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AI

Machine learning with TensorFlow

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

Duration
24h · 3 days
Ask about the program → See all
Who it's for

Ideal for teams that…

1 Developers and data analysts who want to independently implement ML models
2 Professionals with basic Python knowledge interested in applying TensorFlow in practice
3 IT specialists implementing modern data analytics and process automation
4 Students and enthusiasts looking to start a career in machine learning
Outcomes after the program

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

✓

Build, train, and evaluate machine learning models in TensorFlow

✓

Prepare and augment data, and effectively visualize model training processes

✓

Apply transfer learning techniques and advanced model architectures (CNN, RNN)

✓

Gain practical skills in optimizing and deploying models across various use cases

✓

Learn data preparation, analysis, and visualization techniques for ML projects

✓

Build a solid foundation for further learning and advanced AI projects

Program · 6 modules

What we actually do

Day 1: Introduction to Machine Learning and TensorFlow

M01
Module 1: ML Basics with TensorFlow
  • · Introduction to the TensorFlow ecosystem: installation, architecture, core functions
  • · Overview of machine learning and deep learning types (supervised, unsupervised, deep learning)
  • · Constructing artificial neural networks and introduction to optimization mechanics
M02
Module 2: Data Preparation and Analysis
  • · Data processing, cleaning, and exploration with TensorFlow and Pandas
  • · Data visualization techniques and preparing datasets for training
  • · Data augmentation techniques and managing training datasets for ML models

Day 2: Model Building, Training, and Evaluation

M03
Module 3: Building Machine Learning Models
  • · Building regression and classification models in TensorFlow/Keras
  • · Implementing neural layers, model optimization, and hyperparameter tuning
  • · Optimization techniques: hyperparameter tuning, dropout, batch normalization, early stopping
M04
Module 4: Validation and Result Interpretation
  • · Model evaluation techniques: test set splits, performance metrics with TensorBoard
  • · Visualizing training history and interpreting model behavior
  • · Debugging training processes and analyzing model outcomes

Day 3: Practical Projects and Applications

M05
Module 5: Project Work and Case Studies
  • · Solving real-world problems with TensorFlow (e.g., image analysis, text classification)
  • · Using pre-trained models to quickly build effective solutions
  • · Application examples: image analysis, natural language processing, time-series forecasting
  • · Team-based workshop: from data preparation to model deployment
M06
Module 6: Latest Trends and Competence Development
  • · Automated model training, transfer learning, integration with other frameworks
  • · Discussion of AI trends and career development opportunities in machine learning
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.

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