Ideal for teams that…
Hands-on AI and data analytics workshops — built around your team's real cases.
How to design and implement advanced CNN architectures
Techniques for optimization and fine-tuning of convolutional models
Practical use of transfer learning in computer vision tasks
How to deploy and optimize CNN models in real-world projects
What we actually do
- · Basics of neural network architecture
- · CNN architecture overview
- · Comparison of CNNs vs. traditional neural networks
- · Implementing convolutional layers in PyTorch
- · Designing and optimizing pooling layers
- · Creating a CNN model from scratch
- · Analyzing the impact of different architectures on performance
- · Using pretrained models
- · Fine-tuning models on custom datasets
- · Implementing ResNet and Inception
- · Comparative performance analysis of different architectures
- · Regularization techniques: dropout, batch normalization
- · Hyperparameter optimization strategies
- · Implementing an image classification model
- · Building an object detection system
- · Performance optimization
- · Integrating CNNs into real-time applications
From brief to retro in 30 days.
Brief & diagnosis
A call with the team lead + a short survey for participants. We define goals, gap and context.
Program customization
We adapt modules, case studies and code examples to your stack. Approval in 5 days.
Workshop
Trainer-led sessions, hands-on, code review. Mentor available between sessions too.
Retro + report
Outcome report for the team and lead. 30 days of consulting included.
Send a brief. We'll reply within 1 day.
After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.
Thank you!
We'll get back to you within 1 business day.
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