Cambridge

Compass House, Cambridge, united kingdom, CB24 9AD

Vision Park is within easy reach of Cambridge city centre and has the advantage of excellent links with the M11 and A14. Trains from London Kings Cross arrive every 30 minutes, with a 15 minute journey by taxi to the Park. Histon Railway Station is on the boundary of Vision Park, which provides high quality, frequent local transport from St Ives to Cambridge. Guided Bus Vision Park lies alongside the Cambridgeshire Guided Bus which offers fast and frequent buses from Histon to Huntingdon (50 minutes), St Ives (15) and Cambridge city centre (15). Onboard, there is air conditioning, free WiFi and power for your laptop and mobile devices. Please see www.thebusway.info for further information.

Explore Our Courses

AI Facial Recognition Development for Law Enforcement

 21 Hours
This instructor-led, live training in Cambridge (online or onsite) is aimed at beginner-level law enforcement personnel who wish to transition from manual facial sketching to using AI tools for developing facial recognition systems. By the end of this training, participants will be able to:
  • Understand the fundamentals of Artificial Intelligence and Machine Learning.
  • Learn the basics of digital image processing and its application in facial recognition.
  • Develop skills in using AI tools and frameworks to create facial recognition models.
  • Gain hands-on experience in creating, training, and testing facial recognition systems.
  • Understand ethical considerations and best practices in the use of facial recognition technology.
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OpenFace: Creating Facial Recognition Systems

 14 Hours
OpenFace is Python and Torch based open-source, real-time facial recognition software based on Google's FaceNet research. In this instructor-led, live training, participants will learn how to use OpenFace's components to create and deploy a sample facial recognition application. By the end of this training, participants will be able to:
  • Work with OpenFace's components, including dlib, OpenVC, Torch, and nn4 to implement face detection, alignment, and transformation
  • Apply OpenFace to real-world applications such as surveillance, identity verification, virtual reality, gaming, and identifying repeat customers, etc.
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Raspberry Pi + OpenCV for Facial Recognition

 21 Hours
This instructor-led, live training introduces the software, hardware, and step-by-step process needed to build a facial recognition system from scratch. Facial Recognition is also known as Face Recognition. The hardware used in this lab includes Rasberry Pi, a camera module, servos (optional), etc. Participants are responsible for purchasing these components themselves. The software used includes OpenCV, Linux, Python, etc. By the end of this training, participants will be able to:
  • Install Linux, OpenCV and other software utilities and libraries on a Rasberry Pi.
  • Configure OpenCV to capture and detect facial images.
  • Understand the various options for packaging a Rasberry Pi system for use in real-world environments.
  • Adapt the system for a variety of use cases, including surveillance, identity verification, etc.
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
Note
  • Other hardware and software options include: Arduino, OpenFace, Windows, etc. If you wish to use any of these, please contact us to arrange.
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Provisional Upcoming Courses (Contact Us For More Information)

Raspberry Pi + OpenCV for Facial Recognition

2025-05-28 09:30
21 hours
Cambridge

OpenFace: Creating Facial Recognition Systems

2025-06-11 09:30
14 hours
Cambridge

AI Facial Recognition Development for Law Enforcement

2025-06-25 09:30
21 hours
Cambridge

OpenFace: Creating Facial Recognition Systems

2025-07-09 09:30
14 hours
Cambridge

OpenFace: Creating Facial Recognition Systems

2025-07-23 09:30
14 hours
Cambridge

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Consulting/Staffing

Face Recognition Consulting
Face Recognition Staffing
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