The courses include practical works, where students typically learn to create or test AI solutions that can operate in real business environments. Throughout the course, each week, students acquire a new skill through practical sessions. The practical sessions usually start with a hands-on class and are followed by independent work done at home. The content and complexity of the practical sessions are chosen based on the specifics of the course, as well as the current technological advancements in the AI revolution. Here’s an overview of some previous practical sessions:

• Enablers of the AI Revolution: Economic, social, technological, and political factors.
• Predictive Analytics, Category Classification.
• Predictive Analytics, Regression (forecasting numerical data).
• Predictive Analytics, Forecasting Performance Indicators (time series).
• Evaluation of Virtual Assistants in Retail for Other Companies.
• Training a Neural Network Model for Classifying Employee Productivity Based on Audio or Video Input.
• Content Analytics for Enhancing Commercial Texts.
• Speech-to-Text Tools, Transcribing Meeting Audio Recordings and Automatically Generating Summaries.
• Natural Language Processing (NLP) in Business Processes, Speech Synthesis.
• Designing, Building, and Testing a Commercial Chatbot Using Intent Mapping Method.
• Building a Virtual Assistant Based on a Large Language Model.
• Financial Analysis Virtual Assistant.
• Creating an Alexa Skill Voice Chatbot to Facilitate Customer Communication with a Company.
• Building an LLM Web API for Personalizing Advertising Texts.
• Building a Web Scraping and Sentiment Analysis Tool Using Google Sheets to Assess Consumer Sentiment and Market Trends.
• Customer Support Response Generated by a GPT Chat Agent.
• Using GPT for Decision-Making in Management Scenarios.
• Using a Virtual Agent as a Business Startup Consultant.
• Using a Virtual Agent as an Employment Relations Consultant.
• Virtual Agent in Recruitment: Choosing the Best Candidate Based on Job Description.
• Building a Virtual Secretary or Email Bot that Understands Customer Inquiries and Responds.
• Generating a Response Letter Based on Previous Client Correspondence Using Vector Database Methods.
• Risk Assessment Tool Based on a Large Language Model.
• Business Process Automation Platforms (Zapier, Make).
• Using Graph Databases for Storing Company Knowledge.
• Advanced Features of an LLM-Based Virtual Agent: Internet Search and Verbose Output.

These practical sessions cover a wide range of AI applications, providing students with hands-on experience in deploying and testing AI in real-world business scenarios.