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

Lecture 4 Data reduction and fitting (AI driven)

Lab 3 Data reduction and fitting practice (AI driven)

Lecture 5 Root finding

Lecture 6 Integration

Lab 4 Integrals and root finding gotchas

Lecture 7 Random numbers

Lecture 8 Monte Carlo integration

Midterm

Lecture 9 AI driven simulation of a colony part 1

Lecture 10 AI driven simulation of a colony part 2

Lab 5 AI driven simulation of a colony part 3

Lecture 11 The method which rule them all - Optimization, part 1 combinatorics

Lecture 12 Optimization part 2, smooth functions

Fall break

Fall break

Fall break

Fall break

Lecture 13 Optimization part 3, noisy problems

Lecture 14 Optimization part 4, demystifying neural networks and AI

Lab 6 Optimization practice

Lecture 15 Solving system of linear equations

Lecture 16 Speeding up calculations

Midterm

Last day to withdraw

Lecture 17 Interpolation (sometimes we do not need AI)

Lecture 18 Ordinary differential equations part 1

Lab 7 practice

Lecture 19 Ordinary differential equations part 2

Election day

Lecture 20 Ordinary differential equations part 3

Lab 8 practice

Lecture 21 Digital Fourier Transform (DFT)

Lecture 22 DFT filters

Lab 9 practice

Lecture 23 DFT and convolution

Lecture 24 Quantum Computing

Lab 10 practice

Remote day

Lecture 25 Secure communication

Thanksgiving break

Thanksgiving break

Thanksgiving break

Thanksgiving break

Thanksgiving break

Lab 11 Final project in class work

Lab 12 Final project in class work

Lab 13 Final project in class work

2pm Final for 1pm section

9am Final for 11am section