Introduction to Neural Network

2026/2027

Учебный год

ENG

Обучение ведется на английском языке

6

Кредиты

Кто читает:

Кафедра прикладной математики и информатики (Нижний Новгород) (Факультет информатики, математики и компьютерных наук (Нижний Новгород))

Статус:

Курс по выбору

Когда читается:

4-й курс, 2, 3 модуль

Преподаватель

Демидовский Александр Владимирович

Course Syllabus

Abstract

The course covers fundamental and practical aspects of working with modern neural networks and Large Language Models (LLMs). Students will explore the entire lifecycle of language models: from neural networks inference and quality evaluation using standard benchmarks to attention mechanism analysis and parameter-efficient fine-tuning for downstream tasks.

Learning Objectives

• Be able to prepare a dataset for evaluating the quality of a language model
• Be able to perform language model inference
• Be able to evaluate the quality of a language model
• Be able to analyze the model architecture
• Be able to fine-tune the language model
• Know how to optimize a language model for its inference

Expected Learning Outcomes

• Be able to prepare the dataset in the form required for subsequent model quality assessment
• Is able to implement the model inference
• Is able to perform quality assessment of a large language model
• Is able to fine-tune a large language model
• Is able to perform optimization of a large language model
• Is able to analyze Transformer model architecture

Course Contents

• Modern tasks in NLP
• Datasets in the HuggingFace ecosystem
• Inference of large language models
• Evaluation of the quality of language models
• Architecture of Transformer models
• Fine-tuning language models with LoRA
• Optimization of language model inference

Assessment Elements

• Laboratory work №7
• Контроль знаний на семинарах
• Laboratory work №8
• Laboratory work №9
• Exam

Interim Assessment

• 2026/2027 3rd module
  0.18 * Laboratory work №7 + 0.4 * Exam + 0.12 * Laboratory work №9 + 0.18 * Laboratory work №8 + 0.06 * Контроль знаний на семинарах

Bibliography

Recommended Core Bibliography

• Introduction to deep learning, Charniak, E., 2018

Recommended Additional Bibliography

• Ian Goodfellow and Yoshua Bengio and Aaron Courville. Deep Learning, 2016. URL: http://www.deeplearningbook.org
• Нейронные сети. Полный курс : пер. с англ., Хайкин, С., 2018

Authors

• MALAFEEV Aleksei Iurevich
• Klimova Margarita Andreevna
• DEMIDOVSKIY ALEKSANDR VLADIMIROVICH