Technologies / Artificial Intelligence

Understanding deep neural networks - from theory to practice

The training provides an in-depth understanding of the theoretical foundations and practical aspects of implementing deep neural networks. Through a systematic workshop, participants learn not only the technical aspects but also the mathematical foundations behind deep learning. The program is designed to combine theory with intensive practical exercises, taking participants from basic concepts to advanced implementation techniques. The class uses a variety of teaching methods, including interactive workshops, case analysis and hands-on implementations, to ensure a full understanding of the topics presented.

Issues

Mathematical foundations of deep learning
Advanced network architectures
Optimization theory in deep learning
Regularization and standardization techniques
Transfer learning and representations
Oppositional learning
Generative architectures
Debugging neural networks
Strategies for training models
Optimize resources and performance
Implementation of production models
Analysis and interpretation of network behavior

Benefits

Upon completion of the training, the participant will have a deep understanding of the theoretical underpinnings of neural networks, which will enable him/her to make informed design decisions
The ability to analyze and interpret the behavior of neural networks at a mathematical level
He will be able to implement and optimize complex network architectures with a full understanding of the processes involved
Will master advanced regularization and optimization techniques to create efficient and stable models
Will learn to effectively debug and troubleshoot deep neural networks
Will gain practical experience in designing network architectures tailored to specific requirements
Will learn methods to effectively train and tune models using advanced optimization techniques
Will be able to implement deep learning models with performance and resource considerations

Who is this training for?

Machine learning engineers seeking to deepen theoretical knowledge

Researchers involved in artificial intelligence research

Deep learning systems developers

AI solution architects looking for a solid theoretical foundation

Data scientists specializing in deep learning

Academic researchers in the field of machine learning

Neural network optimization specialists

R&D engineers in AI departments

Prerequisites

Sound knowledge of higher mathematics
Experience in the implementation of neural networks
Knowledge of the basics of machine learning
Understand the concept of numerical programming

Training program

Differential calculus and optimization

Fundamentals of probability in deep learning

Feed-forward networks and their characteristics
Convolutional architectures and their applications
Recursive networks and sequence processing
Attention architectures and transformers
Optimization and regularization techniques
Gradient algorithms and their variants
Methods of regularization and prevention of overfitting
Normalization and initialization of parameters
Learning strategies and selection of hyperparameters

Learning representations and transfer learning

Generative architectures
Reinforcement learning in deep learning

Designing architecture for specific applications
Optimize performance and resources
Techniques for debugging neural networks
Implementation strategies in production

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Frequently asked questions

Who is the Understanding deep neural networks - from theory to practice training for?

This training is designed for professionals looking to develop skills in understanding deep neural networks - from theory to practice. Required level: advanced.

How long is the Understanding deep neural networks - from theory to practice training?

The training lasts 5. Available in online or on-site format.

Will I receive a certificate?

Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.

Can this training be conducted for a closed group?

Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.