Deep Learning for Computer Vision (5 days)

This course has been held as an online training course since March 2020. Further Information!

Dive into the captivating realm of "Deep Learning for Computer Vision"! Uncover how machines decipher images, opening doors to self-driving cars, facial recognition, and more. Whether you're an aspiring AI engineer or simply curious, this course offers a unique chance to master image analysis.
Join us to explore convolutional neural networks, image classification, and object detection through hands-on projects. No prior experience needed; we'll guide you from basics to advanced techniques. Shape the future with us—where pixels create endless possibilities. Enroll now and let's bring pixels to life!
This seminar can be run as an in-house training course as well, e.g. in England, France, Switzerland, Austria, Italy, Netherland, Luxembourg, Belgium, Canada or Germany.

Target Group:
This course covers deep learning with a focus on Computer Vision


This course covers an introduction to deep learning and applies it to the field of computer vision. Deep learning is a subset of machine learning which utilizes artificial neural networks to recognize complex patterns in data. These networks learn hierarchical features, resulting in powerful models. These models excel in tasks like image recognition and natural language processing.
In this course we will build a neural network from scratch to gain understanding of its internal working. We will look at different architectures, for example convolutional neural networks and more. We will have a look at how to regularize our data and avoid overfitting. On top of this we will use Keras which is build on top of Tensorflow to experiment with more complex network to solve more challenging problems.
  • Introduction to the fundamentals
  • Numpy
  • Plotting with matplotlib and seaborn
  • Short Introduction to machine learning
  • Developing our first neural network from scratch
  • Detecting numbers and characters
  • Challenges of deep learning
    • Bias-Variance Trade-off
    • Over- and under-fitting
  • Introduction to Tensorflow and Keras
  • Convolutional networks
  • Advanced example
  • The topics are more or less the same as in the 3-days variant of this course. The extra two days gives us time to close some gaps in the Python, Numpy and Pandas knowledge of the participants and also additional exercises.

    • From Mon, 22nd Jan, 2024 until Fri, 26th Jan, 2024 (5 days)
    • From Mon, 4th Mar, 2024 until Fri, 8th Mar, 2024 (5 days)
    • From Mon, 13th May, 2024 until Fri, 17th May, 2024 (5 days)
    • From Mon, 1st Jul, 2024 until Fri, 5th Jul, 2024 (5 days)
    • From Mon, 19th Aug, 2024 until Fri, 23rd Aug, 2024 (5 days)
    • From Mon, 16th Sep, 2024 until Fri, 20th Sep, 2024 (5 days)

    Duration of the course:
    5 days

    The fees for this ML course per day:

    €419 per day (exclusive of VAT)
    Toronto, Canada:
    $588 per day (exclusive of HST)
    Lake Constance, Hemmenhofen, Germany:
    €419 per day (exclusive of VAT)
    plus € 139 for full board and lodging in 4 star hotel
    Hamburg, Munich, Frankfurt, Berlin (Germany):
    €447 per day (exclusive of VAT)
    Zurich and Geneva (Switzerland):
    £447 per day (exclusive of VAT)


    The price comprises:
    Comprehensive course material

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