C7675 - AI-POWERED BIBLIOGRAPHIC TOOLS, LATEX, AND PYTHON FOR SCIENTIFIC PUBLISHING

Conoscenze e abilità da conseguire

Upon completing the course, students will be able to:

• Apply fundamental scientific writing principles and effectively utilize LaTeX integrated with bibliographic management tools for professional academic documents.
• Leverage traditional and AI-powered research tools to streamline literature reviews and manage academic references.
• Employ basic Python programming techniques, assisted by AI tools, for fundamental research data management, manipulation, and visualization.
• Demonstrate proficient interpersonal communication, public speaking, and presentation skills tailored to academic contexts.
• Effectively manage negotiations, resolve conflicts, and exercise leadership within team settings, enhancing collaborative research dynamics.
• Successfully plan, execute, and present collaborative research-oriented projects.

Programma/Contenuti

Teaching Sessions (6 hours total)

Session 1 (2 hours): Academic Writing and LaTeX

Principles of scientific writing, LaTeX document preparation, integration with Overleaf, and bibliographic management using BibTeX.

 

Session 2 (2 hours): Bibliographic Research and AI-Assisted Tools

Introduction to traditional and AI-powered bibliographic tools (Zotero, Connected Papers, Research Rabbit, etc.) and their application to literature reviews.

 

Session 3 (2 hours): Python for Data Management and Visualization

Basics of Python programming for data extraction, management, manipulation, and visualization using AI coding assistance.

 

Laboratory Sessions (12 hours total)

Lab 1 (30 min): Team Formation and Project Introduction

Brief team-building activity and project outline.

 

Lab 2 (4 hours): LaTeX and Bibliographic Research Tools

Extensive hands-on exercises using LaTeX, Overleaf, Zotero, and AI-powered bibliographic tools for academic document preparation and management.

 

Lab 3 (4 hours): Python for Data Management, Manipulation, and Visualization

Practical coding sessions focused on research data tasks, leveraging AI to facilitate code writing and data analysis.

 

Lab 4 (3.5 hours): Project Finalization and Presentation Preparation

Finalize project reports using LaTeX, create visualizations with Python, rehearse group presentations, and engage in peer feedback.

Testi/Bibliografia

• Lecture slides and notes
• Online Latex Editor, Overleaf: https://www.overleaf.com/
• Python Documentation: https://docs.python.org/3/

Metodi didattici

The course content will be entirely covered by the lectures. The course includes some laboratory sessions, which will cover the practical aspects of the lectures. The instructors will tutor the students.

Modalità di verifica dell'apprendimento

The assessment of the "expected learning outcomes" is composed of:

• Individual multiple-choice quiz (40%)
• Group research report (30%)
• Group presentation (30%)

Strumenti a supporto della didattica

The teaching tools are projector with PC and whiteboard.

Orario di ricevimento

Consulta il sito web di Nicholas Fantuzzi