Machine Learning Course or Master’s Degree in Singapore: What To Know Before You Make Your Decision

Machine Learning Course or Master’s Degree?

If you’re planning to break into the AI field, you’re likely wondering: “Should I take a machine learning course or pursue a master’s degree?”

In Singapore, where tech roles are booming and upskilling is highly encouraged through government subsidies and employer support, this decision can significantly shape your career path. This comprehensive guide breaks down the pros, cons, career outcomes, costs, and learning approaches of both options so you can choose what fits you best.

Understanding the Two Paths: Machine Learning Course & Master’s Degree

The terms machine learning course and master’s degree in machine learning are often used interchangeably, but they represent very different experiences in terms of time, cost, learning style, and job outcomes.

• Machine Learning Courses: These are short to mid-term programs focused on hands-on skills, often offered by private training providers like Heicoders Academy, Coursera, or edX. Courses can range from introductory to advanced, and some include career support, mentorship, and capstone projects.
• Master’s Degrees: These are structured postgraduate academic programs delivered by accredited universities such as NUS, NTU, or SMU. They typically last 1–2 years and involve a deeper focus on theory, research, and a final thesis.

Cost Comparison: What’s the Cost to Study Machine Learning in Singapore?

Master’s Degree Cost

A Master’s in Machine Learning or Artificial Intelligence in Singapore typically costs:

• Local Universities (e.g., NUS, NTU, SMU): SGD 40,000++ to 63,000++ (for citizens/permanent residents)
• Private or Overseas Programmes: SGD 50,000++ & above

Example of local university offering Machine Learning Master’s Degree: NUS MComp in Artificial Intelligence

This often excludes opportunity cost if you’re studying full-time and not earning.

Machine Learning Course Cost

Compared to university programmes, machine learning courses offered by private institutions or online platforms are significantly more affordable — and often come with generous government subsidies.

• Private Institutions (e.g., Heicoders Academy): SGD 2,000–5,000
• Online Platforms (e.g., Coursera, edX): SGD 50–2,000
  

Most local courses are eligible for SkillsFuture, UTAP, or IBF subsidies covering up to 70% of fees.

Example of a private institution offering Machine Learning course: Heicoders Academy’s Apllied Machine Learning Course for intermediate learners OR Python Programming and Data Visualisation for beginners.

Subsidy Breakdown in Singapore

• SkillsFuture Credit: Every Singapore Citizen aged 25+ gets $500 (with periodic top-ups) to spend on eligible courses.
• IBF-STS: For financial sector-related roles, covers up to 70–90% of course fees.
• NTUC UTAP: Union members can receive up to $250/year in additional support.
• PSEA: Every Singapore Citizen receives PSEA funds between SGD 1,000 – 6,000 for their post-secondary education and professional development
  

These subsidies make machine learning courses especially attractive to mid-career professionals and career switchers.

Machine Learning Study Duration: How Long Will It Take to Gain Job-Ready Skills?

• Master’s Degree: 12–24 months (full-time or part-time)
• Machine Learning Course: 6–12 weeks per module (or bundled into 3–6 month programmes)
  

Machine Learning courses like those from Heicoders Academy are designed for working professionals, with evening or weekend schedules.

If you’re seeking a faster career transition, a course will get you there quicker.

Machine Learning Curriculum & Learning Approach

Master’s Degree in Machine Learning:

• Emphasises mathematical theory, algorithmic understanding, and research methodologies
• Offers modules like Deep Learning, Computer Vision, and Reinforcement Learning
• Often ends with a thesis or research project

Machine Learning Courses:

• Focus on hands-on skills like Python coding, TensorFlow, Scikit-Learn
• Project-based learning (e.g., building recommender systems, fraud detection models)
• Taught by industry practitioners rather than academics
• Often include job-ready deliverables like GitHub portfolios and capstone projects

Which One Builds More Relevant Skills?

The answer depends on your goals.

A master’s degree provides strong theoretical foundations and exposure to advanced topics in machine learning. It’s especially valuable for those pursuing academic research or roles requiring a deep understanding of algorithms, mathematics, and system design.

Meanwhile, machine learning courses are generally focused on job-ready skills. They emphasise hands-on experience with real datasets, common ML libraries, and industry tools. This makes them more accessible to working professionals or career switchers looking to build practical capabilities quickly.

Ultimately, both learning paths offer different strengths — one provides depth and academic rigour, while the other offers practical skills and faster entry into the workforce. For many, the most effective path is a combination of both.

Entry Requirements & Accessibility

Master’s Degrees:

• Requires a Bachelor’s degree (usually in a related field)
• Often require GRE, recommendation letters, and academic transcripts
• Competitive admission process and limited intakes

Machine Learning Courses:

• Open to anyone, with only basic math or coding familiarity recommended
• Suitable for career switchers without a tech background
• No complex paperwork, faster enrolment

This accessibility makes them popular among PMETs (Professionals, Managers, Executives, Technicians) exploring new roles or industries.

Machine Learning Course or Master’s Degree: Career Outcomes

With a Master’s Degree:

• Common job titles: AI Researcher, Data Scientist, ML Scientist, University Lecturer
• Higher qualifications may help in academic or R&D environments
• Recognition is stronger globally (especially in countries like Germany, China, or Japan)
  

With a Machine Learning Course:

• Job roles: Data Analyst, Machine Learning Engineer, AI Product Manager, Prompt Engineer
• Suitable for entry- to mid-level roles or job switches
• Courses with portfolio projects and mentorship (like those at Heicoders) can help learners land jobs even without a degree

Hiring Trends in Singapore’s AI Sector

A growing number of companies in Singapore are hiring based on skills-first principles. In sectors like fintech, healthcare, logistics, and education, employers are increasingly evaluating candidates based on what they can build, not what certificates they hold.

Key Insights:

• According to Reeracoen Singapore, employers value project portfolios and real-world application over academic grades.
• Startups and mid-size firms prefer candidates who can hit the ground running with practical tools like Python, Pandas, and TensorFlow.
• Government-backed programs like Career Conversion Programmes (CCP) encourage employers to hire based on demonstrable skills.
  

This validates the rising relevance of machine learning courses, especially those focused on upskilling and career switch support.

Machine Learning Portfolio: The Most Overlooked Factor

Regardless of which path you take, having a strong machine learning portfolio is one of the best ways to stand out. Here’s how they differ by learning path:

Master’s Degree:

• May include research publications or thesis work
• Less focus on industry-oriented applications unless you pursue internships

Machine Learning Course:

• Emphasises capstone projects, GitHub repositories, Kaggle competitions, and real datasets
• Typically includes career coaching on how to present your portfolio to employers

In Singapore’s hiring market, a strong portfolio can significantly strengthen your application, especially if you’re aiming for junior or supporting roles in tech. While it may not fully substitute the depth of a formal degree, it can demonstrate your initiative, technical capability, and readiness to learn.

Should You Choose a Machine Learning Course or Master’s Degree?

Choose a Machine Learning Course if:

• You want to switch careers quickly and affordably
• You’re already in a related role (e.g., analyst, developer) and want to specialise
• You prefer practical, job-focused learning
• You don’t have a Bachelor’s degree

Choose a Master’s Degree if:

• You want to do research, pursue a PhD, or enter academia
• You’re targeting senior AI/ML roles at research labs or government agencies
• You want international recognition or plan to work overseas

Some professionals combine both routes—starting with a course to gain experience, then pursuing a degree later.

Machine Learning Degree vs Online Course: Comparison Table

Final Thoughts: Machine Learning Course or Master’s or Both?

It’s easy to frame the question as a binary choice — machine learning course vs master’s degree. But in reality, the two paths often complement each other rather than compete.

A master’s degree will undeniably offer greater depth, academic rigour, and technical foundations, particularly if you already have a STEM background. But pursuing one requires significant time, money, and motivation. What if you sink tens of thousands of dollars and a year or more of effort, only to realise halfway through that it’s not the right fit for you?

That’s why many learners start with a machine learning course. It’s a lower-risk, faster way to validate your interest and capability in the field. Courses like those offered at Heicoders Academy are especially useful for:

• Building foundational knowledge in Python and ML concepts
• Exploring real-world applications before diving into theory-heavy content
• Preparing yourself mentally and technically for a future master’s degree

Many of our past learners have shared that our course gave them the confidence and clarity to later pursue a more gruelling Master’s degree.

So the better question may not be “Which is better?” but rather: “Which one should I start with?”

If you’re at the beginning of your journey or considering a career switch, start with a practical machine learning course. If it clicks and you want to go deeper, a master’s degree can take you the rest of the way.

Together, they form a symbiotic pathway — one that balances exploration, skill development, and long-term academic growth.

References:

Heicoders Academy – Applied Machine Learning

NUS MComp in Artificial Intelligence

SkillsFuture Singapore

Ministry of Education (MOE) – Post-Secondary Education Account

Career Conversion Programmes (CCP) 

Reeracoen Singapore