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Course Details
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
Final Assessment
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/programmes/Pages/IBF-STS.aspx
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
- 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
- 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
Dr. Alvin Ang: 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: Teh Siew Yee is a seasoned data analytics and digital transformation leader with over two decades of experience spanning banking, technology, and manufacturing industries. He has held senior positions at organizations such as Standard Chartered, Hewlett-Packard, TikTok, and SIA Engineering, where he led initiatives in AI governance, financial analytics, and business intelligence. Holding a Master of IT in Business (Artificial Intelligence) from Singapore Management University, he brings strong expertise in applying AI and machine learning to real-world financial and operational use cases.
In “Machine Learning 101 for Financial Trading,” Siew Yee focuses on helping learners understand how data-driven models can be applied to market forecasting, portfolio optimization, and algorithmic trading. His sessions emphasize the fundamentals of supervised and unsupervised learning, time-series analysis, and risk modeling using Python. With his experience in AI strategy and data-driven decision-making, he equips participants with the skills to design, evaluate, and deploy practical trading models that bridge analytics with financial insight.
Tan Woei Ming: Tan Woei Ming is a data scientist and AI engineer with over 15 years of experience in deep learning, predictive modeling, and real-time data automation, primarily in the semiconductor and industrial analytics sectors. He holds a Master’s in Intelligent Systems from the National University of Singapore and a First-Class Honours degree in Electrical and Electronic Engineering from Nanyang Technological University. His professional work includes developing AI-driven predictive systems and deploying machine learning pipelines for high-stakes environments.
In “Machine Learning 101 for Financial Trading,” Woei Ming brings his technical depth to guide learners through the end-to-end process of building trading models—from data preprocessing to feature engineering and model validation. His sessions focus on applying ML algorithms such as regression, decision trees, and reinforcement learning to trading data. By combining his strong engineering background with practical coding instruction, he helps learners translate algorithmic concepts into deployable trading intelligence.
Dwight Nuwan Fonseka: Dwight Nuwan Fonseka is a data engineer and cloud AI specialist with over 18 years of experience in data analytics, software engineering, and intelligent systems design. A certified trainer and experienced practitioner, he has led teams in developing scalable data pipelines, implementing trading analytics systems, and integrating AI solutions into enterprise environments. His expertise bridges cloud architecture, algorithmic modeling, and data visualization for decision support.
In “Machine Learning 101 for Financial Trading,” Dwight helps participants understand how to operationalize machine learning in financial trading environments. His training covers topics such as data ingestion, model deployment, and the use of cloud-based ML tools for backtesting and prediction. By combining hands-on technical practice with real-world trading scenarios, he enables learners to build automated, efficient, and data-driven systems that enhance trading performance and insight.
Dr. Alfred Ang: 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.
Customer Reviews (28)
- Average Rating: 4.3/5 Review by Course Participant/Trainee
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The lecturer Dr Ang has immerse knowledge in the field and able to guide us on using opensource libraries instead of relying on external paid sources for our own studies and usages. The lesson was fun with alot of examples and provide us a basis to start using ML for our tradings. (Posted on 3/13/2026)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 - Average Rating: 3.7/5 Review by Course Participant/Trainee
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Pretty challenging doing this course virtually. Perhaps physical class will be much better. (Posted on 3/13/2026)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 - Average Rating: 2.7/5 Review by Course Participant/Trainee
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If there are 14 sign-up, the room should be bigger or big enough to hold 14 students. If there is a virtual option, make sure there are proper set up so that the participants' learning is not compromised. (Posted on 3/13/2026)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 - Average Rating: 4.0/5 Review by Course Participant/Trainee
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N/A (Posted on 3/13/2026)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 - Average Rating: 4.3/5 Review by Course Participant/Trainee
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Dr Alvin explains concepts really well, in quite an unorthodox way. (Posted on 3/13/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
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Interesting lesson as a python newbie! (Posted on 3/13/2026)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 - Average Rating: 3.7/5 Review by Course Participant/Trainee
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N/A (Posted on 3/13/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
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Dr. Alvin Ang’s Machine Learning 101 for Financial Trading is a highly accessible and informative course for those interested in applying machine learning (ML) to finance. It covers foundational ML concepts like supervised and unsupervised learning, regression, and classification, all while linking them to practical trading scenarios. Dr. Ang does an excellent job of breaking down complex topics and contextualizing them in real-world trading applications, such as stock prediction, risk management, and algorithmic trading. The course is well-structured, starting with basics and progressing to more complex algorithms like decision trees and neural networks. The hands-on approach, using Python code and practical exercises, makes the content engaging and applicable. Dr. Ang’s clear teaching style and real-world examples make the learning experience enjoyable. While the course is beginner-friendly, a deeper exploration into advanced topics (e.g., deep learning for trading) could further enhance it for those with some prior knowledge. Additionally, more coverage on accessing financial data could help learners who are new to finance. Overall, it’s a great starting point for anyone looking to combine machine learning with financial trading, offering both theory and practical skills. (Posted on 3/13/2026)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 - Average Rating: 4.0/5 Review by Course Participant/Trainee
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The course should state clearly the requirements for the course, otherwise course participants will have hard time digest it! (Posted on 3/13/2026)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 - Average Rating: 4.3/5 Review by Course Participant/Trainee
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I am a frequent trader and being able to incoroporate what I leant in this machine learning will be invaluable for my journey. Dr Alvin is very knowledgeable and provides plenty of helpful and valuable resources which greatly improved my knowledge. Regarding training environment, I have taken the course virtually and the sound was quite intermittent sometimes, which result in not able to catch certain things clearly. Will be better if this is a classroom only option. (Posted on 3/13/2026)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 - Average Rating: 4.3/5 Review by Course Participant/Trainee
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N/A (Posted on 3/13/2026)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 - Average Rating: 4.0/5 Review by Course Participant/Trainee
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N/A (Posted on 3/13/2026)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 - Average Rating: 4.7/5 Review by Course Participant/Trainee
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N/A (Posted on 3/13/2026)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 - The trainer manage to deliver the content in a easy way to digest. Review by Course Participant/Trainee
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The trainer manage to deliver the content in a easy way to digest. (Posted on 11/15/2025)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 - Recommended Review by Course Participant/Trainee
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. (Posted on 11/15/2025)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 - Recommended Review by Course Participant/Trainee
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Overall i have better understanding of Machine Learning application for trading using python (Posted on 11/15/2025)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 - Recommended Review by Course Participant/Trainee
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. (Posted on 11/15/2025)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 - Recommended Review by Course Participant/Trainee
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pace and teaching was easy to understand. trainer was patient (Posted on 11/15/2025)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 - Alvin is an excellent trainer! Review by Course Participant/Trainee
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Alvin is an excellent trainer! (Posted on 3/23/2025)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 - Excellent Review by Course Participant/Trainee
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Dr. Alvin Ang is an excellent trainer with a lot of knowledge and experiences! He is very passionate about teaching and will share all that he knows to you. Machine Learning 101 for financial trading. (Posted on 3/21/2025)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
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