AI and Deep Learning for developers
This is a 5 day training (usually split 2-3) with no required preparation.
After completing this academy, you will have a solid understanding of:
- What Artificial Intelligence is
- How it works
- What it is (not) good at
- How to apply.
You will have experience from the exercises and templates to get your business project up and running the way it should.
This academy offers an informative and practical introduction in artificial intelligence and deep learning and consists out of 4 components. We will not only see demos, but also build the models and make exercises to understand how everything works so that you can start working with it yourself.
While using simple definitions, we explore what artificial intelligence, machine learning and deep learning are exactly, what they can do and what they can’t do, and why it works. We look at examples of the different applications of computer vision, natural la,guage processing (NLP) and a few specific cases such as recommendation engines, generative adversarial networks and reinforcement learning. Finally, we dispel some myths concerning AI.
Neural networks form the heart of the present successes in AI and deep learning. We learn to understand what they are exactly and how they work without shunnning details, and we discuss the different ways in which a network can learn. Next, we look at how they are used in computer vision and NLP, how the specific networks work, where their strengths lie, what they learn exactly and how they evolved to overcome practical problems over the years. We compare different networks and their implementation in different frameworks, introduce transfer learning as fundamental building blocks and learn how we can build a network of world class.
The cutting (and bleeding) edge of AI and deep learning is moving fast. New techniques, possibilities and more performant networks are becoming available. We discover what’s coming and how painful it can be to apply AI to these cases. We also discuss the trends when it comes to “ethics and AI” and new datasets.
In research and publications, the emphasis often lies on training better networks with new techniques - the ones we discussed and tested during the “explain” component of the academy. In the last part of the academy, we look at the bigger picture and we go through all phases of an AI project. We discuss the following, among others:
Collecting and preparing the right data and making them available;
The “build versus buy” decision, where we look at the offer of the main cloud vendors;
Producing your trained model, both in the cloud and on mobile.
On the last day of the training, participants can work on their own use case using the concepts that they learned, so they can make a first plan to effectively start using AI.
The target audience is developers who want to get hands on experience with AI and learn how they can implement it to solve their (business) challenges.
This academy has no prerequisites.
You should bring your laptop to run the experiments/exercises, no special hardware required.
November 5-6, 2019 @ The Campus
2020 @ PXL (date to be defined)
Host your own?
Would you like to host this academy for your audience, or internally at your company?
We are looking forward to hear from you: firstname.lastname@example.org