Goals:
The primary goal of this 12-hour course is to introduce attendees to the fundamentals and applications of deep learning, with an emphasis on Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Transformers. Participants will be engaged with a mix of theory and hands-on examples that illustrate the power and scope of these tools in various domains such as image recognition, time series analysis, text processing, and generative deep learning. The course aims to accommodate a wide audience range, ensuring attendees finish with a broad understanding and practical experience of these technologies, leaving them equipped and inspired to apply deep learning in their respective fields.

On completion of this course, participants are expected to have developed the following skills:

1. Understanding the fundamentals of Deep Learning (DL), with a particular focus on Convolutional Neural Networks (CNNs), Recurrent networks (LSTM) and Transformers.
2. Apply DL techniques to real-world problems, including image recognition, time series analysis, text processing and more.
3. Navigating and using pre-trained models effectively to achieve efficient and accurate results.
4. Build and refine their own DL models based on the requirements of the specific tasks they are tackling.
5. Interpret the results of complex DL models and use this information to make informed decisions.
6. Understand the possibilities and limitations of generative deep learning models, both in the field of language and in the generation of other content (images, voice, music, etc).

Contents:

Session 01 - Introduction and Vision with CNNs (3 hours)

Introduction to Deep Learning

Convolutional Neural Networks (CNNs)

- Practical example: FashionMNIST

- Practical Example: Pre-trained Model

Session 02 - Time Series with LSTM (3 hours)

Introduction to LSTM Networks

- Practical Example: S&P 500 Index Price Prediction

- Other examples of LSTM applications

Session 03 - Deep Learning for Text with Transformers (3 hours)

Transformers applied to text:

- Practical examples: OpenAI Playground, PerplexityAI, Pi

- Exploration of transformers libraries (Hugging Face) and KerasNLP

Session 04 - Other Examples of Generative DL (3 hours)

Generative DL applied to image generation:

- Practical examples: Dalle 3, Stable Diffusion XL

- Exploration of diffusers libraries (Hugging Face) and KerasCV


Minimum number of participants: 12


Trainer
Luís Cunha 


Duration
12 hours


Modality
Online, via Zoom


Dates
May 24th and 31st; June 7th and 14th
10 a.m. to 1 p.m.

How to register
You can register via the following link: https://forms.gle/GNFiia1HreMK4hKe8

Price: 170.00€