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
- 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 ACTA certified trainer. Dr. Alvin Ang did his Ph.D., Masters and Bachelors from NTU, Singapore. Previously he was a Principal Consultant (Data Science) as well as an Assistant Professor. He was also 8 years SUSS adjunct lecturer. His focus and interest is in the area of real world data science. Though an operational researcher by study, his passion for practical applications outweigh his academic background. He owns a startup externally.
Dr. Alfred Ang: Dr. Alfred Ang is the founder of Tertiary Courses. He is a serial entrepreneur. He founded OSWeb2Design Singapore Pte Ltd in 2007 offering web development, e-commerce store development, graphics design, ebook publishing, mobile apps development, and digital marketing services. He established the first online gardening store in Singapore, Eco City Hydroponics Pte Ltd in 2000, offering a wide range of gardening products such as seeds, plant nutrients, hydroponics kits etc. Eco City Hydroponics has become the most popular and successful gardening store in Singapore. He founded Tertiary Infotech Pte Ltd in 2012 and transformed the business to a training platform, Tertiary Courses in 2014. Tertiary Courses offers a wide range of SkillsFuture courses for PMETs to upgrade their skills and knowledge. He also established Tertiary Courses Malaysia in 2016. He also founded Tertiary Robotics in 2015 offering Arduino, Raspberry Pi, Microbit and Robotics products
Dr. Alfred Ang earned his Ph.D. from National University of Singapore in 2000, majoring in Electrical and Electronics Engineering. He also completed an online MBA course with U21 Global based in Australia. He obtained his B.Sc (Hons) from National University of Singapore in 1992, majoring in Physics. He topped his Physics cohort for 3 consecutive years and funded his degree study with Book price, awards and tuition. He has worked in Defence, Electronics and Semiconductor Industries. His current interests include Machine Learning, Deep Learning, Artificial Intelligence, Internet of Things, Robotics and Programming.
Dr. Alfred Ang is a ACTA certified trainer and DACE certified course developer. He was Distinguished Toastmasters (DTM) and Senior Member of IEEE. He has published more than 20 peer reviewed papers and co-inventors for more than 20 inventions.
Customer Reviews (7)
- will recommend Review by Course Participant/Trainee
-
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 - will recommend Review by Course Participant/Trainee
-
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 - will recommend Review by Course Participant/Trainee
-
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 1/5/2024) - will recommend Review by Course Participant/Trainee
-
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
-
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
-
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
-
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