AI & Data

Training: Introduction to Deep Learning with PyTorch

The Introduction to Deep Learning with PyTorch course is an intensive 2–3 day program designed for participants who want to learn the practical foundations of deep learning using the popular PyTorch framework.

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

Ideal for teams that…

1 Beginner programmers and data scientists who want to learn deep learning
2 Individuals planning to build AI solutions using PyTorch
3 Data analysts and engineers looking to expand their ML competencies
4 IT specialists and researchers interested in training neural network models
Outcomes after the program

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

✓

How to build and train deep neural network models in PyTorch

✓

How to manage and effectively prepare data for training

✓

How to optimize and monitor the model training process

✓

How to apply transfer learning techniques and adapt models to new tasks

✓

How to prepare models for deployment and integration into real-world systems

✓

How to independently design and train deep learning models with PyTorch

Program · 6 modules

What we actually do

M01
Module 1: Introduction to PyTorch and Working with Tensors
  • · What is PyTorch and why is it so popular?
  • · PyTorch vs TensorFlow – quick comparison
  • · Key advantages of PyTorch
  • · Creating, operating, and manipulating tensors
  • · Using GPUs and optimizing hardware performance
  • · Simple data pipelines for training
M02
Module 2: Building and Training Simple Neural Networks
  • · Neural network architecture and key deep learning concepts
  • · Defining models in PyTorch – layers and activation functions
  • · Implementing training loops and optimization
  • · Parameter initialization and the concept of backpropagation
  • · Building your first network (layers, activations, forward pass)
  • · Hands-on: creating and training a classifier
M03
Module 3: Data Management and Dataset Preparation
  • · Creating and loading datasets (Dataset, DataLoader)
  • · Data augmentation techniques and train/test splitting
  • · Data visualization and analysis
  • · Workshop: preparing a custom dataset for training
M04
Module 4: Model Optimization and Monitoring
  • · Choosing loss functions and optimizers
  • · Regularization, early stopping, and preventing overfitting
  • · Debugging models and diagnosing common pitfalls
  • · Introduction to TensorBoard and other visualization tools
  • · Saving and loading models
  • · Monitoring metrics and training results
  • · Preventing overfitting: dropout, early stopping, L2 regularization
  • · Model evaluation: validation sets, accuracy/F1-score metrics
M05
Module 5: Transfer Learning and Fine-Tuning
  • · Using pretrained models in PyTorch for new tasks
  • · Model adaptation and training of final layers
  • · Example applications: image classification, NLP tasks
  • · Different loss functions (MSE, CrossEntropy) and optimizers (SGD, Adam)
  • · Hyperparameter tuning: learning rate, epochs, batch size
  • · Hands-on: adapting a pretrained model to a custom problem
M06
Module 6: Deployment and Model Scaling
  • · Preparing a model for production
  • · Basics of model integration with Python applications
  • · Introduction to optimization and inference acceleration tools
  • · Project workshop: building a mini AI application based on your own model
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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