Constructor workshop: How to use artificial intelligence and machine learning in research

2 days, 15 full hours of mastering AI and ML in research

Made for:

Physicists

Material science researchers

Educators, PhD or postdoctoral students and assistants

Scientists looking to utilize classical and modern machine learning in their research

Where you will:

Discuss with other researchers on use cases

Learn how to efficiently set up & manage data science projects

Learn to transform & prepare data for analysis in Python

Learn ways to train ML models

Join the workshop

All participants will get certified.

Topics you can expect to be covered at the workshop:

Introduction into Machine Learning (ML)

Mastering Python for Machine Learning

Supervised Machine Learning Techniques

Unsupervised Machine Learning Techniques

Graph Neural Networks

NN basics: back-propagation algorithm, activation and loss functions, simple fully-connected NN

NN architectures (CNN, ResNet, UNet, GraphNN): Normalization, Attention, SkipConnection, DropOut

Introduction to PyTorch

Intro into Diffusion Networks

Practical use cases

Course agenda

Day 1 covers the theory behind AI and ML, while Day 2 focuses on hands-on practice with real-world applications. Check out the agenda:

Day 1

Welcoming	Classical machine learning	Modern machine learning
08:30–09:00 Registration	11:00–11:30 Supervised Machine Learning Techniques - Adriano Persegani	13:30–14:30 NN architectures (CNN, ResNet, UNet, GraphNN, etc.). Normalization, Attention, SkipConnection, DropOut - Ildus Sadrtdinov
09:00–09:30 Opening words - Elena Novoselova	11:30–12:30 NN basics: back-propagation algorithm, activation and loss functions, simple fully-connected NN - Kseniia Alekseitseva	14:30–14:45 Break
09:30–10:00 Introduction into Machine Learning (ML) - Kseniia Alekseitseva	12:30–13:30 Lunch	14:45–15:30 Introduction to PyTorch - Ildus Sadrtdinov
10:00–10:45 Mastering Python for Machine Learning - Adriano Persegani		15:30–16:15 Introduction into Diffusion Networks - Ivan Shchekotov
10:45–11:00 Break		16:15–16:30 Break
		16:30–17:15 Graph neural networks - Dr Maxim Borisyak
		17:15–18:00 Unsupervised Machine Learning Techniques - Adriano Persegani

Day 2

Machine learning for physicists
09:00–09:45 Introduction to Constructor - Alex Anikin
09:45–10:15 Use case 1: ML live coding - Adriano Persegani
10:15–10:30 Break
10:30–11:00 Use case 2: Approaching Optimal pH Enzyme Prediciton with Large Language Models - Petr Popov
11:00–11:30 Use case 3: Sparse representation for machine learning the properties of defects in 2D materials - Andrey Ustyuzhanin
11:30–12:30 Round table and Q&A

Join the workshop

Available workshop formats

We come to your location

These workshops are designed for our trainer to visit and deliver them at your location.

Visit our location

Join us at our selected locations. The first workshop will be held at Constructor University Bremen in November.

Once you select your date of availability, a Constructor representative will reach out to discuss the best workshop options for you.

Constructor workshop: How to use artificial intelligence and machine learning in research

2 days, 15 full hours of mastering AI and ML in research

Made for:

Where you will:

Topics you can expect to be covered at the workshop:

Speakers

Course agenda

Day 1

Welcoming

Classical machine learning

Modern machine learning

Day 2

Machine learning for physicists

Available workshop formats