Andrey Kulinich

Developer, implementer, teacher, founder of a company in the field of generative artificial intelligence.

In 1997, he received a diploma in systems engineering specializing in intelligent systems.
Since 2017, I have been teaching at Innopolis University, heading the CD TO program.

I know how businesses can earn and strengthen their competitiveness through generative AI.

For 20 years I have been creating and managing business training programs for Russian Railways, MTS, Megafon, Beeline, Rostelecom, X5 Retail Group, Magnit, Gazpromneft, Rosgostrach, Severstal, MMK, Otisipharm, EPAM, Baxi, ROAD, Hms, BCS, Productivity Leaders, MIRBIS, HSE, CBO, Moscow Government University, Yandex, Aliexpress.

Andrey Kulinich is a developer of solutions based on generative AI

For 20 years he has been creating and managing business training programs for X5 Retail Group, Russian Railways, Gazprom-Neft, MTS, Rosatom, Inter RAO, Severstal

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kulinich

He has been consulting experts for 20 years

200 clients

3 performances per month

30 years of experience in the field of AI

12 multimedia courses and computer business simulations

23 years of teaching

Projects

Trainings and performances

Consulting on business transformation AI

We are launching the process of digital transformation of the company. Get a free 60-minute consultation.

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Kulinich.AI – development of smart assistants

We develop effective AI-based solutions. Get acquainted with the cases and demo examples on the website.

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The school of prompting – training in working with AI

We train you to use neural networks as fully and effectively as possible in your work and life. Choose a training program.

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Popular Videos

How to create and train a chatbot on DialogFlow. The basics.

Basics of working with Jupyter notebooks

Clustering in Python (KMeans and hierarchical)

Random Forest - very simple on how to use classification in Python

Introduction to Large Language Models (LLM)

01 Uploading data to Jupiter notepad and validation

06 SARIMA model (auto_sarima)

002 Clustering using Python 3