Artificial intelligence offers us an opportunity to make our daily routines more efficient and can enhance the experience for our customers. From understanding big data to smarter robots AI is a continuous process to improve our life and the way we work. Anticipate the needs of your customers, automise production processes or distribute resources efficiently. Power of AI helps you revolutionize your current way of working and interacting. We combine a theoretical framework with practical application and industry specific knowledge. We help you raise awareness of the AI state-of-the-art technology, map needs for implementation for your organization and create a step-by-step roadmap.
Building a common theory framework to streamline the actual state of possibilities for the team, what is possible and what is not in order to identify the business opportunities deriving from AI. In the practical workshop we focus on the fastest ways to implement AI and establish the roadmap.
We provide you with both theoretical framework and hands-on building experience and then facilitate the discussion to uncover possible applications and opportunities of AI in your industry and for your company.
We have a broad network of experts both in Finland and worldwide and hand pick them based on specific trends and needs. We will provide the best people for your specific case.
Our trainings are always adjust to fit specific company and be relevant for their industry.
Example course outline, by Jerome Leudet:
First Session (4h):
* General introduction to Deep Neural Networks
Getting familiar with deep neural networks, background maths and glossary. Presentation of different tasks or applications (vision, NLP, translation, Deep RL). Presentation of the different architectures (CNNs, RNNs, LSTMs). Supervised vs Unsupervised techniques. Presentation of the different building blocks (feed forward, convolution, regularisation). Different frameworks and architectures. Debugging and visualisation of Neural networks.
Workshop: implement an image classifier for MNIST, proposed framework: Pytorch
Second Session (4h):
* Vision and Classification Tasks
Different classification tasks. Classification: Resnet, inception, Squeeze nets, SEnets. Detection: (Faster)RCNN, Yolo. Segmentation: RefineNet, PSPnet, DeepLab. Tracking: openCV, heatmaps, attention networks
* Unsupervised learning and generative models
Autoencoders, learning from unlabeled data. Variational Autoencoders, constraining latent space, and latent space arithmetics. Generative Adversarial networks. Style transfer. Super sampling.
Workshop: Implement an Autoencoder for classification of mostly unlabeled data, proposed framework: Pytorch.
Price: €12000/8h, flexible.