perspective to teaching AI, focusing on both the opportunities and risks of emerging technologies.
Dr. Alfred Ang is a specialist in artificial intelligence and data science with extensive experience applying machine learning models to real-world business and financial contexts. As Founder of Tertiary Courses Singapore, he has designed and delivered numerous WSQ and IBF-accredited programs in Python programming, data analytics, and AI adoption for financial services. His professional expertise covers areas such as predictive analytics, algorithmic modeling, and natural language processing, giving learners a strong foundation in understanding how AI transforms financial trading strategies.
With a PhD in Computer Science, Dr. Ang blends academic rigor with industry insights, helping participants bridge the gap between theory and application. He emphasizes practical, hands-on learning using financial datasets, enabling learners to build trading models that leverage supervised and unsupervised machine learning techniques. By combining deep technical knowledge with a learner-centric teaching style, Dr. Ang empowers financial professionals to adopt AI and machine learning for smarter, data-driven trading decisions.
Review
Customer Reviews (30)
- will recommend Review by Course Participant/Trainee
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The IBF accredited course IBF - Machine Learning 101 for Financial Trading is well structured and meticulously delivered by Dr Alvin Ang. This course will equip you with useful knowledge, coding skill and practices in building machine learning model for financial trading.1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
Dr. Alvin is passionate about data science, trading as well as being a trainer. He had showcased his broad experience in data science and was able to deliver complex topics in a simpler and less overwhelming way. Apart from the course contents, Dr. Alvin shared about useful insight from a variety of resources and career advancement which are relevant to the course
It was an informative and interactive course where Dr Alvin’s open to discussion. I would recommend this course if you would like to explore the opportunities of using machine learning algorithms for trading. (Posted on 1/4/2024) - will recommend Review by Course Participant/Trainee
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I believe that extending the course to 4 days or more would be beneficial, given the wealth of knowledge Dr. Alvin Ang has to offer. His expertise, patience, and passion make him an exceptional educator, and I'm grateful for the knowledge and skills I acquired under his guidance.1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
I had the privilege of attending his course, which was an incredibly enriching experience. Dr. Ang's deep expertise in data, AI, and engineering was evident as he shared his extensive knowledge and ensured we could apply it practically.
His teaching style, driven by his contagious passion for data, sparked our curiosity and encouraged us to delve deeper into the subject. Beyond learning ML for Trading, I gained valuable insights into other relevant skills and development areas.
Overall, highly satisfied and recommended. (Posted on 9/4/2023) - Might Recommend Review by Course Participant/Trainee
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Trainer knowledge & provide drink (Posted on 5/12/2018)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Every thing is good actually. No complaints here. Keep up the good work. Review by Course Participant/Trainee
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The instructor Siva is great. He explains everything clearly, also very polite and has a lot of patience. Now I want to enroll on other related courses because I learned a lot from this one. Two thumbs up. (Posted on 11/8/2017)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Might Recommend Review by Course Participant/Trainee
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As this is only a one day course, I understand that it will be hard to cover all the fundamental topics. Most of the topics would be touch-and-go, and hands-on might be limited. That's what happen for this course. But its understandable, as explained. To help the learner, it would be good if current notes can be explained, specifically, some basic steps or instructions on the solidworks function to be covered. This can 'make-up' for the touch-and-go nature of the one day course. (Posted on 8/18/2017)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
Write Your Own Review
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