Whether delivered online or in-person, these instructor-led live Face Recognition training courses utilize interactive, hands-on exercises to explore both the foundational principles and advanced concepts of Face Recognition.
Face Recognition training is offered in two formats: "online live training" and "onsite live training". Online live training (also referred to as "remote live training") is conducted through an interactive, remote desktop environment. Onsite live training can be hosted directly at your customer premises in Athens or within NobleProg’s corporate training centers located in Athens.
Face Recognition is frequently referred to as Facial Recognition.
Take Metro Line 3 (M3) from Airport toward Dimotiko Theatro.
Get off at Evangelismos.
The address is on Vasilissis Sofias Avenue, very close to the station. Evangelismos station is directly on the avenue.
Allow roughly 40–50 minutes total, depending on waiting/walking time.
From Athens Central Railway Station (Larissa Station)
Take the metro to Syntagma and change to Line 3 toward Doukissis Plakentias/Airport.
Get off at Evangelismos.
Walk to No. 46.
By bus
There are several buses running along Vasilissis Sofias Avenue. Nearby stops include Rigilis Street and Syntagma, while the Evangelismos area is served by multiple bus routes.
The metro is generally the simplest option, especially if you're arriving with luggage.
This instructor-led, live training in Athens (online or onsite) is designed for beginner-level law enforcement officers aiming to transition from manual facial sketching to using AI tools for developing facial recognition systems.
Upon completion of this training, participants will be able to:
Grasp the core principles of Artificial Intelligence and Machine Learning.
Acquire foundational knowledge of digital image processing and its role in facial recognition.
Build proficiency in using AI tools and frameworks to construct facial recognition models.
Gain practical experience in creating, training, and evaluating facial recognition systems.
Comprehend the ethical implications and best practices associated with facial recognition technology.
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