MACHINE LEARNING

Build models that
learn from data.

Learn the core workflow behind machine learning—from preparing data and selecting features to training, evaluating and improving practical predictive models.

Explore curriculum Course details

FormatIndependent courseLearning stylePractical & project-orientedAccessLearn at your pace

Machine Learning workspaceLEARN → APPLY

TOOLPython

TOOLScikit-learn

TOOLPandas

PRACTICAL LEARNINGBuild capability through application.

Learn concepts, work with data and apply what you understand.

WHAT YOU'LL BUILD

Skills you can
actually use.

Focused learning designed around understanding, practice and application.

ML foundations

Understand supervised learning, features, targets and the model workflow.

Data preparation

Prepare datasets and features for model training.

Model building

Train practical baseline models using common algorithms.

Evaluation

Measure model performance and understand where a model succeeds or fails.

CORE TOOLKIT

Work with the tools behind the workflow.

PYPythonBuild the ML workflowSKScikit-learnTrain & evaluate modelsPDPandasPrepare model-ready data

CURRICULUM PREVIEW

Structured learning.
Practical direction.

This is the course direction; detailed lessons can be managed in the LMS as final content is produced.

MODULE 01Machine learning foundationsModels, features, targets and the end-to-end workflow.Foundation

MODULE 02Preparing data for MLCleaning, encoding and creating model-ready inputs.Data

MODULE 03Supervised learningRegression and classification concepts with practical models.Models

MODULE 04Model evaluationMetrics, validation and comparing model performance.Evaluation

MODULE 05Applied prediction projectBuild and evaluate a model around a realistic prediction task.Project

PROJECT-ORIENTED LEARNING

Apply what
you learn.

Use a realistic problem to connect concepts, tools and decisions.

EXAMPLE PROJECT DIRECTION

Practical prediction model

Data→Explore→Build→Evaluate

Project scope can evolve as the final curriculum is produced.

WHO IT'S FOR

Choose this course if it matches the skill you want to build.

Python learnersApply Python to predictive problems.

Data professionalsAdd machine-learning concepts to existing data skills.

DevelopersUnderstand how practical ML models are built and evaluated.

Career learnersExplore ML through a structured, application-focused course.

COURSE FAQ

Before you begin.

Is this a separate course?

Yes. Machine Learning is offered independently and is not part of a forced bundle.

Do I have to complete another eLearningz course first?

No. It is a separate course. The final page will clearly state any Python/statistics knowledge recommended for the curriculum; another eLearningz purchase will not be mandatory.

Is this a subscription?

No. eLearningz is being built around individual course enrollment.

Will there be practical work?

Yes. The course direction includes exercises and project-oriented application.

INDIVIDUAL COURSE

Ready to learn this skill?

Enrollment will open when this course is published in the LMS catalog.

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Build models thatlearn from data.

Skills you canactually use.