AI & Data

Training: Advanced Image Analysis with CNNs

The Advanced Image Analysis with CNNs training is an intensive workshop designed to introduce participants to the latest deep learning techniques for image analysis.

Duration
6h
Ask about the program → See all
Who it's for

Ideal for teams that…

1 Individuals who want to expand their skills in image analysis using CNNs and already have basic knowledge of machine learning and Python
2 Professionals looking to explore advanced techniques for building and optimizing CNN architectures
3 Participants aiming to work on real-world projects in Computer Vision and Deep Learning
4 AI enthusiasts interested in exploring the latest trends and tools used in industry and scientific research
Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

✓

How to design and train advanced CNNs using TensorFlow and Keras

✓

Techniques to prevent overfitting and methods to improve model performance in image tasks

✓

How to interpret CNNs using visualization and analysis of filters and activation maps

✓

The ability to independently execute complex image analysis projects using cutting-edge AI architectures and tools

Program · 6 modules

What we actually do

M01
Module 1: Basics of Convolutional Neural Networks
  • · Operation of convolutional, pooling, and fully connected layers
  • · Representation of digital images as input tensors; processing RGB and grayscale images
  • · Tools and libraries for efficient image dataset management
M02
Module 2: Building and Training a Basic CNN Model
  • · Practical exercises implementing simple CNN architectures in TensorFlow/Keras
  • · Strategies for preventing overfitting: dropout, batch normalization, L2 regularization
  • · Data preprocessing, image augmentation, and basic model optimization techniques
M03
Module 3: Advanced Architectures and Regularization
  • · Analysis of more complex CNN architectures (e.g., ResNet, Inception) and their applications
  • · Advanced regularization strategies and augmentation methods
M04
Module 4: Improving Model Quality and Interpretability
  • · Automated hyperparameter optimization with KerasTuner and Optuna
  • · Optimization methods: learning rate tuning, transfer learning strategies, early stopping
  • · Tools and techniques for CNN interpretability, including visualization of filters and activation maps
M05
Module 5: Applying CNNs to Real-World Problems
  • · Image segmentation and object detection in medical, industrial, and other domains
  • · Introduction to combining CNNs with other techniques (RNNs, GANs) for advanced image analysis tasks
M06
Module 6: Project Workshop and Summary
  • · Team-based work on selected image analysis problems
  • · Presentation of results, discussion of best practices, and exploration of trends in computer vision
Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.
How we work

From brief to retro in 30 days.

01

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

02

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

03

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

04

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

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.

✓Quote within 48h of the brief
✓First session within 30 days
✓Pilot before the full decision
✓VAT invoice, payment in instalments possible

Ochrona antyspamowa (Cloudflare Turnstile) zostanie aktywowana po wpięciu klucza.

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