The first online course to teach C# developers how to create deep learning applications in C# with CNTK neural networks​

This course will introduce you to Deep Learning and Neural Networks and get you up to speed with Microsoft's Cognitive Toolkit (CNTK) library.


You will build a solid foundation in deep learning and learn how to design, train, and evaluate deep neural networks. You'll be building C# applications from day one and I will provide you with all the source code, libraries, and data sets you need to get going.


I will coach you in our private support group where you can hang out with your fellow students and upload homework assignments.


Check out this short introduction video that explains the core concepts of neural networks and how to use them in C#:

I found that participating on such a well-taught course was an awesome experience for me. I love the fact that we can all learn and help each other at a global scale. I think you are gifted teacher as well as f***ing amazing technically skilled. It was truly an enlightening experience

Yoav Kaplan, course student


  • 22 Video Lectures

  • 11 Quizzes

  • Source Code & Data sets

  • Lifelong Access

  • Certificate of Completion

  • 81 Text Lessons

  • 11 Homework Assignments

  • Private Support Group

  • 24-Hour Response Time


Check out this complimentary lecture in which I will show you how to build a Hotdog Detector in C# using a deep convolutional neural network.


Course prerequisites
Installing NET Core 3.0
Installing Visual Studio Code

Deep Learning
What is deep learning?

Linear Regression
Linear regression
Multiple regression
Regression metrics
Predict taxi fares in New York
My answers

Deep Neural Networks
Neural networks
Neural architecture
Visualizing hidden layers
Training deep neural networks
Predict house prices in California
My answers

Binary Classification Networks
Binary classification

Binary metrics

ROC, AUC, and Bias
Predict heart disease
My answers

Multiclass Classification Networks
Multiclass neural networks
Multiclass metrics
Recognise handwriting
My answers

How To Train Neural Networks
Partitioning data
Minibatch training
Sparse vector encoding
K-Fold Cross Validation
Detect spam messages
My answers

The convolution layer
The pooling layer
The dropout layer
Data augmentation
Detect hotdogs
My answers

Prebuilt CNNs
The VGG16 model
Feature extraction
Detect cats and dogs
My answers

The 1D-convolution layer
The word embedding layer
Rate movie reviews with a 1D-CNN
My answers

Recurrent Neural Networks
Recurrent neural networks
LSTM networks
Rate movie reviews with an LSTM
My answers

Artistic Style Transfer
Artistic style transfer
Transfer artistic style
My answers

Up-convolutional networks
Generative adversarial networks
Make AI-generated wildlife
My answers

In Conclusion
What you've learned


The Full Course


11 C# Applications

Full Walkthrough & Datasets

Private Support Group

81 Text Lessons

22 Video Lessons

11 Quizzes

Lifelong Access To 1 Course

All My AI Courses


40+ C# Applications

Full Walkthrough & Datasets

Private Support Group

300+ Text Lessons

100+ Video Lessons

30+ Quizzes

Lifelong Access To All Courses


Check out my other machine learning courses:

Machine Learning with C# and ML.NET

This course will introduce you to machine learning and AI and get you up to speed with Microsoft's new ML.NET library.

Deep Learning with C# and CNTK

This course will teach you how to build deep learning C# apps that use neural networks and Microsoft's CNTK library.

Cloud AI with Azure Machine Learning

This course will teach you how to leverage the power of the cloud to build Azure AI applications at cloud scale.

Machine Learning with F# and ML.NET

This course will teach you how to build machine learning apps with Microsoft's F# language and the new ML.NET library.

Machine Learning with Python and ML.NET

This course will teach you to to build machine learning apps in Python with NimbusML and the  ML.NET library.

“After hearing about neural networks for years without actually using them, I am proud to say I have successfully trained and used my first neural network – in C#. Thank you so much, Mark. Neural Networks are ridiculously awesome!

Joel Dokmegang, course student


1. Course FAQs

  • i. I’m a complete beginner in Machine Learning. Are the courses going to be right for me?

    Absolutely! The only thing you need to know is how to build simple console applications in C#. Everything else I will teach you step by step. In fact the sooner you enroll, the faster you will get the results that you want.

  • ii. How much time will it take to go through a course?

    Each course contains roughly 6 weeks of content. We encourage you to dedicate at least 2 hours per weekday for about six weeks to keep up with daily assignments.

  • iii. What if I can’t keep up with the group?

    You have lifetime access to all videos and files that come with the course, so you can learn at your own pace.

    And if you get stuck you can always just post a question in the support group and the students or I will help you out.

2. Support FAQs

  • i. Is there support as I go through the program?

    You will have daily supervision from me, your instructor. You also have access to a private support group where you can ask questions on a daily basis and get them answered, meet other students and collaborate with them. 

3. Program FAQs

  • i. How is this program different from other courses?

    This course is unique. There is no other course on the market that will teach you how to build machine learning apps in C#.

    You will be building machine learning apps from day one. You’ll ‘learn by doing’ and master key ML skills on the fly as you’re coding complex applications. This hands-on approach will have you learn new skills much faster than any other course that only uses text content or training videos.

4. Misc FAQs

  • i. What if I have a question that’s not on this FAQ list?

    I’m here to help and want you to be completely comfortable with your investment. Just drop me an email with any questions you may have, at

© Copyright 2020 by MDFT Europe. All Rights Reserved.