To wersja testowa nowego serwisu infoShare Academy — wyświetlane treści i oferta nie są wiążące ani kompletne

AI

Optimizing Machine Learning and AI models

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

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

Ideal for teams that…

1 Data scientists and machine learning engineers with project experience in ML
2 Specialists responsible for deploying models in resource-constrained environments
3 Professionals working with large language models and computer vision who want to optimize performance
4 ML engineers interested in advanced training and inference methods to reduce time and costs
Outcomes after the program

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

✓

Apply advanced optimization techniques for machine learning and deep neural network models

✓

Accelerate training and inference processes while maintaining model quality

✓

Compress models and adapt them for edge device deployment

✓

Work with tools (ONNX, TensorRT, Triton) and distributed frameworks for handling large models

✓

Design scalable and efficient AI solutions ready for production

Program · 7 modules

What we actually do

Day 1: Optimization Basics and Advanced Work Environments

M01
Module 1: Introduction to ML & AI Model Optimization
  • · Needs and objectives of optimization across modeling stages
  • · Overview of techniques: quantization, pruning, mixed-precision training
  • · Data pipeline optimization – improving loading and augmentation
  • · Agile model lifecycle management for optimization (benchmarking, evaluation)
M02
Module 2: Data Pipelines and Flow Management
  • · Automating loading, preprocessing, and augmentation for efficiency
  • · Practical: testing and tuning augmentation pipelines
  • · Validating data quality and efficiency in model training
M03
Module 3: Technologies and Tools for Optimization
  • · ONNX – model exchange and acceleration standard
  • · Inference acceleration frameworks: TensorRT, Triton
  • · Integration with popular libraries (PyTorch, TensorFlow)
  • · Hands-on workshop: preparing a model for optimization

Day 2: Optimization Techniques and Practical Deployment

M04
Module 4: Training Process Optimization
  • · Mixed-precision training – reducing resource requirements
  • · Gradient accumulation and distributed training
  • · Hyperparameter selection and tuning for optimization
M05
Module 5: Model Compression and Post-Training Adaptation
  • · Quantization and pruning methods and applications
  • · Performance- and memory-optimized model formats
  • · Deployment of optimized models on edge devices
  • · Case study: optimizing large language models and computer vision models

Day 3: Production Optimization and Scaling

M06
Module 6: Applying Optimization in Production Environments
  • · Specifics of optimizing LLMs and CV models
  • · Deploying optimized models in cloud and on-premise environments
  • · Performance monitoring, diagnostics, and inference troubleshooting
  • · Practical cost and efficiency analysis: case studies
  • · Scaling and managing AI models at large scale
M07
Module 7: Best Practices and Trends in AI Optimization
  • · Resource usage monitoring and automated scaling
  • · Diagnostics and troubleshooting after deployment
  • · Tools for automated benchmarking and post-update testing
  • · Trends in large model optimization and adaptive algorithms
  • · Discussion and participant knowledge exchange
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

How we handle your data

We process your business data (name, work e-mail, phone number, company, job title) in order to handle your corporate training inquiry and prepare an offer. The data controller is infoShare Academy Sp. z o.o., Al. Grunwaldzka 472B, 80-309 Gdańsk. Providing the data is voluntary but necessary to receive a response. You have the right to access, rectify, erase or restrict the processing of your data and to object to it. Full information is available in our data processing notice.

Optional marketing consents

The controller of your personal data is infoShare Academy sp. z o.o. The rules for processing personal data are set out in the Privacy Policy and the Data Processing Notice.

Other programs for teams

See all →
AI

Advanced image analysis methods using CNN

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

24h · 3 days →
AI

AI - general training

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

AI →
AI

AI Agents in Practice: Building, Integrating, and Scaling

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

8h · 1 day →