All trainings Professional AI and data training

Master in Data Science Using Artificial Intelligence

Develop the technical, analytical, and responsible-AI skills to transform raw data into insight, predictive models, intelligent applications, and measurable business value.

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Practical labs Applied AI projects Completion certificate

Training at a glance

0 modulesComplete learning pathway

40 learning hoursLessons, labs, and capstone

Beginner to AdvancedStructured progression

USD 25.00Training fee

Training overview

Build complete data products—not isolated models.

This master training connects programming, statistics, data preparation, visualization, machine learning, deep learning, generative AI, deployment, and governance into one practical journey.

Participants learn by working with realistic datasets, translating business questions into analytical tasks, evaluating models carefully, and communicating results to both technical and nontechnical stakeholders.

Aspiring data scientistsBuild strong foundations and a project portfolio.

Analysts and BI professionalsAdvance into predictive and AI-driven analytics.

Developers and engineersAdd data science and machine learning capabilities.

Business professionalsLearn to frame and lead evidence-based AI initiatives.

Learning outcomes

What you will be able to do

Graduate with an end-to-end workflow for turning business problems and data into responsible AI solutions.

Program with Python

Prepare, analyze, and model data with reliable Python workflows.

Engineer quality data

Collect, clean, validate, query, and transform analytical datasets.

Build predictive models

Train and evaluate regression, classification, clustering, and forecasting models.

Apply generative AI

Use embeddings, large language models, retrieval, and prompt workflows responsibly.

Deploy and monitor

Package models, expose predictions, monitor performance, and manage lifecycle risks.

Communicate insight

Create visual stories, dashboards, recommendations, and stakeholder presentations.

Table of contents

Complete training curriculum

Twelve connected modules progress from foundations to production deployment and a portfolio-ready capstone.

12 modules60 hours1 capstone

Learning experience

Learn by building with real data

Learn

Clear technical foundations, demonstrations, and worked examples.

Practice

Python notebooks, SQL exercises, experiments, and data labs.

Evaluate

Model comparison, quality checks, responsible-AI review, and feedback.

Deliver

An end-to-end capstone solution ready for your professional portfolio.

Data science and artificial intelligence training

Applied data science and AI capability

Training resources

Resources that support practical mastery

Python notebooksReusable demonstrations, exercises, and analytical workflows.

Practice datasetsStructured learning data for analysis, modeling, and visualization.

Project frameworksTemplates for problem framing, experiments, evaluation, and deployment.

Responsible AI checklistGuidance for privacy, bias, explainability, security, and human oversight.

Training FAQs

Questions before enrollment?

No advanced background is required. The training begins with Python and data foundations, although basic computer literacy and comfort with numbers will help.

The program uses Python, Jupyter notebooks, SQL, common data and machine-learning libraries, visualization tools, and modern generative AI workflows.

Yes. The learning pathway is designed for career development and can be delivered in flexible formats for individuals or organizational teams.

Yes. Each stage includes applied work, leading to an end-to-end capstone project suitable for a professional portfolio.

Participants who complete the required modules, practical activities, and capstone can receive a certificate of completion.

Enrollment enquiry

Build your future with data and AI.

Ask about the next session, individual enrollment, payment details, or a tailored delivery plan for your team.

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