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Machine Learning Certification Training in Singapore (Classroom)

80-hour in-person Machine Learning training in Singapore CBD. DBS, Grab and AWS practitioner trainers, 5 capstone projects, MLOps with MLflow and SageMaker, industry-recognised certificate, placement support.

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Call Us: +65-3138-8060
Officially accredited by
PMI Authorized Training Partner
PeopleCert Accredited Training Organisation
ITIL Accredited Training Organisation
75,000+ trained
50 Contact Hours
What is this course?

Machine Learning certification training in Singapore prepares you for ML engineer and applied scientist roles at DBS, OCBC, UOB, Grab, Sea, ByteDance, Google APAC, Meta APAC and AWS Singapore. Learners Ink's 80-hour live cohort covers supervised and unsupervised learning, deep learning with TensorFlow and PyTorch, MLOps with MLflow and SageMaker, responsible ML aligned to MAS Veritas, and 5 capstone projects on Singapore BFSI, e-commerce and public sector datasets.

Pick your delivery format
Same curriculum, same instructors, same certificate.
Upcoming Batches

Upcoming ML Training Batches in Singapore

Classroom cohorts in Singapore. Small group sizes, named instructors, money-back guarantee.

Start DateModeScheduleFee (SGD)SeatsAction
Weekend BatchJuly 25-26 and August 1-2, 2026 (4-day weekend)
Classroom, Singapore2 weekends (4 days), Sat-Sun, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Filling fast
Book Now
Weekday BatchJuly 28-31, 2026 (4-day intensive)
Classroom, Singapore4-day intensive, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
12 of 25 left
Book Now
Weekend BatchAugust 22-23 and August 29-30, 2026 (4-day weekend)
Classroom, Singapore2 weekends (4 days), Sat-Sun, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Weekday BatchAugust 25-28, 2026 (4-day intensive)
Classroom, Singapore4-day intensive, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Weekend BatchSeptember 19-20 and September 26-27, 2026 (4-day weekend)
Classroom, Singapore2 weekends (4 days), Sat-Sun, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Weekday BatchSeptember 22-25, 2026 (4-day intensive)
Classroom, Singapore4-day intensive, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Weekend BatchOctober 24-25 and October 31 - November 1, 2026 (4-day weekend)
Classroom, Singapore2 weekends (4 days), Sat-Sun, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Weekday BatchOctober 27-30, 2026 (4-day intensive)
Classroom, Singapore4-day intensive, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Weekday BatchNovember 17-20, 2026 (4-day intensive)
Classroom, Singapore4-day intensive, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Weekend BatchNovember 21-22 and November 28-29, 2026 (4-day weekend)
Classroom, Singapore2 weekends (4 days), Sat-Sun, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Weekend BatchDecember 12-13 and December 19-20, 2026 (4-day weekend)
Classroom, Singapore2 weekends (4 days), Sat-Sun, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Weekday BatchDecember 15-18, 2026 (4-day intensive)
Classroom, Singapore4-day intensive, 9am to 5pm Singapore time
$2,199$1,799Early Bird, save $400
Open
Book Now
Program Highlights

What Makes Our ML Program in Singapore Different

Industry-Aligned Certificate

Learners Ink Machine Learning certificate plus aligned pathways to AWS ML Specialty, Microsoft DP-100 and Databricks ML credentials.

Production-Grade Pipelines

Build reproducible scikit-learn and PyTorch pipelines with MLflow tracking, FastAPI serving and Docker packaging.

Deployment Capstone

Ship a real ML service end-to-end: dataset to API with monitoring, drift detection and stakeholder defence.

Deep Learning Depth

CNNs, RNNs, Transformers and transfer learning with PyTorch on real image, text and tabular tasks.

Senior ML Engineer Instructors

Practitioners from FAANG, GCC banks and Big 4 with active production ML and MLOps experience.

2 Full-Length Practice Tests

100-question simulated assessments with answers and explanations across classical ML, DL and MLOps.

S$112,000 to S$188,000
Average ML salary in Singapore (2026)
50 Hours
Learners Ink aligned instructor-led training
2,000+ Q
Practice questions + 2 full-length practice tests
42%
Median ML salary uplift vs non-certified

Why Get ML Certified in Singapore?

Singapore is Southeast Asia's AI and machine learning capital. The Smart Nation initiative, the National AI Strategy 2.0 and AI Singapore have created sustained demand for ML engineers and applied scientists at DBS, OCBC, UOB, Standard Chartered, GIC, Temasek, MAS, Singtel, Grab, Sea (Shopee), Razer, ByteDance Singapore, TikTok, Google APAC, Meta APAC, Stripe APAC, Amazon AWS and the global research arms of Salesforce and ServiceNow.

Government grants under IMDA's TechSkills Accelerator and the SkillsFuture credit scheme directly subsidise ML upskilling for Singapore citizens and PRs, and the MAS Veritas framework has institutionalised responsible ML in financial services. ML engineer postings in Singapore exceeded 4,200 in the last quarter on LinkedIn alone.

Learners Ink's Machine Learning program in Singapore is delivered by practitioners from DBS, Grab, Sea and AWS Singapore. The cohort blends 80 hours of live instruction with hands-on lab work on Python, scikit-learn, TensorFlow, PyTorch, MLflow, SageMaker and Vertex AI, with capstones drawn from Singapore BFSI, e-commerce and public sector datasets.

Certified ML engineers in Singapore earn SGD 90,000 to 130,000 at 2 to 5 years, SGD 140,000 to 200,000 at senior IC, and SGD 220,000 to 340,000 plus equity at staff and principal levels at Grab, Sea, ByteDance and the BFSI majors. Singapore's tax regime keeps take-home strong relative to peers in HK and Sydney.

Learning Outcomes

What You Will Master in this ML Program

Twelve outcome pillars mapped to the PMI® Examination Content Outline, with deep practice across People, Process and Business Environment.

Classical ML Mastery

Regression, classification, ensembles, clustering and dimensionality reduction with rigorous evaluation.

Pipelines and Reproducibility

scikit-learn Pipelines, ColumnTransformer, MLflow tracking, model registry and versioning.

Deep Learning with PyTorch

Neural networks, CNNs, RNNs, Transformers and transfer learning on real datasets.

Applied GenAI for ML

Use LLM APIs and RAG patterns for feature ideation, data labelling and model evaluation.

MLOps

FastAPI serving, Docker, CI/CD for ML, model monitoring, drift detection and retraining triggers.

Advanced Evaluation

Cross-validation strategies, calibration, fairness, uncertainty and explainability with SHAP and LIME.

Hyperparameter Optimisation

GridSearch, RandomSearch, Bayesian optimisation with Optuna and automated ML basics.

Recommender and Ranking

Collaborative filtering, matrix factorisation, learning-to-rank and embedding-based retrieval.

Big Data ML

PySpark MLlib, distributed training intro and feature stores.

Deployment Capstone

Ship a real ML service end-to-end with monitoring, alerting and defence presentation.

Responsible AI

Bias, fairness, privacy, explainability and governance for production ML.

ML Engineer Portfolio

Public GitHub portfolio, deployed demos and a polished case-study writeup.

Skills Covered

70+ Data Science & AI Skills You Will Build

Core Machine Learning Certification Training competencies aligned to the latest Learners Ink exam blueprint, ready to apply on day one.

Python 3.11scikit-learnXGBoostLightGBMCatBoostPyTorchTensorFlow basicsHugging Face TransformersOptunaMLflowFastAPIDockerKubernetes basicsGitHub Actions for MLDVCFeature Stores introPySpark MLlibRegressionClassificationEnsemblesBoostingStackingClusteringPCARecommender SystemsLearning to RankTime Series MLAnomaly DetectionNeural NetworksCNNRNN and LSTMTransformer ArchitecturesAttentionTransfer LearningImage ClassificationObject Detection IntroNLP PipelinesTokenisationEmbeddingsCross-ValidationBayesian Hyperparameter TuningAutoML IntroCalibrationROC/AUCBias-Variance Trade-offClass ImbalanceSMOTECost-Sensitive LearningSHAPLIMEPermutation ImportanceCounterfactual ExplanationsFairness MetricsModel MonitoringData DriftConcept DriftChampion-ChallengerShadow DeploymentA/B Testing for MLOnline LearningReinforcement Learning IntroPrompt EngineeringLLM APIsRAGVector DatabasesEmbedding SearchResponsible AIDifferential Privacy IntroModel CardsData Sheets
In-Person Classroom

Why Choose Classroom ML Training in Singapore?

In-person learning delivers focus, networking and instructor engagement you cannot replicate online. Here is what makes our classroom cohorts stand out.

In-Person Pair Programming

Side-by-side coding and ML system design on whiteboards.

Peer Networking and Study Groups

Build a network with ML engineers from leading employers.

Hands-On Lab Energy

50+ Jupyter and PyTorch labs with mentor code reviews.

Distraction-Free Learning

A dedicated training venue removes home distractions for 50 intensive hours.

Premium Training Venues

Centrally located with full amenities, printed materials and parking.

Same Curriculum, In-Person Energy

Identical 50-hour ML curriculum with the energy of in-room workshops.

Prefer the Live Online Virtual Classroom? Same curriculum, same instructors, same certificate.
View Live Online Program
Interactive ROI Tools

Calculate Your PMP Return on Investment in Singapore

Three quick calculators to model your salary uplift, course payback period, and long-term career projection. All figures are indicative, based on PMI Earning Power data and local salary benchmarks.

10 years
Assumes a 42% salary premium for PMP-certified professionals, per PMI Earning Power Salary Survey.
Post-PMP Annual Salary
SGD 144,840
Annual Uplift
+SGD 42,840
10-Year Lifetime Gain
SGD 428,400

Top Industries in Singapore that Hire ML-Certified Professionals

Verified demand across the leading sectors driving ML hiring in Singapore, with the marquee employers in each industry.

Banking and Financial Services

DBS Bank, OCBC Bank

DBS, OCBC, UOB, and global investment banks anchor APAC PMOs in Singapore.

Technology and Digital

Grab

Grab, Sea, and global tech APAC HQs run continuous product and platform programs.

Shipping, Logistics and Trade

DBS Bank, OCBC Bank, Grab

PSA, Maersk, and ONE run global maritime programs from Singapore.

Government and Smart Nation

DBS Bank, OCBC Bank, Grab

Smart Nation initiatives and GovTech programs require certified PMs across ministries.

Pharmaceuticals and Biotech

DBS Bank, OCBC Bank, Grab

Tuas Biomedical Park hosts global pharma manufacturing and R&D programs.

Construction and Infrastructure

DBS Bank, OCBC Bank, Grab

LTA, BCA, and HDB run sustained capex programs including MRT expansion and HDB upgrades.

Leading Singapore Employers Hiring ML-Certified Talent

Verified hiring patterns from the largest employers in Singapore. ML-certified candidates are actively preferred or required for these roles.

EmployerIndustryWhy ML MattersTypical Roles
DBS BankBankingLargest Southeast Asian bank, deep digital transformation PMO.ML aligned senior delivery roles
OCBC BankBankingActive hirer of PMs across wealth, retail, and corporate banking.ML aligned senior delivery roles
GrabTechnologyAPAC super-app headquartered in Singapore with sustained PM hiring.ML aligned senior delivery roles
SingtelTelecom5G and digital transformation programs across the group.ML aligned senior delivery roles
PSA InternationalShippingGlobal port operator running terminal modernisation programs.ML aligned senior delivery roles
Shopee (Sea)E-commerceRegional e-commerce leader running continuous platform programs.ML aligned senior delivery roles
GICSovereign WealthGlobal investment programs require disciplined PM leadership.ML aligned senior delivery roles
Accenture SingaporeConsultingAPAC delivery centre, PMP a baseline for senior consultants.ML aligned senior delivery roles

Top ML Designations and Career Tracks in Singapore

The most in-demand ML-tagged designations and the value each adds to your career.

Project Manager

Most-posted PM title in Singapore across banking, tech, and government.

APAC Program Manager

Regional program leadership at MNCs headquartered in Singapore.

PMO Manager

Banking and government PMO governance roles.

Digital Transformation Lead

DBS, OCBC, and tech firms running enterprise transformation.

Construction Project Manager

LTA and HDB capex programs.

Engagement Manager

Big Four APAC offices in Singapore.

Salary & Career Path

ML Salary Progression in Singapore

Source: NodeFlair Singapore tech salary report 2026, MAS Financial Sector Workforce Survey, Glassdoor Singapore ML engineer bands and live LinkedIn postings. ML engineers in Singapore earn a 30 to 45 percent premium over generalist software engineers at the same year-band, with applied scientists at Grab, Sea, DBS and ByteDance commanding the top of the range.

Salary Bands (Midpoint Visualised)
Associate PM (0-3 yrs)
S$68,000 to S$100,000
Years of experience: 0-3
Project Manager (3-6 yrs)
S$96,000 to S$140,000
Years of experience: 3-6
Senior PM (6-10 yrs)
S$130,000 to S$192,000
Years of experience: 6-10
Program Manager (10-15 yrs)
S$165,000 to S$245,000
Years of experience: 10-15
PMO Director (15+ yrs)
S$210,000 to S$335,000
Years of experience: 15+
Practice & Mock Exams

2 Full-Length Practice Tests with Answers and Explanations

Two complete 180-question simulations modelled on the live PMI exam, with detailed answer keys, rationale for every option and instructor-led debriefs. Access is gated, share your details and we unlock both tests instantly.

01

Machine Learning Proficiency Test 1 (Full Length)

100 Q180 min

Full simulation across classical ML, deep learning and MLOps with code-reading items, answer rationale and skill-gap map

02

Machine Learning Proficiency Test 2 (Full Length)

100 Q180 min

Second full simulation with ML scenario stems, MLOps and Responsible AI items, target 75%+ before capstone defence

Pass guarantee: achieve 75% on both full-length practice tests and we back you with a written ML pass guarantee.

Free ML Resources & Downloads

Free ML Study Resources for Singapore Learners

Download our complete library of free ML preparation resources, no email gate on the practice test, just instant access.

Most Popular
Practice Test

Free ML Mini Practice Test (25 Questions)

Classical ML, DL and MLOps mini test with instant scoring and answer rationale.

PDF Download

ML Algorithms One-Pager (PDF)

All major supervised and unsupervised algorithms with use cases and trade-offs.

PDF Download

MLOps Reference Architecture

End-to-end MLOps reference: training, registry, serving, monitoring and retraining.

PDF Download

Deep Learning Cheat Sheet

Architectures, losses, optimisers and regularisation on a printable reference page.

Research Report

ML Engineer Salary Benchmark 2026

City-by-city ML Engineer and Applied Scientist salary data from LinkedIn and Glassdoor.

Template

10-Week ML Study Planner

Day-by-day editable planner with mini-project and capstone checkpoints.

Brochure

Brochure: Learners Ink ML Program

Course outline, fee schedule, batch calendar and instructor profiles.

Your ML Roadmap

From Enrolment to ML, a Six-Step Journey

Most learners complete the full journey in 8 to 12 weeks. We support you end-to-end, from eligibility check to PMI® application narrative and sitting the exam.

1

Career Counselling Call

Free 30-minute call to map your background and confirm ML readiness.

2

Enrol and Pre-Work

Receive Python and math refresher pack, environment setup and access to the LMS.

3

50-Hour Training

Live cohort across classical ML, deep learning, MLOps, applied GenAI and Responsible AI.

4

Graded Projects

Complete 4 graded ML projects: tabular, NLP, computer vision and time series.

5

Deployment Capstone

Ship an end-to-end ML service with FastAPI, Docker, MLflow and monitoring.

6

Earn Your Certificate

Pass the internal proficiency assessment plus capstone defence to receive your Learners Ink ML certificate.

Course Overview

ML Certification Training, Course Overview

The Learners Ink Machine Learning program in Singapore runs 80 hours of live instructor-led training across weekends or weekday evenings, with CBD classroom or live online options. The curriculum spans Python foundations, statistics, supervised and unsupervised ML with scikit-learn, deep learning with TensorFlow and PyTorch, MLOps and deployment with MLflow, SageMaker and Vertex AI, and 5 capstones on credit scoring (MAS aligned), demand forecasting, recommendation systems, NLP sentiment and computer vision quality inspection.

What You Will Learn

  • Classical ML: regression, classification, ensembles, clustering, recommenders
  • Deep learning: NN, CNN, RNN, Transformers and transfer learning with PyTorch
  • Hyperparameter optimisation: Optuna, AutoML basics
  • MLOps: MLflow, FastAPI, Docker, CI/CD for ML, monitoring and drift
  • Applied GenAI for ML teams: LLM APIs, RAG, vector databases
  • Embeddings, semantic search and retrieval-augmented patterns
  • Responsible AI: fairness, explainability, model cards, data sheets
  • ML system design and architecture trade-offs
  • 1,000+ practice questions plus 2 full-length proficiency tests with answers and explanations
  • Deployment capstone: end-to-end ML service with monitoring and defence
  • ML Engineer portfolio: GitHub repos, deployed demos, case-study writeups
  • Interview readiness: coding, math, ML system design and behavioural
Course Details
Course NameMachine Learning Certification Training (Classroom)
Duration50 Contact Hours
FormatIn-Person Classroom, Singapore
AccreditationIndustry-aligned, capstone-based
Certification BodyLearners Ink
Class SizeMax 18 per cohort, personalised attention
CertificateCertificate of Completion from Learners Ink
Exam Prep2,000+ Practice Questions + 2 Full-Length Practice Tests with Answers and Explanations
Course Fee$1,799 (Early Bird) - was $2,199
Contact+65-3138-8060
Emailsupport@learnersink.com
Eligibility

ML Exam Eligibility Requirements

Review the eligibility pathway that matches your background. The Learners Ink Machine Learning Certification Training programme is designed to satisfy the Learners Ink prerequisites end-to-end.

Pathway: Learners Ink Machine Learning Certificate

  • Working Python, pandas/NumPy and basic statistics required
  • Complete 50 hours of live instructor-led training
  • Submit 4 graded ML projects across tabular, NLP, CV and time series
  • Pass the internal proficiency assessment (100 questions, 70 percent pass mark)
  • Complete and defend the deployment capstone with monitoring
  • Optional: prepare for AWS ML Specialty, Microsoft DP-100 or Databricks ML credentials

Who Should Attend This ML Training in Singapore?

Ideal for professionals who lead, manage or coordinate projects and are ready to earn a globally recognised credential.

Aspiring ML Engineer

End-to-end production-grade ML from classical to deep learning to MLOps

Data Scientist

Level up from notebooks into deployed, monitored ML systems

Software Engineer

Pivot into ML Engineering and Applied Science roles

Data Engineer

Add modelling, training and deployment depth to data platform skills

Backend Engineer

Build production ML services with FastAPI, Docker and CI/CD for ML

AI Researcher

Add MLOps, deployment and Responsible AI to research depth

Product Manager

Lead ML-powered products with hands-on system design literacy

Tech Lead / Architect

Design ML platforms, feature stores and monitoring strategies

DevOps / SRE

Specialise into MLOps and ML platform engineering

Quant Analyst

Modernise quant pipelines with production ML and DL

Domain SME

Healthcare, retail, banking and telecoms SMEs leading ML initiatives

PhD / Researcher

Translate research skills into industry ML Engineer roles

Career Switcher

Structured ML program with capstone and portfolio output

Consultant

Lead client ML engagements with credible production experience

Cloud Engineer

Specialise into ML platform engineering on AWS, Azure or GCP

Full ML Syllabus

ML Certification Training Curriculum

6 domains, 28 modules covering every objective on the current Machine Learning Certification Training blueprint from Learners Ink.

Rigorous classical ML with scikit-learn pipelines and evaluation.

1.1 Regression

  • Linear, Ridge, Lasso, ElasticNet
  • Polynomial features and splines
  • Quantile and robust regression
  • Diagnostics and assumptions

1.2 Classification

  • Logistic Regression
  • Decision Trees
  • k-NN, Naive Bayes, SVM
  • Class imbalance and SMOTE

1.3 Ensembles

  • Bagging and Random Forests
  • Gradient Boosting
  • XGBoost, LightGBM, CatBoost
  • Stacking and blending

1.4 Evaluation

  • K-Fold, Stratified, GroupKFold
  • Calibration and threshold tuning
  • ROC AUC, PR AUC, F1, MCC
  • Bias-variance trade-off

1.5 Pipelines and Reproducibility

  • scikit-learn Pipeline and ColumnTransformer
  • Leakage prevention
  • MLflow tracking and registry
  • Seed and environment pinning

Why Choose Learners Ink for Your ML Certification in Singapore?

Production-Grade 50-Hour Curriculum

Classical ML through deployment: DL, MLOps, applied GenAI and Responsible AI.

Senior ML Engineer Trainers

Instructors from FAANG, GCC banks, Big 4 with active production ML and MLOps experience.

AXELOS, PMI, Scrum Alliance Accredited

Also officially accredited for PRINCE2, ITIL, PMI and Scrum Alliance credentials.

75,000+ Professionals Trained

Across Fortune 500 companies and government agencies since 2019.

100% Live Classes

Every class is live, never pre-recorded, with real-time Q&A and pair coding.

Real Deployment Capstone

End-to-end FastAPI + Docker + monitoring deployment, not toy notebooks.

Multiple Delivery Formats

Weekday, weekend or accelerated bootcamp, live online or in-person.

Applied GenAI Module

LLM APIs, RAG, embeddings and prompt engineering for ML teams.

MLOps Depth

MLflow, CI/CD for ML, monitoring, drift, champion-challenger patterns.

Responsible AI Coverage

Fairness, SHAP/LIME, model cards and data sheets in every capstone.

Rated 4.7 / 5 on Trustpilot

Real reviews from ML alumni across the USA, UK, UAE, Australia and India.

100% Money-Back Guarantee

If our training does not meet your expectations, a full refund is available.

Free Re-Sit Within 12 Months

Re-attend any future cohort, classroom or live online, free of cost for revision.

ML System Design Mocks

Mock interviews on coding, math and ML system design with senior practitioners.

Career Services

Resume polish, LinkedIn makeover, mock interviews and curated ML job board.

Corporate and Group Training

Tailored in-house ML programs for teams of 5+ with group pricing.

Optional Vendor Pathways

Aligned to AWS ML Specialty, Microsoft DP-100 and Databricks ML credentials.

Globally Recognised Certificate

Receive your Learners Ink ML certificate, capstone defence credit and digital badge.

How We Compare

Learners Ink vs Other ML Training Providers

A transparent, feature-by-feature comparison so you can make an informed choice.

FeatureLearners InkTypical Other Providers
Curriculum Depth
50 hours: classical ML, DL, MLOps, applied GenAI and Responsible AI
Often 25 to 35 hours, classical ML only
Trainer Quality
Senior ML engineers from FAANG, GCC banks, Big 4
Recorded video instructors with limited production ML experience
Live vs Pre-recorded
100% live instructor-led, real-time code and design reviews
Often pre-recorded with limited mentor access
Deployment Capstone
Real FastAPI + Docker + monitoring deployment with defence
Toy notebooks without deployment
MLOps Coverage
MLflow, CI/CD for ML, monitoring, drift, champion-challenger
Skipped or surface-level
GenAI Coverage
Applied GenAI, RAG and embeddings for ML teams
Rarely included
Responsible AI
Fairness, SHAP/LIME, model cards, data sheets
Skipped
Career Services
Resume, LinkedIn, ML system design mocks, curated job board
Limited or upsell
Choose Your Format

Classroom vs Live Online vs Hybrid ML Training

Side-by-side comparison of our three ML delivery formats so you can pick what fits your schedule, learning style and budget.

DimensionClassroom (In-Person)Live Online (Virtual)Hybrid (Blended)
Delivery ModePhysical classroom, in-room instructorLive Zoom or Microsoft Teams, real-time instructorMix of classroom days plus live online sessions
Learners Ink AccreditedYes, Learners Ink-aligned curriculumYes, Learners Ink-aligned curriculumYes, Learners Ink-aligned curriculum
Curriculum HoursFull Machine Learning Certification Training blueprint coverageFull Machine Learning Certification Training blueprint coverageFull Machine Learning Certification Training blueprint coverage
Interaction LevelHighest, in-room peer and instructorHigh, breakouts, polls, live Q&AVery high, classroom days plus virtual reinforcement
Schedule FlexibilityFixed venue and datesMost flexible, weekday or weekend cohortsModerate, anchored to classroom days
Travel and CommuteDaily commute to venueZero commute, learn from anywherePartial commute on classroom days only
Session RecordingsNot recordedRecorded, 90 days portal accessOnline sessions recorded, classroom days are live only
NetworkingStrongest in-room networkingGlobal cohort networking via virtual breakoutsBest of both, in-person plus global cohort
Typical Fee RangePremium, includes venue and refreshments20 to 25 percent lower than classroomMid-range between classroom and live online
Best FitLearners who thrive on in-room energy and local networkingWorking professionals, frequent travellers, global learnersLearners who want classroom rigour with online convenience

Note: Hybrid cohorts are available on request for corporate batches of 8 or more learners. Speak to a counsellor to design a blended schedule.

Meet Your Instructors

Senior Practitioners, Not Career Trainers

DR

Dr. Ravi Bhardwaj

PhD ML, ex-FAANG Staff ML Engineer, Kaggle Grandmaster

Ravi has 14+ years of production ML at FAANG scale, with deep expertise in ranking, recommender systems and large-scale training infrastructure.

HA

Hala Al-Mansoori

MSc AI, AWS ML Specialty, MLOps practitioner

Hala leads MLOps engineering at a GCC tier-1 bank. She specialises in regulated-industry ML, fairness audits and real-time inference platforms.

ML

Marcus Lee

MS CS, Microsoft DP-100, Databricks Certified

Marcus has 11+ years of applied ML across retail and telecoms, with hands-on Transformer fine-tuning and production LLM deployment experience.

Student Reviews

What Our Students Say About Learners Ink ML Training

Rated 4.7 / 5 from 170+ verified students
"Joined the Learners Ink ML cohort serving Singapore learners. PyTorch module was production-quality, and the local cohort dynamics across Singapore made the experience genuinely worth the fee."
Karthik R.
ML Engineer, Indian SaaS , Singapore
"Joined the Learners Ink ML cohort serving Singapore learners. MLflow lab was exactly what I needed, and the local cohort dynamics across Singapore made the experience genuinely worth the fee."
Jenna T.
Senior DS turned MLE, US fintech , Singapore
"Joined the Learners Ink ML cohort serving Singapore learners. Ensemble methods finally made sense, and the local cohort dynamics across Singapore made the experience genuinely worth the fee."
Yuto S.
ML Engineer, Japan AI startup , Singapore
"Joined the Learners Ink ML cohort serving Singapore learners. End-to-end pipeline was the whole point, and the local cohort dynamics across Singapore made the experience genuinely worth the fee."
Camila P.
ML Lead, Brazil e-commerce , Singapore
Career Services & Alumni Support

Beyond Certification, A Career Services Layer

ML is a career inflection point. Our learners get end-to-end support, from resume positioning and LinkedIn® optimisation to mock interviews and a curated ML job board.

Resume and CV Review

ML Engineer-aligned CV review optimised for ATS keywords and recruiter scans.

LinkedIn Profile Makeover

Reposition for ML Engineer, Applied Scientist and Data Scientist recruiter searches.

Mock Interview Coaching

ML system design, coding, math and case interviews with senior practitioners.

Curated ML Job Board

Hand-picked ML and Applied Scientist roles across product, fintech, healthcare and consulting.

Alumni Network

Join Learners Ink ML alumni at FAANG, GCC banks, Big 4 and AI-native startups.

Portfolio Coaching

GitHub repo polishing, deployed demo reviews and Kaggle submission strategy.

FAQs

Frequently Asked Questions, ML Training in Singapore

Related Cities

ML Training in Cities Near Singapore

Same Machine Learning Certification Training curriculum, locally relevant employer, salary and exam-centre context for nearby metros.

Ready to Become a Singapore ML Engineer?

Join the next Singapore CBD cohort. 80 live hours, 5 capstones, full MLOps stack.

Rated 4.7 / 5 on Trustpilot