What to do after basic programming (Think Python)

[Headacheguy]

I had finished Think Python, an introductory book on programming using python.

I'm a physics major. So I'd probably need simulations and computational skills. I tried searching Google for intermediate python books, found nothing.

Any suggestions on how to proceed?

 

[Timo]

Learning physics seems like the obvious idea to me. At least up to the point where you get an idea what you need "simulations and computational skills" for.

 

[bcbwilla]

I'd recommend taking courses or self study in numerical analysis.

 

[robphy]

Some suggestions...

https://www.amazon.com/dp/3540294155/?tag=pfamazon01-20

https://www.amazon.com/dp/3642183654/?tag=pfamazon01-20 (I haven't seen this one yet)

https://www.amazon.com/dp/0521191327/?tag=pfamazon01-20

http://vpython.org/
http://www.phy.uct.ac.za/courses/phy1004w/2012/index.html

http://www.physics.orst.edu/~rubin/Books/eBookWorking/index.html

 

[LudusRex]

Congratulations on completing Think Python! As a scientist, it is important to have strong programming skills in order to conduct simulations and analyze data. There are many resources available for intermediate level python programming, including online courses, books, and tutorials. Some suggestions for further learning and development in this area include:

1. Online courses: Platforms like Coursera, edX, and Udemy offer a wide range of courses on intermediate python programming, specifically tailored for scientists and researchers. These courses often cover topics such as data analysis, scientific computing, and simulation techniques.

2. Books: There are many books available on intermediate python programming for scientists, such as "Python for Data Analysis" by Wes McKinney and "Scientific Computing with Python" by Claus Führer, Jan Erik Solem, and Olivier Verdier. These books provide a deep dive into the use of python for scientific applications.

3. Tutorials and online resources: Websites like Real Python and DataCamp offer tutorials and resources specifically for scientists and researchers looking to improve their python skills. These resources often include hands-on exercises and real-world examples.

In addition to these resources, it may also be helpful to connect with other scientists and researchers who have experience in using python for simulations and data analysis. They may be able to provide guidance and share their own experiences and techniques. Overall, keep practicing and exploring different applications of python in your field to continue building your skills and knowledge. Best of luck in your programming journey!