Master's Program

MSc Artificial Intelligence & Machine Learning

24 months · 120 ECTS · Online/Hybrid · Practitioner faculty

Program Overview

MSc Artificial Intelligence & Machine Learning

PRAKTIX flagship MSc — deep foundations in ML, deep learning, and production AI systems with practitioner faculty and gamified labs.

Unlike traditional masters that treat AI as an elective, PRAKTIX weaves AI into EVERY module — sector-specific application labs, Only Experts content, interactive gamified learning paths, and connections to PRAKTIX's global employer network.

This 24-month program (120 ECTS) spans 4 semesters with 8–10 modules, a research thesis, and a sector capstone project. Learn from practitioner faculty who ship AI in production — not theory alone. Choose standard, interactive (gamified), or hybrid learning modes.

PRAKTIX MSc pricing is ~10% below comparable European online masters (benchmark €15,000/year programs → PRAKTIX €13,500 total).

Curriculum — 4 Semesters

9 modules · 24 months (120 ECTS) · 120 ECTS · Thesis + capstone

Semester 1 — AI Foundations & Research Methods

Machine learning fundamentals, Python for AI, research design, and academic writing for MSc thesis.

Python PyTorch Research methods

Semester 1 — Sector Context & AI Landscape

Industry-specific AI applications, regulatory context, and employer network introduction.

Case studies Only Experts Sector labs

Semester 2 — Advanced AI Methods

Deep learning, model evaluation, MLOps basics, and production deployment patterns.

Deep learning MLOps Eval frameworks

Semester 2 — Gamified Applied Labs

Interactive sector simulations with XP rewards — choose standard, interactive, or hybrid paths.

PRAKTIX gamification Simulations Peer review

Semester 3 — Deep Learning & Neural Architectures

Transformers, CNNs, RNNs, and modern architecture design for production systems.

Transformers CNNs Architecture design

Semester 3 — MLOps & Production AI

Model serving, monitoring, CI/CD for ML, and scalable inference pipelines.

Kubernetes MLflow Monitoring

Semester 4 — Research Thesis

Thesis: Research in Machine Learning & AI Systems — supervised research with academic rigor and industry relevance.

Research Academic writing Supervision

Semester 4 — Capstone: Production ML System Deployment

Industry capstone with mentor support, portfolio evidence, and employer network presentation.

Capstone template Mentor review QR credential

Semester 4 — Employer Network & Career Launch

Global employer connections, portfolio review, and career placement support.

Employer network Portfolio review Career coaching

Thesis: Research in Machine Learning & AI Systems

Supervised research project with academic rigor and industry relevance — mentored by practitioner faculty.

Capstone: Production ML System Deployment

Industry capstone with portfolio evidence and presentation to PRAKTIX employer network partners.

Learning Outcomes & Career Paths

Master deep AI methods with sector-specific application across 4 semesters (120 ECTS)
Complete a research thesis and industry capstone with mentor support and portfolio evidence
Earn PRAKTIX MSc credential with +3600 XP and verified global employer network access
Deploy production-ready AI solutions aligned with EU AI Act and responsible AI standards

ML Engineer AI Research Scientist AI Systems Architect

Expert Faculty

Practitioner faculty and Only Experts content — industry leaders who ship AI in production.

Dr. Elena Richter

PRAKTIX Expert · Industry Practitioner

James Okafor

PRAKTIX Expert · Industry Practitioner

Sophie Laurent

PRAKTIX Expert · Industry Practitioner

Admission Requirements

Bachelor's degree (180 ECTS) in a relevant field or equivalent professional qualification
English proficiency (B2 minimum) for live sessions and thesis writing
Basic programming or domain experience recommended — foundation modules provided
Commitment to complete thesis/capstone and employer network presentation