summaryrefslogtreecommitdiff
diff options
context:
space:
mode:
-rw-r--r--admin/meeting-notes/2025-04-29.md40
1 files changed, 32 insertions, 8 deletions
diff --git a/admin/meeting-notes/2025-04-29.md b/admin/meeting-notes/2025-04-29.md
index 5e8e9b7..97bb99b 100644
--- a/admin/meeting-notes/2025-04-29.md
+++ b/admin/meeting-notes/2025-04-29.md
@@ -1,22 +1,46 @@
## Updates
-- Working on Jupyter Notebooks (/tutorials/notebooks). Module 1 & 2 -> notebooks
-- Writing in .md -> convert to .ipynb & .tex
-- Time
+- Schedule, couple days behind schedule
+- Focused on core content (tutorials)
+- Working on Jupyter Notebooks. Module 1 & 2 -> notebooks
+- Have a compiled pdf / textbook.
+- Workflow: still writing in .md -> convert to .ipynb & .tex
---
## Topics
and questions
-- Course Overview
+- Jupyter Notebooks
+ - Planned for:
+ - Control Structures
+ - Functions
+- Course Overview
+ - Review and discuss potential changes
+ - Error Module
---
## Discussion
+- AI programming tutorial
+ - Types of AI
+ - Language
+ - Vision
+ - Generative
+ - Reinforming
+- AI vs Algorithms
+ - Rubics Cube example of algorithm
+- VCS tutorial -> Github vs. git
---
## Actions
-- [ ] Finish off Jupyter tutorial (.md version)
-- [ ] Finish Module 2
-- [ ] Start Module 3
-- [ ] Work on Jupyter Notebooks & focus on interaction for module 1 \ No newline at end of file
+
+To do:
+
+- Each Tutorial should have two problems (one to work in classroom, one to leave as homework)
+- Intro to algorithm at the beginning of Module 2 (computational algorithm vs. real-world algorithms)
+- Move AI at the end of Module 2
+- AI vs. alorithms
+- AI types (LLM vs. Resconstructive AI vs. Generative AI, Reinforcement AI, Vision AI etc)
+- Then we go into AI applications: AI for code debugging vs AI for code generation based on flowcharts
+- pick a GIT GUI program for next time and see how much we can simplify the discussion on Git and Github
+- Module 3 - bare minimum numerical methods: 1. Equation solvers/Root finding: Newton, Secant Method. 2. Systems of Equations: Gauss Method, LU Decomposition. 3. Integration: Trapezoid Method, Simpson Method. 4. Differentiation/ODEs: Explicit Euler, RK methods, Implicit Euler. \ No newline at end of file