Data-Science & ML Fundamentals

Core machine-learning literacy for analysts and power users. Participants learn the difference between supervised and unsupervised learning, work through regression and classification intuitively, understand how models are evaluated, and get hands-on with no-code ML tools so the concepts stick without a coding prerequisite.

This is a conceptual and practical grounding rather than a mathematics course, aimed at analysts and technical staff who need to understand what machine learning can and cannot do before committing to a project. Participants work through the model lifecycle: framing a problem, preparing features, splitting data honestly, training, and evaluating with metrics that suit the question rather than the ones that look best. Supervised and unsupervised approaches are both covered, along with overfitting, class imbalance and the specific ways a model that scores well in testing fails in production. Python and scikit-learn are used throughout, so prior comfort with Python helps.

HRD Corp Training Provider MalaysiaHRD Corp SBL-Khas Claimable

Programme Modules

01

Supervised vs Unsupervised

The two families of ML, when each applies, and examples participants will recognise from their own work.

02

Regression & Classification

Predicting a number vs predicting a category, with worked examples and the intuitions behind each.

03

Model Evaluation

Train/test splits, accuracy, precision/recall, and why a 'good' score can still be a bad model.

04

No-Code ML Tools

Building and comparing models in a visual tool, interpreting outputs, and knowing the limits of auto-ML.

Key Outcomes

  • Distinguish supervised and unsupervised learning
  • Explain regression and classification intuitively
  • Read and challenge model-evaluation metrics
  • Build a model in a no-code ML tool
  • Spot where ML helps, and where it doesn't

Training Mode   Physical / Online / Hybrid / e-learning

HRD Corp   SBL-Khas Claimable

Duration   1 Day

Training Hours   9:00 AM to 5:00 PM

Level   Intermediate (analyst level)

Certificate   None, Orbix own course. Delivered as an HRD Corp claimable workshop with an Orbix certificate of completion.

Frequently Asked Questions

Yes. Data-Science & ML Fundamentals is HRD Corp SBL-Khas claimable. Employers registered with HRD Corp (PSMB) can claim the training fee against their levy, as Orbix Tech Sdn Bhd is an HRD Corp certified training provider. Submit the SBL-Khas application before the session date.

Data-Science & ML Fundamentals runs for 1 day, 9:00 AM to 5:00 PM. It is delivered as an in-house closed group session, so the schedule can be adjusted to fit your team's working hours.

Yes. Delivery options are physical, online, hybrid, e-learning. In-house sessions run at your premises anywhere in Malaysia, online sessions run live over video conference, and hybrid combines both for teams split across sites.

None, Orbix own course. Delivered as an HRD Corp claimable workshop with an Orbix certificate of completion. Each certificate carries a certificate number that can be checked at orbixtech.my/certificate-verify.

Level: Intermediate (analyst level). The session is built around worked examples and group exercises rather than theory, so participants apply the material to their own organisation during the session.

Half-day and full-day sessions are quoted per session for a closed group, from RM 800 and RM 1,750 respectively. Advanced 2-day programmes are quoted per participant, from RM 4,000. All figures are before any HRD Corp levy claim.