Scientists frequently need to work with data. Working with spreadsheet programs such a Excel quickly reaches its limits for large amounts of data or more complex problems. Programming can help to solves these types of problems in better and more reproducible manner. Python offers many libraries that scientists that can use effectively in their daily work.
This first step should be short evaluation of your prior programming knowledge. You should answer these questions:
What prior programming experience do you have?
What are your objectives for using Python?
Are you already using Python? I yes, what is your level experience?
Depending on your prior programming knowledge, you should attend different courses:
If you have only little or no programming knowledge, the course Python for Non-Programmers would be the best for you.
If don’t have any or only little Python knowledge but you are a regular user of another programming language, the course Python for Programmers serves your needs the best.
If you already use Python on a regular basis and you feel you are proficient in writing good Python programs, you can go straight to the next step.
If you already attended a course of step 2 or are proficient with Python, attending the course Python for Scientists and Engineers would be the next logical step.
If you would like to get deeper into one topics, these courses might be of interest for you:
Depending on your objectives you defined in step 1, you may continue your Python learning journey with step 3 or step 4 of these curricula:
Roadmap for DevOps and SysAdmins (direct link to Step 3)
Roadmap for Testers (direct link to Step 3)
Roadmap for Software Developers (direct link to Step 3)
Roadmap for Web Developers (direct link to Step 3)
Tel: | +49 341 260 3370 |
Fax: | +49 341 520 4495 |
mail: | info@python-academy.de |
Tel: | +49 341 260 3370 |
Fax: | +49 341 520 4495 |
mail: | info@python-academy.de |