Supporting by:
The school starts in
45
registered participants
Traditionally, every summer we invite the best industry specialists, experts, mentors, and lecturers from leading IT companies to create a unique educational platform for learning the features and innovations of artificial intelligence technologies.
Objective:
– to create an educational platform for studying theoretical bases and practical skills between students and the IT industry in the field of artificial intelligence.
– to increase the attention of students of technical specialities to the challenges and opportunities provided by artificial intelligence technology.
– to create the basis for the development and creation of innovative products and solutions using artificial intelligence.
Artificial intelligence is a powerful driver of change that opens up endless possibilities for the development of new technologies.
When: June 24 - July 7, 2024
Format: Online
Training features: Two parallel learning streams (CoreA - 1-2 year students; CoreB - participants with experience in IT, including 3-4 year students).
School language: English
Target audience: Technical students from Ukraine and abroad
School Topics: machine learning, Python basics, deep learning, mobile development for iOS, Android, etc
For who we are looking (or need):
– Speakers, mentors, tutors for the school's work
– partners for quality representation of the school
Write to our inbox: marketing@lnu.edu.ua
P.S. By creating artificial intelligence, we are opening up endless possibilities for a future where machines and humans can work together to achieve incredible success in science, art, and life in general," - chat GPT!
CORE A (EDUCATIONAL)
Python for DS, ML&DL
1. Python for data analysis
2. Python for visualization
3. Python for data mining
4. Version Control System basics:
Git, Data Version Control (DVC),
Data sources (Kaggle, etc.),
ML Hubs (Hugging Face, etc.)
Cloud services and technologies.
Cloud computing
1. Cloud computing basics,
SaaS, PaaS and IaaS
2. Amazon Web Services
3. Google Cloud Platform
4. MS Azure
Big Data
1. Big Data in AWS
2. Big Data in GCP
3. Big Data in Azure
4. Big Data Visualization
Deep learning
1. Deep learning basics
2. Supervised deep learning
3. Reinforcement deep learning
4. Unsupervised deep learning
Advanced Мachine learning
1. Image recognition and classification
2. Speech recognition and Audio recognition
3. Text recognition and text emotion detection
4. Deep learning for forecasting
Databases & Data warehouses
1. Database basics, relational, non-relational,
distributed databases
2. Data warehouse, ETL, Data Workflows
3. NoSQL: Key-Value, Column-based,
Document-based, Graph databases
4. Database usage for Data Science,
Data Analysis and Machine Learning
Мachine learning basics
1. Machine learning basics
2. Supervised Machine Learning
3. Reinforcement Machine Learning
4. Unsupervised Machine Learning
Machine Learning tools
1. Basic libraries: Numpy, Pandas, Scikit-learn,
Seaborn, matplotlib, sktime, skforecast
2. ML Frameworks (part 1):
TensorFlow, Keras, PyTorch
3. CV Libraries and frameworks, OpenCV
4. NLP libraries and frameworks, NLTK
Generative AI
1. Generative models basics
2. Generative models for artificial art
3. LLM, Transformers, BERT,
GPT models family (GPT-1, 2, 3, 3.5, 4)
4. LLM fine-tuning techniques
Real-world AI applications
1. ChatGPT usage, ChatGPT API,
tokenization, creation and usage GPTs
2. Artificial Intelligence of Things,
Embedded AI, AI Autonomous
Systems (drones, vehicles, etc)
3. AI Code Generation, Copilot, etc
CORE B
Advanced Мachine learning
CV, Image recognition and classification, NLP, Speech recognition, Audio recognition, Text recognition and emotion detection, Deep learning for forecasting, End-to-end Machine learning projects/models to solve practical problems, Generative models, artificial art, Language models, Transformers, BERT, GPT models family (GPT-1, 2, 3, 3.5, 4), GPTs: Usage and creation, Adaptive AI, AI Trust, Risk and Security Management (AI TRiSM), AutoML, Multi-modal learning, Democratized AI
High-performance computing
Fundamentals of parallel, hybrid and distributed computing, Getting Started with Jetson Xavier, NX Developer Kit, Getting started with Google Coral's, TPU USB Accelerator or/and Google Coral, Development Board
Mobile development
Android, iOS, Flutter, Kotlin Multiplatform for Cross-Platform Mobile Development,
Swift, React Native for mobile, Integration of artificial intelligence systems in mobile
development, Distribution of mobile applications
Web development
Web development using Flask / Django, Authentication methods for web services, Organization of infrastructure and deployment of web services, Web analytics, Social network analysis, Crawlers, analytical platforms, Integration of artificial intelligence systems in web development, JavaScript
Software development
C, C++, Java, Go, Digital Immune System, Superapps, Platform Engineering, AI Code Generation
IoT, IIoT, AIoT
Internet of Things, Industrial Internet of Things, Artificial Intelligence of Things, Edge AI, Embedded AI, Autonomous Systems (drones, vehicles, etc)
AI in Automotive
Atomization
AI Virtual reality
Metaverse Digital twins
Building of products empowered by AI
Usage of AI in modern services, applications, platforms
AI in COVID researches and solutions, AI in sustainable,
ecological and environmental technologies
Decision Support Systems and Applied Observability
Cyber security and AI
Soft Skills
Communication, Collaboration and teamwork, Time management and organization, Empathy / Emotional intelligence, Owning up to errors, Problem solving and creativity, People skills and management, Innovation, Analytical thinking
Opening ceremony of the school
Vitaliy Kukharskyy - Vice-Rector for Research, Teaching and IT-Development
Speakers (in process)
General partner
Official partners
Partner
Participant
Information partner
How to join?
1) To provide the school with a speaker or mentor;
2) to support the project implementation by becoming its partner.
Advantages of partnership:
- additional promotion of your company among students;
- communication and involvement of the students into the company's activities;
- distribution of information content and posts about the company in the social networks of the University;
If you want to take part in schoolwork or cooperate with us, send us an email: marketing@lnu.edu.ua