Machine Learning Training in Singapore – ML Algorithms, Deep Learning & MLOps

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SoftPro9 runs Machine Learning Engineering training as live online batches in Singapore time, for learners in the CBD, one-north, Jurong East, Tampines and across the island.

  • Covers: Python, NumPy, pandas, scikit-learn, XGBoost, LightGBM, CatBoost, Optuna and more
  • Mode: Live online in Singapore time
  • New batches: Every Monday and Thursday; SGT slots 9:30 AM / 4 PM / 10 PM
  • Duration: 20–24 weeks at 10–12 hours a week, including a production capstone
  • Fee: The current fee is listed on the Machine Learning Engineering course page: /course/machine-learning-ml-training-course. Any cloud ML certification exam is optional and paid directly to the exam provider.
  • Batch size: Up to 15 learners
  • Practice: GPU-enabled cloud notebooks, MLflow tracking server and your own GitHub repositories

Last updated: 28 October 2026

Machine Learning course in Singapore: basic to advanced

Singapore's banks, logistics firms and tech companies hire ML engineers who can build models that meet strict governance standards. The course is split into three levels. You can join at the level that matches your experience after a short assessment at counselling.

Basic

Maths and ML foundations

  • Python, NumPy and pandas for ML work
  • Linear algebra: vectors, matrices, dot products, eigenvectors
  • Calculus for ML: derivatives, gradients and gradient descent
  • Probability, distributions and Bayes' theorem
  • The ML workflow: train/validation/test splits, bias and variance
  • Linear and logistic regression built from scratch, then with scikit-learn
  • Evaluation metrics: RMSE, precision, recall, F1, ROC-AUC

Singapore practice: Data-protection practice under the PDPA.

Intermediate

Algorithms and model building

  • Decision trees, random forests and ensembles
  • Gradient boosting with XGBoost, LightGBM and CatBoost
  • Support vector machines and k-nearest neighbours
  • Clustering (k-means, DBSCAN, hierarchical) and PCA
  • Feature engineering, encoding, scaling and pipelines
  • Hyperparameter tuning with grid search and Optuna
  • Imbalanced data, cross-validation strategies and data leakage
  • Recommender systems: collaborative filtering and matrix factorisation

Singapore practice: Model governance and explainability, in line with Singapore's AI governance guidance.

Advanced

Deep learning and MLOps

  • Neural networks and backpropagation with PyTorch
  • CNNs for images and sequence models for text and time series
  • Transfer learning and fine-tuning pretrained models
  • Time-series forecasting with ML and deep learning
  • Model explainability (SHAP) and fairness checks
  • MLOps: experiment tracking with MLflow, data versioning with DVC
  • Serving models with FastAPI and Docker; batch versus real-time inference
  • Monitoring drift and retraining; intro to Kubernetes, AWS SageMaker and Google Vertex AI

Singapore practice: Multilingual text (English, Chinese, Malay, Tamil) in NLP exercises.

Who joins from Singapore

  • Finance professionals in the CBD moving into data roles
  • Engineers at regional tech offices around one-north
  • Mid-career switchers building a new portfolio

Roles it typically leads to in Singapore

  • Machine-learning engineer
  • ML / MLOps engineer
  • Data scientist (modelling-focused)
  • Applied ML engineer
  • Computer-vision or recommender-systems engineer

Freshers usually start in junior or support versions of these roles.

Machine Learning Engineering – full course details and fee →

Tools you will use

Every tool below is used hands-on in class or in a project, not just mentioned on a slide.

  • Python
  • NumPy
  • pandas
  • scikit-learn
  • XGBoost
  • LightGBM
  • CatBoost
  • Optuna
  • PyTorch
  • TensorFlow / Keras
  • SHAP
  • MLflow
  • DVC
  • FastAPI
  • Docker
  • Kubernetes (intro)
  • AWS SageMaker
  • Google Vertex AI
  • Git & GitHub
  • Jupyter

Projects you will build

  1. A credit-risk model with tuned gradient boosting, SHAP explanations and a fairness check

  2. A product recommender system evaluated against a popularity baseline

  3. An image classifier fine-tuned from a pretrained CNN

  4. A capstone model served through a FastAPI endpoint in Docker, with MLflow tracking and drift monitoring

  5. Singapore project: An HDB resale-price model with documented model-governance checks, using data and conventions from Singapore.

Upcoming Singapore Machine Learning batches

New batches start every Monday and Thursday, with no more than 15 learners in each. Weekday class slots in SGT: 9:30 AM / 4 PM / 10 PM. Weekend slots: 1 PM / 10 PM.

Early-morning and evening SGT slots let learners study before or after the office.

Start dateCourseModeBatch size
Thu, 29 Oct 2026Machine Learning (all levels)Live onlineUp to 15
Mon, 2 Nov 2026Machine Learning (all levels)Live onlineUp to 15
Thu, 5 Nov 2026Machine Learning (all levels)Live onlineUp to 15
Mon, 9 Nov 2026Machine Learning (all levels)Live onlineUp to 15

Message us with the start date and slot you want, and we will confirm your seat.

Reserve on WhatsApp

Machine learning in brief

Machine learning is the part of AI where software learns patterns from data instead of following hand-written rules. A trained model can score a loan application, recommend a product, flag a faulty part or forecast demand, and it improves as it sees more data.

This course goes deeper into the engineering side than a general data science course: how algorithms work under the hood, how to tune and validate them properly, and how to ship, monitor and retrain models in production with MLOps tools such as MLflow, DVC, Docker and cloud ML platforms.

Why machine learning skills matter in Singapore

Singapore is the regional headquarters city for South-East Asia, with banks and fintechs in the CBD and Marina Bay, technology and research companies at one-north, logistics around the port and Changi, and a government that has invested heavily in digital services and AI. Employers here expect polished, production-quality work.

Who hires in Singapore

  • Banking and fintech

    Global and local banks plus a large fintech sector in the CBD and Marina Bay.

  • Technology and research

    Regional tech headquarters and research organisations at one-north and the Science Parks.

  • Logistics and trade

    Port, airport and supply-chain companies managing regional trade flows.

  • Government technology

    Public-sector digital and AI programmes and their vendors.

Singapore context you will work with

Generic courses use generic datasets, and interviewers notice. Our exercises include:

  • SGD pricing and 9% GST in invoice data
  • Data-protection practice under the PDPA
  • Model governance and explainability, in line with Singapore's AI governance guidance
  • Multilingual text (English, Chinese, Malay, Tamil) in NLP exercises
  • Accessibility standards for public-facing web apps

How to choose the right Machine Learning track

Your backgroundStart withWhy
Software developerFull courseYour engineering habits are what MLOps needs
Data analyst with PythonAlgorithms, then MLOpsMove from reporting to models that run in production
Engineering / maths graduateFull courseThe maths module will be a quick refresher
New to programmingPython firstML assumes you are comfortable writing Python
Mainly interested in ChatGPT-style appsArtificial Intelligence courseThat course focuses on LLMs, RAG and agents

Common pairings: Machine Learning + Python (if you are new to coding), Machine Learning + Artificial Intelligence (for generative AI roles), and Machine Learning + DevOps (for MLOps-heavy roles). Learn one course well before adding a second.

From course to first role: a realistic path

  1. Master the maths and ml foundations before moving on.

  2. Build and publish your projects, including the Singapore capstone.

  3. Apply for entry roles such as machine-learning engineer or ml / mlops engineer with employers like the banking and fintech above.

Honest note: freshers usually start in junior or trainee roles, and salaries in Singapore vary too widely for a headline figure. Ask us which openings we are seeing.

Machine Learning certification: what we cover and what we issue

There is no single official machine-learning certification. Cloud vendors run optional exams such as AWS Certified Machine Learning Engineer – Associate, Google Cloud Professional Machine Learning Engineer and Microsoft Azure Data Scientist Associate (DP-100); they are paid directly to the vendor and are not part of our fee. SoftPro9 issues a course completion certificate. Employers mainly judge ML candidates on deployed projects and how well they explain their modelling choices.

What to check before choosing a Machine Learning institute in Singapore

  • A 2026 syllabus: look for Docker, Kubernetes (intro), AWS SageMaker, Google Vertex AI, not only the basics.

  • Projects on your own accounts, a trainer you can meet first, and a published fee with nothing hidden.

  • No "global certification" or "100% placement" claims: vendors run their own exams, and nobody can promise a job.

How our Machine Learning classes work

  • Taught from Bangalore

    Classes are taught live by the same trainers who teach our Bangalore classroom, streamed to Singapore in SGT.

  • Live, with recordings and reviews

    Live sessions in SGT, recordings for revision, and project reviews from the trainer. GPU-enabled cloud notebooks, MLflow tracking server and your own GitHub repositories.

  • Interview preparation

    Mock interviews, resume reviews and referrals to Singapore and remote openings we hear about. We do not guarantee a job.

Machine Learning training across Singapore: which option suits your area

AreaWhereMost learners choose
CBD, Marina Bay, Tanjong PagarCentralLive online, evening slots
one-north, Buona Vista, Science ParkWestLive online
Jurong East, ClementiWestLive online, weekend batches
Tampines, Changi Business Park, WoodlandsEast / northLive online

Singapore batches are live online in SGT (2.5 hours ahead of India); there is no classroom in Singapore.

Where your classes come from

Singapore batches are live online. They are run from our Bangalore centre, which you are welcome to visit if you are ever in the city.

SoftPro9 IT Services – Bangalore
22/1, Opp Infosys, BHBCS Layout, BTM Layout 2nd Stage, BTM Layout, Bengaluru, Karnataka – 560076

Phone: +91 95354 51414

Getting here

We are in BTM Layout 2nd Stage, opposite the Infosys office. The nearest metro is Jayadeva Hospital station, about a 10-minute walk away, and BMTC buses on the Outer Ring Road and Bannerghatta Road stop nearby.

Opening hours

Monday–Friday 9:30 AM–7:30 PM · Saturday 9:30 AM–3:30 PM · Sunday closed

Get directions

Machine Learning training in Singapore: frequently asked questions

How much does Machine Learning training cost in Singapore?

The current training fee is listed on the Machine Learning Engineering course page: /course/machine-learning-ml-training-course. It covers live classes, the practice environment, projects and interview preparation. Any cloud ML certification exam is optional, not included, and paid directly to the exam provider.

How is this different from the Data Science course?

Data Science covers the whole workflow from analysis to modelling and communication. Machine Learning goes deeper into algorithms, tuning and putting models into production with MLOps.

How much maths do I need?

School-level maths is enough to start. We teach the linear algebra, calculus and probability that ML relies on, with code and intuition rather than proofs.

Do you cover MLOps?

Yes. You track experiments with MLflow, version data with DVC, serve models with FastAPI and Docker, and monitor drift.

Do I need a GPU?

No. Deep-learning exercises run in GPU-enabled cloud notebooks we provide.

Is there a classroom in Singapore?

No. Singapore learners join live online batches in Singapore time, with recordings and a 15-learner cap.

Can I use SkillsFuture credit?

Please ask us before planning around SkillsFuture or any other subsidy. We will tell you in writing whether a course qualifies; do not assume it does.

When does the next batch start?

New Machine Learning batches start every Monday and Thursday. See the batch table on this page for the next dates and SGT class slots.

Do you guarantee placement?

No. We provide interview preparation, resume help and referrals to openings we hear about in Singapore, but no institute can honestly guarantee a job.

Other courses in Singapore

Related courses

Machine Learning training in other cities

Talk to us about your Machine Learning course

Tell us your degree, your current job (if any) and where in Singapore you are. We will suggest a track and a batch that fits.

Chat on WhatsAppCall +91 95354 51414