Data Analysis 1: Introduction to Jupyter Notebooks

Dies ist eine speziell für die Universität Mainz angepasste Version der "Einführung in Citizen Science". Der Kurs dauert etwa 1,5 Stunden und richtet sich an Citizen-Science-Praktiker:innen und Forschende. Er bietet einen grundlegenden Einstieg in das Thema und setzt keine Vorkenntnisse voraus. Der Kurs hilft Ihnen dabei: Citizen Science zu definieren, die Geschichte und Bedeutung von Citizen Science zu verstehen – und nachzuvollziehen, wie sich daraus die heutige Praxis entwickelt hat, verschiedene Typologien kennenzulernen, die die unterschiedlichen Formen und Stufen der Beteiligung von Bürger:innen in Citizen-Science-Projekten beschreiben. Am Ende dieses Kurses werden Sie die wichtigsten Merkmale von Citizen Science besser einordnen können. Nach jedem Abschnitt finden Sie ein kurzes Quiz oder eine kleine Übung. Am Ende des Kurses gibt es ein Abschlusstest mit zehn Fragen. Wenn Sie mindestens 50 % der Punkte erreicht haben, erhalten Sie das offizielle Badge der ecs academy. Schreiben Sie sich in den Kurs ein. Verwenden Sie dazu den key code opensciencecertificate. Nach der Anmeldung können Sie alle Inhalte nutzen, die Quizfragen bearbeiten und nach erfolgreichem Abschluss das Badge erhalten. Bitte sende nach dem Abschlusstest eine E-Mail an m.gross@ub.uni-mainz.de.Nach Überprüfung Ihrer Aktivitäten wird das Badge an Sie versendet und dient als Nachweis für den Erhalt des Open Science Zertifikats. Viel Freude beim Lernen – und viel Erfolg im Kurs! This is a version of the Introdcution to citizen science that been adapted to the needs of University Mainz. This is a course of approximately 1.5 hours for citizen science practitioners and researchers, that provides you with a basic introduction to citizen science and requires no prior knowledge of the subject.  The course will help you to: define citizen science, understand the history and significance of citizen science and how it has evolved into the modern-day practice we see today, understand the different typologies that have been created to explain the varying levels of public participation in citizen science. By the end of this course you will better understand the key characteristics of citizen science. At the end of each section there is a short quiz or activity, and a ten question quiz at the end of the course. If you score 50% or more in the final quiz then you will earn a course completion badge. Click here to enrol in this course and use enrolment key opensciencecertificate to do so. Once you enrol you will be able to take quizzes and receive a badge upon successful course completion. Please sent an email to m.gross@ub.uni-mainz.de after finishing the quiz. After checking your activities you will receive the badge from our side. Happy learning and enjoy the course!

Welcome to the “Introduction to Pandas” course! This comprehensive course, designed for beginners, takes approximately 3 hours to complete and provides a foundational understanding of Pandas. No prior knowledge of the subject is required. This course will help you to: Understand what Pandas is and its key features and benefits. Work with Series and DataFrames, the core data structures in Pandas. Perform indexing, selecting, and assigning operations in Pandas. Utilize basic functions to manipulate and analyze data. Apply grouping operations to aggregate and summarize data. Combine and merge datasets for comprehensive data analysis. By the end of this course, you will be well-prepared to handle data efficiently using Pandas, setting a strong foundation for more advanced data analysis and manipulation tasks.

Welcome to the “Introduction to NumPy” course. This free course, designed for beginners, takes approximately 3 hours to complete and provides a foundational understanding of NumPy. No prior knowledge of the subject is required. This course will help you to: Understand what NumPy is and its key features and benefits. Create and manipulate arrays efficiently. Perform element-wise operations on arrays. Use mathematical and statistical functions with NumPy. Execute operations involving arrays of different shapes and sizes. Perform advanced indexing and slicing techniques. Work with arrays in the context of data analysis and scientific computing. By the end of this course, you will be well-prepared to interact with NumPy confidently, setting a strong foundation for more advanced data analysis and machine learning courses.

Welcome to the “Visualization in Python” course. This free course, designed for beginners, takes approximately 4 hours to complete and provides a foundational understanding of data visualization using various Python libraries. No prior knowledge of the subject is required. This course will help you to: Understand the importance and role of data visualization in data science. Learn how to create and customize a variety of charts and plots using Matplotlib. Explore the capabilities of GGPLOT for creating layered visualizations. Utilize Seaborn for statistical data visualization. Harness the power of Bokeh for interactive visualizations. By the end of this course, you will be well-prepared to create insightful and interactive visualizations, setting a strong foundation for more advanced data analysis and visualization tasks.

Welcome to the “Introduction to Python” course. This comprehensive, beginner-friendly course is designed to take approximately 4 hours to complete and provides a solid foundation in Python programming. No prior knowledge of Python or programming is required. This course will help you to: Understand the basic syntax of Python, including how to execute calculations and define and modify variables. Navigate through various control structures such as conditionals and loops to control the flow of your program. Explore and manipulate essential data structures like tuples, lists, and dictionaries. Learn to structure your code effectively by defining and using functions to prevent repetition and improve code clarity. By the end of this course, you will have a strong understanding of Python's core concepts and be well-prepared to advance to more specialized topics such as data analysis and machine learning.

This course will help you understand the ethical and organizational challenges of designing and implementing participatory activities with different stakeholders and particularly citizens in an ethical and meaningful way. By the end of the course, you should have a good understanding of the questions and considerations to take into account when planning, implementing and evaluating such an activity. The contents of this course build on the learnings of the PRO-Ethics project, and especially its main output, the Ethics Framework and Guidelines: A guide for research funding organizations implementing participatory activities.

This is a free course resource that was developed as a guide for designing your own course on the citizen science-topics discussed: Research & Methodology, Education & Awareness-raising, Support Resources & Infrastructure, and Policy & Assessment. It includes resources such as detailed session/workshop outlines and PowerPoint slides. The enrollment key for the course is TIME4CS

Clea Montanari Clea Montanari

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This area of moodle is set for communication and exchange of resources between network members of the network of citizen science educators and trainers. 

Lucy Robinson Lucy Robinson

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Welcome to this short training course, which we hope you will find inspiring, energising and informative. The course is specifically aimed at museum staff, or those working closely with museums and similar institutions like science centres. It has been developed by citizen science practitioners at museums in the UK and Germany, with support from colleagues across Europe and beyond. Over the course of two hours, we will share examples and case studies of citizen science projects at museums, highlight museum-specific considerations, challenges and opportunities when developing a project, and give you tools and strategies to develop your own citizen science research project. The six sections introduce you to:A brief history of citizen science in museumsResearch opportunities through a citizen science approachEnhancing outcomes for citizen science participantsReal-world impact: Societal, conservation and policy outcomes of citizen scienceEthical considerationsOur goal is for you to:Reflect upon the long tradition of museums as an interface between research and society, professional societies and individual lay researchers, as well as in the form of (joint and open) data collection and archiving. Understand the benefits of a citizen science approach, for yourself and your organisation, for academic research, for the people who take part, and for the environment. Be able to capitalise upon and appreciate the opportunities and challenges at Museums as host organisations for citizen scienceBe aware of ethical considerations, and strategies to work towards equitable and inclusive citizen science.Understand the tools and resources available to support you as you develop or participate in a citizen science scheme.