The training began with a session titled "Effective Prompt Engineering," focusing on techniques for effective communication with artificial intelligence. In this session, presented by Professor Murat Yerlikaya, participants were introduced to ways of interacting efficiently with AI, effective prompt-writing techniques, and practical tips. Following this, Professor Yerlikaya led another session titled "NotebookLM: Note Taking with AI, Automatic Q&A, and Language Tools Integration," where participants gained detailed knowledge about note-taking, note management, and DeepL integration using the NotebookLM tool. Later in the day, participants learned valuable insights about using artificial intelligence in data analysis. In the session titled "Using AI in Data Analysis," guided by Murat Yerlikaya, a hands-on workshop was conducted on performing data analysis and obtaining analytical results using ChatGPT.
The afternoon portion of the training continued with the session "Artificial Intelligence-Supported Literature Review and Summarization Methods with Typeset," led by our coordinator, Mehmet Akın Bulut. Participants explored methods for conducting scientific literature reviews, summarizing data, and performing content analysis. Following this, a session titled "Data Visualization Applications" was held, where the use of AI-supported data visualization tools in academic processes was discussed. The training concluded with a "Program Evaluation and Q&A" session with all the instructors.
This training, organized to promote the more effective use of artificial intelligence technologies in academia, received significant interest from participants and was highly productive. We extend our thanks to all the instructors and participants.
