Lecture 1 Computers and programming languages introduction

Lab 1 Basics of python

Lecture 2 Program flow control

Lecture 3 Functions and scripts

Lab 2 Debugging and troubleshooting

Labor day

Lab 3 Using Visual Studio Code IDE

Lab 4 Using Visual Studio Code IDE

Lecture 4 Data reduction and fitting

Lecture 5 Data reduction and fitting practice (AI driven)

Lab 5 Working on homework

Lecture 6 Root finding

Lecture 7 Integration

Lab 6 Integrals and root finding gotchas

Lecture 8 Random numbers

Lecture 9 Monte Carlo integration

Midterm

Lecture 10 AI driven simulation of a colony part 1

Lecture 11 AI driven simulation of a colony part 2

Fall break

Fall break

Fall break

Fall break

Lab 7 AI driven simulation of a colony part 3

Lecture 12 The method which rule them all - Optimization, part 1 combinatorics

Lecture 13 Optimization part 2, smooth functions

Lecture 14 Optimization part 3, noisy problems

Lecture 15 Optimization part 4, demystifying neural networks and AI

Lab 8 Optimization practice

Last day to withdraw

Lecture 16 Solving system of linear equations

Lecture 17 Speeding up calculations

Midterm

Lecture 18 Interpolation (sometimes we do not need AI)

Election day

Lecture 19 Ordinary differential equations part 1

Lab 9 practice

Lecture 20 Ordinary differential equations part 2

Lecture 21 Ordinary differential equations part 3

Lab 10 practice

Lecture 22 Digital Fourier Transform (DFT)

Lecture 23 DFT filters

Lab 11 practice

Remote day

Lecture 24 DFT and convolution

Thanksgiving break

Thanksgiving break

Thanksgiving break

Thanksgiving break

Thanksgiving break

Lecture 25 Quantum Computing

Lab 12 practice

Lecture 26 Secure communication

2pm Final for 1pm section

9am Final for 11am section