Introduction to
Deep Learning

8 April, 2024Virtual

3 days
Virtual
Data Science
Machine Learning

This three-day course covers the fundamentals of Deep Learning and explains how it differs from traditional Machine Learning. Developed by consultants with a proven track record of developing and deploying Deep Learning models at leading, data-driven enterprises, this training delivers the right mix of theory and hands-on practice.

You will gain the practical skills you need to implement your own Deep Learning algorithms and learn to apply them to unstructured data, such as images or text.

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Duration

3 days

Time

09:00 – 17:00

Language

English

Lunch

Excluded

Certification

No

Level

Professional

What will you learn?

After the training, you will be able to:

Build and train your own neural networks with Keras/TensorFlow.

Apply deep learning to a range of different types of data: images, text, and time series.

Intuitively understand the theory behind Deep Learning to make the right choices.

Key takeaways

Deep Learning Theory

  1. History: The rise of deep learning and its current-day applications. 
  2. How to choose the right (number of) layers and architecture for your problem: batch normalization, dropout, fully-connected layers, convolutional layers, LSTMs. 
  3. How to choose the correct hyperparameters for your problem: learning rate, optimizers, weight initialization, batch size. 

Deep Learning in Practice

  1. Build a neural network and train it from scratch.
  2. Data pre-processing & augmentation techniques. 
  3. Transfer learning from existing popular architectures. 
  4. Current Deep Learning models and techniques for images, text, and time series. 

Program

Who is it for?

This training is perfect for Data Scientists who want to upgrade their skills in Deep Learning. If you already have experience with Machine Learning and wish to transition from hand-crafted input features to data-driven features, this course is ideal for you. It’s especially suited for Data Scientists working with unstructured data like text, images, sound, and time series.  

Requirements

Basic knowledge of Python and Machine Learning concepts is beneficial. To make the most of this training, we recommend having at least one year of work experience with Pandas, Scikit-learn, and Matplotlib. 

Why should I follow this training?

Create Deep Learning algorithms from the experts. 

Leverage the power of deep learning to solve problems that would be impossible to solve with traditional ML techniques.

What else
should I know?

After registering for this training, you will receive a confirmation email with practical information. A week before the training, we will ask you about any dietary requirements and share literature if you need to prepare.

See you soon!

All literature and course materials are included in the price. 

All literature and course materials are included in the price. 

After registering for this course, you will receive a confirmation email with practical information. 

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