Technology has become a central element of our lives. Social Medias, Digital Marketing, Artificial Intelligence, Connected homes… Our world is changing before our eyes, opening exciting opportunities but also new challenges and traps. More than ever, navigating these worlds safely requires a savvy knowledge of what happens behind the scene.
To contribute to LFC’s goal of educating the global citizens of the future and navigate the modern world, LFC*extra is now presenting Connected World, a series of free technology related courses taught online by members of our community with a solid expertise in their field and the desire to share their knowledge with our students.
Our first two instructors are Lycee parent Scot Wheeler, marketing expert, founder of The Center for Narrative Awareness (CENTNA), lecturer at Northwestern University, and Lycee alumni Winston Michalak, an electric engineering major at Harvard University.
Media Literacy (grades 6-7)
Artificial Intelligence 101 (grades 8-10)
Artificial Intelligence 102 (grades 8-10)
MEDIA LITTERACY COURSE
With Lycee parent and Northwestern University Lecturer Scot Wheeler - In English
Tuesdays and Thursdays, 5:30-6:30pm; Classes run February 23rd through March 30
This course focuses on strengthening participants’ ability to operate as effective individual critical thinkers in their media-saturated environment by developing their understanding of the business objectives and consumer insights that shape the delivery of content and media.
Week 1 – Bread and Circuses: The Power of Entertainment (2/23 & 2/25)
Learning Objective: At the end of this week, participants will understand how throughout history, media and entertainment have intertwined with culture, commerce and civics.
Week 2 – Thinking Fast and Slow (3/2 & 3/4)
Learning Objective: At the end of this week, participants will understand the difference between reflexive thought and reflective thought, and the utility of each.
Week 3 – The Market for Media (3/9 & 3/11)
Learning Objective: At the end of this week, participants will understand that all content is delivered in pursuit of some kind of monetary or ideological opportunity, and that consumption of content always involves some cost, particularly if engaged uncritically.
Week 4 – Bubbles, Beliefs and Branding (3/16 & 3/18)
Learning Objective: At the end of this week, participants will have made a collage of their personal “filter bubbles”, with articulation of their values and beliefs. They will understand that these are what advertisers and content creators want to build associations around with them, and that these values should shape their responses to content rather than become shaped by content.
Week 5 & 6 – Video Project (w/o 3/22 = independent work. 3/30 = presentation event.)
Learning Objective: At the end of these two weeks, participants will have solidified their understanding of the course topics by working in groups to script, record and produce a 5-10 minute presentation describing:
The role of content/entertainment in shaping/reinforcing culture, commerce and civics,
The kinds of content in today’s paid and social media that attempt to influence these areas,
Their perspectives on what values should be promoted through content, and what that content would look like,
Ideas for how they and their peers can more reflectively engage with the ideas they encounter through media, and even deliver their own ideas through media.
ARTIFICIAL INTELLIGENCE 101 & 102
A programming introduction
With Lycee Alum and Harvard student Winston Michalak - in French
Tuesdays and Thursdays, 5:30-6:30pm;
101: Classes run January 12-February 4
102: Classes run February 23-March 19
Course Infrastructure: Google Colab, Google Classroom, Zoom Video Communications
The world is changing. Computer programming has become an essential and highly sought-after skill, and computers have huge potential with the introduction of artificial intelligence and the closely related field of machine learning. This course is meant to provide an introduction to programming through the lens of machine learning. The primary objective of the course is to expose students to the fundamentals of machine learning and computer programming.
Upon successful completion of this course, students will be able to:
• Learn basics of data analysis
• Learn basics of python programming
• Understand the logic underlying various machine learning algorithms
• Gain practical experience deploying various machine learning models and methods
• Use Google Colab Notebooks to solve problems, visualize data, and communicate results
• Open the door to conduct cutting-edge research on machine learning and artificial intelligence
This course is entirely remote and will be conducted using Zoom Video Communications and Google Colab Notebooks. Google Colab is an open-source application that is part of the Google Workspace (with Docs, Sheets, Classroom, etc.) and allows anyone to create documents containing code, equations, visualizations, graphs, and narrative text. It is a powerful tool for performing data analysis and machine learning, and having a good understanding of Google Colab is very useful in the professional world.
This course does not have any assignments or grades. The main objective of the course is to allow students to focus on having fun and learning the material. That said, it will be far more useful for the student to engage with the course materials as deeply as possible, and the student will ultimately get out of the course what she decides to put into it.
Programming is a powerful skill to have. Like any spoken language such as English or French, programming languages are nuanced and sometimes unintuitive. Therefore, the most effective way to learn programming is by programming as frequently as possible. We hope this course will provide students with many useful examples of programming problems, and we strongly encourage students to explore and build programs on their own as well.
Artificial Intelligence 101: This course is intended to serve as the first part of a two part curriculum. In this first part, the student is introduced to basic classification machine learning algorithms. In the second part, the student is introduced to more complicated classification algorithms and simple regression methods. The second part of the course may not be taken without taking the first part of the course, as the material builds on itself.
Artificial Intelligence 102: This course is the second part of a two-part curriculum that started with AI 101. In this second part of A Programming Introduction to Artificial Intelligence, we will visit more advanced classification methods — including kNN and Tree-based methods — and (time allowing) introduce additional AI-based frameworks — including deep learning and simple regression models."