AI, digital masters, sustainability course

In September 2021 we have added new materials for course we did this year in LPI this year with new track of students

https://github.com/Big-data-course-CRI/materials_big_data_cri_2024_2025 

The course is read together with Interaction data lab (twitter @idlab) 

Course Description

This course will provide an introduction to the field of Data Science, with applications to statistical testing, explainable AI and sustainability related data (examples of spatial data, citizen science data). This course provides connections with other courses on Data Science course, Statistics, Research Methods, Citizen Science and Exploring Sustainability and Artificial Intelligence.

The course will first cover the basics of data cleaning, analysis, visualization and statistical testing. The aim of this first part is to build intuition working with data (notion of  dataframe), in particular in the context of testing for the significance of associations between variables. This will be of particular importance to the personal research project that involves the collection of quantitative data. In the second part we will speak about the foundations of AI, which will play an important role for other courses further and will help students to orient better in numerical methods for analysis being created nowadays. Why focus on the foundation of AI, explainable data analysis and network data? Over the past decade, developing explainable AI methods became an important milestone in science and technologies. In the foundations of AI we will speak about the Network studies, which have had significant impact in disciplines as varied as mathematics, sociology, physics, biology, computer science or quantitative geography, giving birth to Network Science as a field of itself. With the recent rise of social networks in the last decade, their use has now become widespread in the digital world. We will provide theoretical foundations of the field of Network Science and Embeddings, which are both widely used for processing the data and development of algorithms. In the practical hands-on part we will speak about analysis and visualization of real-world data.

Course objective (Pedagogical objective)

At the end of the course the students will have gained intuition to analyze real-world data and get introduction to some AI methods. They will be able to use Python for statistical analyses and working with data. They will know practical tools and packages to work with sustainability data, as well as network visualization tools. Finally, they will have obtained good practices for code and data management.

Syllabus and Agenda:

18th September:

• Morning: Elements of statistics for data analysis: building intuition with a dataset)

• Afternoon: Introduction to data science, network science

20th September 

• Morning: Foundations on AI for data science: from theory to practice on data fitting, embedding, modeling

• Afternoon: Spatial data analysis, Data and Network visualization

May 2024, together with Afgan Girls, Lecturers without borders
What is the bigger picture?

773 million people in the world are illiterate. Even more people are digitally illiterate UNESCO reports. UNESCO also reported that over 617 million children and adolescents were not achieving minimum proficiency levels in reading and mathematics.

What do we do?

Addressing illiteracy is a huge field on its own. We start by bridging the AI gap in the communities we can access. We create educative programs on the basic computer science behind AI, using explainable AI and digital art approaches.

What is the format?

Seminars, participatory lectures.

Review Process: To ensure the quality and relevance of presentations, we will be conducting an open review process using Google Slides during the weeks preceding the event. This will allow for constructive feedback from peers and experts in the field, ultimately enhancing the overall experience for our audience, particularly the students.

How can I participate?

We started already by organising the first week in May 10th-25th in collaboration with Afghan Girls Success Gate.

Computer scientists who would be interested in joining future editions of the Thematic Week in AI Literacy, please reach out to us at info@lewibo.org with the subject "AI Literacy thematic week".

NetSciEd conference presentation

Blogpost for NetSciEd 2024: Lecturers without borders changes since 2017

As the follow up on the seminar organised during NetSci2024 and specifically NetSciEd satellite, I have written the session

These are the links I was sharing. Since 2017 when we started Lecturers without borders in Nepal, we have gone through different stages of development of the organisation of the outreach - from the very first stages of 'do it yourself' stage when there were just 4 of us doing all lectures, coordination. To the stage, when coordination was mainly done by coordinators funded by the foundation, to the regime, when the organisation was again mostly driven by volunteers. What is important for me however throughout this experience is the willingness of people to make, to share knowledge, across borders, in usual situations.

Experience of teaching in India. There were children, whose age I was not sure about, whose background I did not know until the start of the lecture (from 7 to 10 age old). very often i have been giving lectures about network science, as something very intuitive, universal, and which could become

Which materials we were teaching. Since 2017 i have been following NetSciEd workshops where researcher were working on Network Literacy (e.g. see the work, which have been translated to many languages https://sites.google.com/view/netscied-2021/home-page) I have been always taking it as an example of perfect materials to share with students of different ages, from even 5-6 years old, where you can play a network game or make some visualisations of networks, which will be clear to everyone.

If you ever want to make a lecture, when you are traveling, these are the links to follow www.lewibo.org

Article about us

https://www.forbes.com/sites/juliabrodsky/2022/01/27/how-lecturers-without-borders-shares-the-joy-of-science/