Erreechten Niveau

Mëttelstuf

Dauer

6,00 Mount

2 semesters, with 2 modules per semester. Each module will have one weekly webinar plus complementary course work.

Sprooch(e) vun der Déngschtleeschtung

Nächst Sessioun

07.09.2026

Detailer gesinn

Plaz

Online

Präis

400,00€

Wien organiséiert dës Formatioun?

L'European Business Institute (EBU) est une école de commerce à but non lucratif basée au Luxembourg, proposant des programmes flexibles et de haute qualité en ligne et sur campus, conçus pour les apprenants du monde entier. Engagée en faveur de l'innovation et de l'inclusion, l’EBU donne les moyens aux étudiants — en particulier à ceux issus de régions défavorisées — de réussir grâce à des webinaires interactifs en direct, des certificats vérifiés par blockchain et un corps professoral reconnu à l’international. L'EBU se spécialise dans des domaines de pointe tels que l’intelligence artificielle, la cybersécurité, la blockchain, la robotique et la science des données. En soutien à l’apprentissage tout au long de la vie,l’EBU offre une bourse exclusive de 86% à tous les étudiants avec le code EBULLL25 qui s'applique au moment d'enregistrement. Rejoignez un environnement d’apprentissage collaboratif et constructiviste via Zoom en direct, aux côtés d’étudiants venus de plus de 60 pays.

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Den Inhalt vun dëser Säit ass net op Lëtzebuergesch verfügbar

U wie riicht sech d'Formatioun?

Graduate level

Virkenntnisser

Some subject area knowledge is required.

Ziler

Gain a solid and structured foundation in Artificial Intelligence through this comprehensive professional certificate. Designed to equip you with both theoretical insight and practical understanding, this program includes four university-level courses.

Inhalt

Module 1: Introduction to AI
Module 2: Machine Learning
Module 3: Deep Learning Fundamentals
Module 4: Natural Language Processing

Behandelt Punkten

Module 1: The Introduction to Artificial Intelligence course is designed to help learners decode the mystery of Artificial Intelligence and understand its business applications.

The course provides an overview of Artificial Intelligence concepts and workflows, Machine Learning, Deep Learning, and performance metrics.
Students learn the difference between supervised, unsupervised, and reinforcement learning; are exposed to use cases; and see how clustering and classification algorithms
help identify Artificial Intelligence business applications.

Module 2: This Machine Learning course examines the automation of data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. Students will master Machine Learning concepts and techniques, including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare students for their role with advanced Machine Learning knowledge.
Module 3: This module is designed to help students learn the fundamentals of Deep Learning. It will make students familiar with the concepts of Deep Learning, Convolutional neural networks, and the effectiveness of Deep Learning. This course examines the rapidly growing field of Data Science with neural networks.
Module 4: This Natural Language Processing course will give Students a detailed look at the science

behind applying Machine Learning algorithms to process large amounts of natural language data. Students will learn the concepts of Natural Language understanding, Feature Engineering, Natural Language Generation and Speech Recognition techniques.

Pedagogesch Methoden

The online delivery blends synchronous and asynchronous components. Students complete self-directed assignments hosted on the course platform. Weekly Forums support a required active, rubric-based student contributions that foster collaboration.

Evaluatioun

Exams may include essays, short answers, or MCQs. Formats include open/closed book. Time zones are considered. Assessments are formative and summative. Students have 2 weeks to review grades and must follow the appeal process in the Student Handbook.