Schedule
Week 1ΒΆ
π In-Class: Tue, Jan 6
Worksheet
In-Class Activities
Perceptions of AI
Individual reflection and small-group discussion.Reading and Reflection
Read this article and respond to guided questions.Class Discussion: Responsibility
Whole-class discussion on responsibility and accountability in AI.
Submission
Upload a PDF of the completed worksheet to Gradescope under
In-Class β Week 1 Tuesday
π In-Class: Thu, Jan 8
Worksheet
In-Class Activities
What Makes Something Intelligent?
Group Activity: Small-group discussion using a shared board.
Big Ideas in AI
Short discussion on perception, representation, learning, interaction, and societal impact.
Worksheet activity applying the Big Ideas to:
Face detection on phones
A biological intelligence example
Another AI system
Resources: Big Ideas Poster
Areas where AI is Used
Short discussion on major AI application areas (e.g., vision, language, recommendation systems, robotics).
Worksheet Activity: Connecting AI areas to CSE courses.
Submission
Upload a PDF of the completed worksheet to Gradescope under
In-Class β Week 1 Thursday
Week 2ΒΆ
π¬ Discussion: Mon, Jan 13
Overview
Weβll go over DataHub and a Python review.
Download the Python Review Notebook.
π In-Class: Tue, Jan 13
Worksheet
In-Class Activities
The Imitation Game (Turing, Sections 1β5)
Individual reflection followed by small-group discussion on what the Imitation Game captures about intelligence and what it leaves unresolved.Learning Machines (Turing, Section 7)
Read and discuss different parts of Turingβs argument about learning machines, then explain your section to your group.
Engineered vs. Learned Intelligence
Work in small groups to classify AI systems as engineered or learned and justify your reasoning.What Is Required for Learned Intelligence Reflect individually on what a system needs in order to learn, then contribute your ideas to a shared class list.
Submission
Upload a PDF of the completed worksheet to Gradescope under
In-Class β Week 2 Tuesday
π In-Class: Thu, Jan 15
Worksheet
In-Class Activities
Engineered vs. Learned Intelligence
Work in small groups to classify AI systems as engineered or learned and justify your reasoning.What Is Required for Learned Intelligence Reflect individually on what a system needs in order to learn, then contribute your ideas to a shared class list.
Machine Learning Pipeline Build a high-level machine learning pipeline, discuss the role of each stage, and reason about why learning systems are iterative.
Learning Paradigms Identify whether example systems use supervised, unsupervised, or reinforcement learning and explain why.
Designing a Learning System Individually propose a learning system by defining the problem, the type of data or experience needed, the learning paradigm, and what success would look like. (PLEASE SUBMIT THIS AS HW2)
Submission
Upload a PDF of the completed worksheet to Gradescope under
In-Class β Week 2 Thursday
π Week 2 Reflection β Due: Sun, Jan 18, 11:59 PM PT
Please complete the weekly reflection survey by Sunday - It should only take a minute.
Week 3ΒΆ
π In-Class: Tue, Jan 20
Log in to DataHub using your UCSD account. Then click on the worksheet link below - it should directly open the worksheet in DataHub.
Worksheet
Open on DataHub directly: Worksheet 5
If the DataHub link does not work, download the notebook from GitHub and upload it to DataHub.
π In-Class: Thu, Jan 22
Quick Poll
Please complete this short poll at the start of class: Poll Link
In todayβs class we will:
Continue reviewing Worksheet 5 and finish the final exercise.
Review the material we have covered so far.
Address any specific topics you would like to revisit and work through a few sample questions together.
Worksheet
Open on DataHub directly: Worksheet 5
If the DataHub link does not work, download the notebook from GitHub and upload it to DataHub.
Submission
Upload a PDF of the completed worksheet to Gradescope under
In-Class β Week 3 ThursdayTo receive credit, your submission must include an attempted solution for
Exercise: Brute-Force Search for Celsius to Fahrenheit.
Test 1 Prep:
Please review the Test 1 preparation notes and let us know if you have any questions or clarifications.
We will work thruogh the Practice Set 1 on prairielearn.
π Week 3 Reflection β Due: Sun, Jan 25, 11:59 PM PT
Please complete the weekly reflection survey by Sunday - It should only take a minute.