CH410/510 Scientific Computing¶

Overview¶

The class will meet Monday and Wednesday at 9 am 1 hr, and then Friday at 9 am for 2 hr.
All classwork will be done remotely. Details are here.
Details regarding grading and course policies are in the syllabus.

Getting help¶

Python reference and links to helpful material

Office hours:¶

Check slack #general channel for zoom links to office hours.

Anneliese: 4 pm on Mondays
Luis: 5 pm on Mondays and 4 or 6 pm on Tuesdays
Michael: 2 pm on Wednesdays
Joseph: 2 pm on Thursdays
Mike: 1 pm on Fridays

Getting set up:¶

To get your environment set up, please follow these instructions.
To test your environment, please try to run this jupyter notebook (right-click to save onto your computer.)

Schedule and course materials¶

Warning: Future dates and material may be subject to (minor) change.

In general, Mon and Wed will be instruction days where we cover new programming material. Fri will be an open “lab” where you will work on exercises in groups.

Date	Topic
3/30	Introduction. Configuring jupyter and python Postclass: Class 1: Introduction
4/1	The jupyter notebook. Python as a calculator. Due: Configure Environment; Take the Initial Survey if you haven’t. Preclass: test notebook; Inductive 02: Python as a calculator Postclass: Class 2: Python as a Calculator
4/3	Conditionals and loops Preclass: Inductive 03: Conditionals; Inductive 04: Loops Postclass: Class 3: Conditionals and Loops
4/6	Lists Preclass: Inductive 05: Lists Postclass: Class 4: Lists
4/8	Numpy arrays Preclass: Inductive 06: numpy arrays Postclass: Class 5: Numpy Arrays
4/10	Tuples, dicts, and strings; functions Preclass: Inductive 07: Tuples; Dicts and Strings; Inductive 08: Functions Postclass: Class 6: Tuples; Stings; Dicts and Functions
4/13	Pandas data frames Due: Lab 00.0: Python Practice Preclass: Inductive 09: pandas DataFrames Postclass: Class 7: Pandas DataFrames; Lab 00.0: Python Practice Key
4/15	Graphing and matplotlib Preclass: Inductive 10: Graphing in matplotlib Postclass: Class 8: Matplotlib
4/17	Lab: programming puzzles Preclass: Lab 00.1: Programming Puzzles Postclass: Class 9: Python Puzzles Lab
4/20	Simulation Preclass: Chapter 1: Simulation Postclass: Class 10: Random numbers in python
4/22	Simulation Due: Lab 00.1: Programming Puzzles Postclass: Class 11: Stats in python; Lab 00.1: Programming Puzzles Key
4/24	Lab: simulating an experiment. Preclass: Lab 01: Simulation
4/27	Fitting models to data Preclass: Chapter 2: Regression Postclass: Class 13: Model Fitting I
4/29	Fitting models to data Due: Lab 01: Simulation Postclass: Class 14: Model Fitting II; Lab 01: Simulations Key
5/1	Lab: fitting models to data Preclass: Lab 02: Regression Postclass: Class 15: Model Fitting Lab
5/4	Intro to machine learning Preclass: Chapter 4: Machine Learning Lite Postclass: Class 16: Intro to machine learning
5/6	Classification with machine learning Due: Lab 02: Regression Postclass: Class 17: Introduction to PCA; Lab 02: Regression Key
5/8	Lab: classification using machine learning Due: Prospectus Preclass: Lab 04: Machine Learning Postclass: Class 18: PCA lab
5/11	Molecular structures Preclass: Chapter 3: Dealing with Files Postclass: Class 19: Dealing with files in python
5/13	Molecular structures Due: Lab 04: Machine Learning Postclass: Class 20: Practicum: parsing a pdb file; Lab 04: Machine Learning Key
5/15	Lab: calculating structural properties Preclass: Lab 03: Small files Postclass: Class 21: Processing pdb file lab
5/18	Big(ish) data Preclass: Chapter 5: Big Files (HTS) Postclass: Class 22: Introduction to parsing big files
5/20	Big(ish) data Due: Lab 03: Small files Postclass: Class 23: Parsing big files class 2; Lab 03: Small files Key
5/22	Lab: analyzing HTS data Preclass: Lab 05: Big Files (HTS) Postclass: Class 24: fastq file lab
5/25	Memorial day, no class
5/27	Working with images Due: Lab 05: Big Files (HTS) Preclass: Chapter 6: Image Analysis Postclass: Class 25: Working with images I; Lab 05: Big Files (HTS) Key
5/29	Working with images, start lab Preclass: Lab 06: Image Processing Postclass: Class 26: Working with images II and start Lab
6/1	Finish lab: analyzing microscopy images Preclass: Lab 06: Image Processing Postclass: Class 27: Finish images lab
6/3	Final project, in-class work
6/5	Final project, in-class work Due: Lab 06: Image Processing Postclass: Lab 06: Image Processing Key
6/9	Final project due Due: Final Project