Speakers

ML and DL basics, supervised, reinforcement and unsupervised learning. Key concepts of Machine Learning (ML) and Deep Learning (DL); Model training approaches: supervised learning, unsupervised learning, reinforcement learning; Examples of ML and DL applications.

Generative models basics. In this speech, we will explore the fundamentals of generative models, delving into their core concepts and how they create new data, such as images, text, and audio. We’ll highlight their connection to cutting-edge technologies like AI and deep learning, showcasing practical applications across various fields. Expect insights into the mechanics, benefits, and transformative potential of generative models in shaping innovation.

Google Cloud Platform Review. Tools and practices for working with Big Data.

"Neural networks. Transformers. Building models with Keras and PyTorch"
We are going to cover the main concepts in Deep Learning and Neural Networks and their differences compared to classic ML / Data Science. Understand what task can be solved using TensorFlow and PyTorch.

"MS Azure and Big Data in Azure."
This presentation dives into Microsoft Azure's comprehensive AI platform, empowering developers to build intelligent applications at scale. We'll explore how Azure AI simplifies your AI toolchain, fostering the creation, evaluation and deployment of cutting-edge solutions.

"Database basics, relational, non-relational, distributed databases, data warehouse, ETL, data workflows."
We'll run through the overview of the DB basics, ways to operate with, and main use cases. In a nutshell we will cover how relational databases organize structured data, how NoSQL databases handle unstructured data, and the benefits of distributed databases for scalability and fault tolerance. Going forward to data warehousing, extraction and transfer processes.

Project and data management (Git, Data Version Control (DVC), Data sources (Kaggle, etc.), ML Hubs (Hugging Face, etc.)). How to manage effective tools and approaches to project and data management? I will explain the basics of working with Git for code version control, using Data Version Control (DVC) to track changes in data and models, as well as an overview of popular data sources such as Kaggle, and platforms for sharing models and tools, such as Hugging Face. The material will help you understand how to organize work with projects and data, ensuring reproducibility and efficiency.

Database usage for Data Science, Data Analysis and Machine Learning. The presentation explores the role of databases in Data Science, Data Analysis, and Machine Learning workflows. Key topics include selecting appropriate database types (SQL, NoSQL, and graph databases) for different data scenarios, optimizing data retrieval and preprocessing for analysis, and integrating databases with machine learning pipelines. Real-world examples demonstrate how effective database management enhances data-driven insights and supports scalable machine learning applications.

NLP, NLP tasks, NLP libraries and frameworks (e.g. NLTK). Supervised Machine Learning Unsupervised Machine Learning Reinforcement Machine Learning Markiyan Fostiak Software Engineering Lead Cloud computing basics, SaaS, PaaS and IaaS. The presentation provides an introduction to cloud computing, focusing on its fundamental concepts and service models: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). It highlights the key differences between these models, their use cases, and benefits for businesses and developers. Practical examples illustrate how cloud computing enhances scalability, flexibility, and cost-efficiency in modern IT environments.

This presentation delves into Amazon Web Services (AWS) and its capabilities for managing and analyzing big data. Key topics include AWS services such as S3, Redshift, EMR, and Glue, which facilitate data storage, processing, and analysis at scale. Practical use cases demonstrate how AWS empowers businesses to extract insights from large datasets, optimize workflows, and enable machine learning applications in a cost-effective and scalable manner.

LLM, Transformers, BERT, GPT models family, LLM fine-tuning techniques. The presentation explores Large Language Models (LLMs) and their underlying Transformer architecture, focusing on prominent models like BERT and the GPT family. It covers the evolution of these models, their capabilities in natural language processing tasks, and the core concepts behind their success. Additionally, fine-tuning techniques, including transfer learning, prompt engineering, and parameter-efficient tuning, are discussed to demonstrate how LLMs can be adapted for specific applications, enhancing performance and efficiency.

Why are soft skills critical for techies?
Agenda:
- Why are soft skills power skills?
- How to increase personal effectiveness?
- How to make decisions effectively?
- How to delegate?
- What are the false friends of productivity?
- How to recognize the non-obvious signs of a great team?
- And much (or little) more!

This lecture covers modern DevSecOps implementation, beginning with the "shift left security" concept. We'll examine technical components including dependency scanning, automated security testing (SAST, DAST, IAST), secrets management, and Infrastructure as Code security. The practical segment focuses on organizational implementation: security champions programs, CI/CD pipeline security gates, and incident response protocols. We'll address GDPR and PSD2 compliance requirements, concluding with a live demonstration of key concepts. Learning outcome: Participants will gain practical knowledge and skills for implementing secure software development practices

Introduction to modern cryptography - where academia meets applied solutions. While implementing and working with modern cybersecurity solutions, one cannot omit one of the most powerful tools in terms of data protection - cryptography. This talk is dedicated to introducing and demonstrating modern cryptography as a broad spectrum of security tools commonly used to keep our data safe in the digital world. The lecture aims to summarize the knowledge and introduce the audience to the world of not only well-known cryptographic primitives but also less common ones such as Blind Signatures and Oblivious Pseudorandom Functions from a scientific perspective, along with examples of their use in real-world solutions.

“Data Analysis and Reporting Life Cycle”
This lecture draws from my personal experience and insights gained while working at Miratech. Having mentored trainees, I understand the key skills (some students are missing) needed to kick-start a career in analytics. During the session, we will cover:
• Data analysis and Reporting Life Cycle
• Practical tips for data preparation
• Best practices for data visualization
• The importance of simplicity in analytics
• Real-life examples
Additionally, we’ll explore other topics such as forecasting, segmentation, naming, colours, and "calculation of parrots."

Ever wondered how your favourite apps stay functional 24/7, even while you’re catching up on sleep?

In this lecture, we’ll delve into the world of background workers, focusing on .NET implementations and exploring their role in powering real-world applications. For instance, systems like LeoCard, the unified electronic ticketing system for public transport in Lviv, likely rely on background services to process transactions or queues, manage user data, and ensure seamless operations for thousands of daily commuters.
Key takeaways from this session:
• Understanding Background Workers: Grasp the fundamentals of background workers and their significance in application architecture.
• Real-World Applications: Explore practical use cases, including emails sending or financial transaction management.
• Designing Resilient Systems: Learn tips for creating scalable and efficient background tasks.
• Cross-Language Perspectives: While focusing on .NET examples, we’ll also examine how similar tasks are handled in other languages, such as Python, using tools like Celery.

LLM fine-tuning techniques (RAG і GenAI agents)
Introduction
Overview of Fine-Tuning Techniques
Understanding RAG
GenAI Agents
Demo Setup: Building an Agent from Scratch
Q&A

Dive into the world of unsupervised learning on hierarchical clustering algorithms. It will cover key techniques such as agglomerative and divisive clustering and demonstrate their application through examples. The session will start with a theoretical overview of the methods, followed by practical demonstrations of their application in various scenarios. This lecture is an invaluable opportunity for students to deepen their understanding and refresh knowledge of clustering algorithms and enhance their analytical skills.

OAuth and OpenID Connect are two extremely important protocols for anyone who works with security. This lecture provides the basics of using these protocols, as well as some general-purpose terms and principles of security.

Machine learning, deep learning, neural networks

This session is perfect for students eager to think outside the box, embrace imaginative problem-solving, and find innovative solutions in everyday challenges. Expand your perspective and learn how creativity can be your most valuable skill!During the session you will learn:
- Examples of creative approaches which costed nothing but brought fortunes
- Theory of Minimal Impact
- See no problems, but possibilities
- How GenAI can help us being creative

Version Control Systems: Git, Data Version Control (DVC), etc.
During the workshop, participants will learn what git history is and why it is important to keep it clean and organized. What is the difference between merge and rebase. What is interactive rebase and what is its power not only in words but also in practice.

Usage of AI in modern services, applications, platforms
Diring the talk we will discover how AI drives real-world innovation across today’s digital landscape, from personalized apps to chatbots improving customer service. In this talk, we’ll break down the core AI techniques behind these successes, examine use cases that optimize workflows, and explore the ethical considerations of responsible AI deployment. Attendees will gain practical insights into leveraging AI tools and frameworks to enhance their future projects and careers.

Impostor syndrome is a psychological phenomenon that most of us suffer from to some extent. I'm no exception, and I've been dealing with it for most of my IT career, which is about 10 years now. It took me a while to realize that imposter syndrome was one of the biggest blockers to my personal and career development, but when I did, I gradually, in small and big steps, fought it in all available ways. In my talk, I will share my story and how it helped me grow from an ordinary developer to a team leader and later to the entire department.

Probability in Real Life
In the lecture, we will study interesting examples of the use of probability theory. We will get acquainted with the basic concepts and terms that are later used in data analysis and with which mathematical modeling of the phenomena surrounding us is carried out.

Statistics in Real Life
We will consider the basics of mathematical statistics and numerical data analysis. In particular, we will get acquainted with descriptive statistics, estimation of sample parameters and testing of statistical hypotheses. We will talk about parametric and nonparametric criteria for testing hypotheses.

Data visualization
We will explore the main Python libraries for data visualization. We will learn how to present the results of statistical research in a form convenient for further analysis.

Eigen decomposition, singular decomposition and their applications
We will review decomposition methods that are widely used in various fields of data science, including machine learning, signal and image processing, and in recommender systems to improve the accuracy and efficiency of algorithms.

Social network analysis
We will study the basic methods of statistical modeling and analysis of phenomena and processes in large networks. We will get acquainted with a set of modern algorithms and technological platforms for effective analysis of big data in network structures.

Classical regression analysis
We will learn the basic principles of building a simple and multivariate linear regression model. We will consider interesting examples of forecasting sales depending on the price of the product and wages depending on many factors (gender, age, education, part-time or full-time employment).

Bayesian Data Analysis

Decision making theory

Introduction to zero-knowledge proofs
Life on the command line: How text-based interfaces can improve data processing
CV, CV tasks, CV Libraries and frameworks (e.g. OpenCV)

Soon...

What is Cloud and what are they for
Types of Clouds
Microsoft Azure basics
Basic Azure services
Azure Virtual Machine
Azure Storage Account
Learning paths in Azure

How AI Code Generation works. Copilot.

Relational, non-relational, distributed databases in modern software. (Key-Value, Column-based, Document-based, Graph databases)

Mastering Real-Time Processing with Kafka and Flink
This training explores the shift from batch to streaming data processing, highlighting the roles of Apache Kafka for data ingestion and Apache Flink for real-time stream processing. Learn how these tools work together to enable scalable, real-time analytics and modern data-driven solutions.

What "Generative AI" impacts on the real Enterprise?

Radical directness: how to achieve results faster through a feedback culture in the team?
During this presentation, Mariana will talk about:
- The skill of working with feedback as a strong soft skill in the development of technical specialists.
- Difficulties that prevent you from working with feedback efficiently.
- The 4A Framework is a tool for successfully giving and receiving feedback.

Bringing AI ideas and systems to production

Bringing AI ideas and systems to production

Headway Autopark and How Being Open About Failures Moves Us Forward
* Headway’s approach to handling failures and owning mistakes, with real-world cases of how we do it.
* Why failures are actually some of your most important learning opportunities and why being open to them is a crucial part of your self-growth journey.
* What to do if you’re afraid of making mistakes.
* Why avoiding failure is actually harmful to your growth.

Cloud computing basics, SaaS, PaaS and IaaS

Reverse Engineering: Tasks and Tools. An introduction to the world of reverse engineering, its role in cybersecurity and other fields. Practical demonstration of popular tools, such as IDA and Ghidra.

Languages and Automata
The Chomsky classification of formal languages will be presented. Also, different methods of determining of formal languages, in particular we shall discuses the determining of formal languages by automata.
Algebraic Codes
The lecture will be devoted the algebraic theory of codes. We present some algebraic codes, their methods of determining and the maximality of some types of codes.
The Hill Cipher
We present the first mathematical cipher which introduced by Lester Hill in 1927. The method of encryption and decryption of the Hill Cipher, and modern its applications are discussed.

In this session, we will cover the key aspects of protecting applications and the associated infrastructure from cyberattacks, vulnerabilities, and misconfigurations through the implementation of a Product Security Operations Center (PSOC).

Modular Arithmetics and its Applications
This lecture will focus on the properties of integers and their relationships. Modular arithmetic is a fascinating and practical area of advanced mathematics. It is essential in pure mathematics and has a wide range of real-world applications. Moreover, modular arithmetic allows for the easy creation of groups, rings, and fields, which are fundamental components of most modern public-key cryptosystems.

Cryptography methods overview and application
This lecture provides overview of modern cryptography methods and their application:

- Evolution of cryptosystems development from Classical Ancient Cryptography to modern Elliptic Curve Cryptography.
- Concept of cryptosystems efficiency and reliability, types of cryptanalyses. Advantages and disadvantages of symmetric and asymmetric cryptosystems.
- Cryptographic hash functions.
- Application of modern cryptosystems (AES, ChaCha20, RSA, Diffie–Hellman key exchange): electronic digital signature, cryptocurrency, cryptographic protocols TLS/SSL, SSH, OpenSSL library, digital certificates.

The Power of Effective Teamwork
In this session, we will talk about what makes teamwork so powerful. We’ll explore the key difference between a group and a team—spoiler: it's not just working together! Then, we`ll break down the different roles team members play and why every role matters. Lastly, we’ll discuss the stages a team goes through to grow and perform its best. Get ready to learn practical tips you can apply right away to make teamwork work for you!

Cybersecurity in everyday life
This lecture offers fundamental practical guidance on safeguarding personal accounts. We will explore the mindset and methods of hackers, as well as contemporary strategies for ensuring account security. Key topics include creating strong and secure passwords, understanding Multi-Factor Authentication (MFA), and recognizing social engineering tactics with strategies to effectively resist them.

Secure Coding
In this lecture we will focus on best practices and techniques for developing software that minimizes security risks and prevents vulnerabilities. The goal of this session is to help developers identify, mitigate, and prevent vulnerabilities throughout the software development lifecycle.This lecture emphasizes the importance of integrating security into every stage

Game developer as a full-time job
During this session we will discuss the details of working as the game developer in a nowadays industry. From coding the first game towards building your own studio. We will discuss how the games become profitable and what it's like to spend your days thinking about ideas and implementing the game in Unity.

Swizzling in Swift

Leadership in IT