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Artificial Intelligence courses
Category overview
Všimli ste si, že ak s nami niekto nesúhlasí, alebo povie niečo, čo sa nám nepáči, prestaneme počúvať a v hlave začneme spriadať plány na svoju obranu alebo útok?
Často to končí hádkou, prinajmenšom zlým pocitom, že nám dotyčná osoba krivdí, nerozumie, nerešpektuje nás.
Ak odoláme pokušeniu obhajovať sa alebo útočiť, pozorne si druhú stranu vypočujeme, budeme zvedaví na dôvody, skúsenosti, informácie, z ktorých vychádzala pri svojich tvrdeniach, nemusí to tak dopadnúť.
Ak s niečím nesúhlasíme, máme iný názor, ako náš partner, skôr ho presvedčíme o našom názore, ak mu dáme najavo, že počúvame jeho námietky. Hľadáme to, čo nás spája a vymedzujeme sa len voči tomu, s čím nerezonujeme. Neútočíme, naopak ukazujeme, že sme otvorení iným názorom a snažíme sa byť objektívni. Tým mu prejavujeme náš skutočný záujem a rešpekt.
Bude to fungovať, ak:
- Skutočne počúvame (nie len počujeme).
- Hľadáme, čo je na jeho názoroch pravdivé, s čím rezonujeme, s čím/s akou časťou toho, čo hovorí, súhlasíme.
- Pri argumentácii najskôr hľadáme to dobré, čo funguje/ s čím súhlasíme/čo je fakt a oceníme to. Až potom vylepšujeme.
Napr.:
Počúvam, čo hovoríš, a potom reagujem:
„Áno, na tvojom názore sa mi páči…“, „Z toho čo hovoríš, súhlasím s ….“
A potom dodám svoju myšlienku:
„… a ešte by sme mohli…“, „… a pre mňa je ešte dôležité…“, „… a k tomu chcem pridať ešte…“
Ďalším tipom na vytváranie atmosféry spolupráce namiesto konfrontácie je sústredenie sa na spojku ALE. „Ale veď ‘ale’ používame, ako keď dýchame!?“ Bežne si neuvedomujeme, že sme sa práve nadýchli a vydýchli. A istotne, sme tak urobili! ☺
Spojka “ale” je totiž toxická, preto je s ňou potrebné manipulovať len s ochrannými pomôckami. Presvedčiť sa o tom môžeme na nasledujúcom príklade:
Ktorá z nasledujúcich viet vyznieva konfrontačne, a ktorá skôr nabáda k hľadaniu riešenia?
- „Ja chcem ísť k moru, ale ty chceš ísť do hôr.“ („Stále je medzi nami nejaký problém…“, „Nikdy sa mi nechceš prispôsobiť…“, „Mali by sme sa rozísť pre neprekonateľné rozdiely!“)
- „Ja chcem ísť k moru a ty chceš ísť do hôr.“ („Čo s tým urobíme?“, „Ako to vyriešime?“)
Snažme sa, aby naše diskusie boli o spoločnom hľadaní objektívnych kritérií. Veď je len na nás, či chceme byť súčasťou riešenia, alebo problému.
A nezabúdajme – požadované správanie môžeme vyvolať tým, že ho ukážeme ako prví. ☺
Contents
Active courses: 4
Price incl. VAT
1 246.00 €
Current VAT 23%
Duration
Day: 8 days
Course overview
Python Programmer with AI Assistance - a package of courses is intended for those who want to acquire the basics of programming in Python using artificial intelligence. In the course, you will learn the basics of Python and advanced programming, which you will expand with programming with AI assistance. Python is an ideal programming language even for beginners. The package of courses covers work with artificial intelligence - general familiarization with basic terms and chatbots such as ChatGPT or Gemini. You will then learn to apply AI when developing applications in Python. The package contains the courses: Python programming - basics in the scope of 2 days Python programming - advanced in the scope of 2 days Introduction to working with artificial intelligence in the scope of 2 days AI assistance when programming in Python in the scope of 2 days
Minimum input knowledge
No specific entry knowledge is assumed.
Output knowledge
Creating more complex programs in Python, including object-oriented design creation and its implementation. All this without, but especially with effective use of artificial intelligence.
Training syllabus
Installation of Python and PyCharm IDE
- creating first scripts running a program in PyCharm IDE running a program on Linux
Python Language
- characteristics of the Python language history of the language and its use
Lexical Structure of Python
- comments and whitespace identifiers, literals operators and separators keywords
Data Types and Variables
- Boolean data type numbers and strings None data type
Working with Strings
- creating strings basic string operations string formatting
Operators and Expressions
- types of operators (logical, relational, arithmetic) precedence and associativity of operators
Program Flow Control
- conditions loops
Containers in Python
- tuples, lists, dictionaries, sets
Dates and Time with the PyQt Library
- QDate, QTime and QDateTime classes universal time summer and winter time
Creating Charts with the Matplotlib Library
- creating and exporting charts line, bar, pie charts
Working with Excel Files with the Openpyxl Library
- reading and writing data formulas, images and charts
Working with Images with the Pillow Library
- image manipulation image export watermark creation
Creating a GUI with the PyQt Library
- principles of graphical user interface basic components (QLabel, QPushButton, QSlider) event programming working with graphics
Creating Web Requests with the requests Library
- GET, POST, HEAD requests working with JSON data authentication
Web Applications with the Flask Library
- basics of web applications routing templates
Functions
- types of functions creating functions anonymous functions
Object-Oriented Programming
- OOP principles classes, objects and methods inheritance
Modules
- meaning of modules, built-in modules working with modules creating custom modules
Packages
- meaning of packages working with packages
Files and Directories
- writing to files reading from files with command working with CSV files
Exceptions
- errors in a program catching and creating exceptions
Practical Examples
- creating charts, working with images simple graphical and web application
Python Language Basics - Review
- lists (arrays), tuples and working with them working with strings, formatting, string module dictionaries and working with them
Working with Files
- basics of working with files opening files for reading and writing working with files
Errors and Exceptions
- familiarization with exceptions types, raising, catching and handling exceptions
Object-Oriented Programming
- OOP basics, classes, properties and methods constructors and destructors inheritance and multiple inheritance
Debugging
- use of the debugger for testing, finding errors, but also understanding a program written by another programmer
Introduction to Working with Artificial Intelligence AI
- definition and history of AI, key areas and applications
Use of AI
- creative writing, creation of images, music, video and code, robotics
Theoretical Basics
- machine learning, neural networks, deep learning networks
Large Language Models (LLM)
- definition of LLM, creation of language models, use of existing models
Chatbots
- Copilot, Gemini, ChatGPT, DeepSeek
Prompts
- definition of prompts, principles of prompt creation
Practical Examples
- text summarization, translations, information mining, document analysis
Functions and Modules
- types of functions, creating functions, anonymous functions, importing and using modules
Object-Oriented Programming
- OOP principles, classes, objects and methods
Working with Files
- reading from a file, writing to a file, exception management
AI Assistance When Programming in Python
Tools and Frameworks in Python
- Ollama, LangChain, LangFlow, Hugging Face Transformers
Gradio
- creating dashboards for LLM applications
Price incl. VAT
307.50 €
Current VAT 23%
Duration
Day: 2 days · Evening: 3 days · Weekend: 2 days
Course overview
The Artificial Intelligence - Practical Applications course is for everyone who wants to use the potential of artificial intelligence in practice. Within the course, participants will learn to implement AI solutions into everyday work processes, automate tasks and increase productivity. The course does not require programming knowledge and is focused on practical use of available AI tools and platforms.
Minimum input knowledge
Basic skills in working with a PC. No special entry knowledge is required.
Output knowledge
The course participant will begin to orient themselves in basic terms and will be able to identify different approaches in the area of AI. This course can also be an introduction to self-realization, after which the participant will be able to use the acquired knowledge in applications.
Training syllabus
Introduction to Artificial Intelligence
- What AI, machine learning and deep learning are
- Current trends and ethical aspects
Large Language Models (LLM)
- ChatGPT, Claude, Gemini
- Effective work with prompts
- Prompt engineering techniques
AI for Increasing Productivity
- Automation of texts, e-mails and presentations
- Summarization and translation of texts
Generating Images Using AI
- DALL-E, Imagine
- Creating prompts and editing images
AI Tools for Video and Audio
- Transcription and subtitling
- Voice generation and voice cloning
AI in Data Analysis
- Data analysis and visualization
- Predictions using AI tools
Automation of Work Processes
- Integration of AI into existing tools
- AI assistants (Copilot, Gemini)
AI in Customer Support
- Chatbots and virtual assistants
- Automated answers
Security and Data Protection
- GDPR and AI
- Risks and best practices
Future of AI
- New technologies and trends
- Case studies
Price incl. VAT
307.50 €
Current VAT 23%
Duration
Day: 2 days · Evening: 3 days · Weekend: 2 days
Course overview
The course is intended mainly for programmers who want to become familiar with the basics of artificial intelligence and start using it in their programming work
Minimum input knowledge
Basic programming skills are an advantage
Output knowledge
Participants will become familiar with basic artificial intelligence tools, their principles and operation with the goal of using them effectively in practice.
Training syllabus
Introduction to Working with Artificial Intelligence AI
- definition and history of AI, key areas and applications
Use of AI
- creative writing, creation of images, music, video and code, robotics
Theoretical Basics
- machine learning, neural networks, deep learning networks
Large Language Models (LLM)
- definition of LLM, creation of language models, use of existing models
Chatbots
- Copilot, Gemini, ChatGPT, DeepSeek
Prompts
- definition of prompts, principles of prompt creation
Practical Examples
- text summarization, translations, information mining, document analysis
Price incl. VAT
369.00 €
Current VAT 23%
Duration
Day: 2 days · Evening: 4 days · Weekend: 2 days
Course overview
The AI Assistance When Programming in Python course is intended for everyone who wants to become familiar with a modern way of programming in Python with the help of artificial intelligence
Minimum input knowledge
Basics of programming in Python, basics of AI
Output knowledge
Course participants will become familiar with the principles and techniques of programming in Python with the assistance of artificial intelligence.
Training syllabus
Large Language Models (LLM)
definition of LLM, creation of language models, use of existing models
Chatbots
Copilot, Gemini, ChatGPT, DeepSeek
Prompts
definition of prompts, principles of prompt creation
Practical Examples
text summarization, translations, information mining, document analysis
Tools and Frameworks in Python
Ollama, LangChain, LangFlow, Hugging Face Transformers
Gradio
- creating dashboards for LLM applications