You can be writing useful Python programs by this time next week
If you're reading this, then you know that you need to learn to code to stay relevant in biological research. If you can't code, then you're stuck doing boring analyses by hand, relying on help from busy colleagues, and missing out on postocs and research jobs where programming is a requirement.
You've probably stared at a program that someone else has written, scared to make a change in case you break something, and not really understanding what's going on. You may even have tried, and failed, to learn programming before.
Lots of us in biology think that programming is just too difficult.
But the problem isn't with you. It's with the way you're trying to learn. Yes, there are a million tutorials and examples online - but they're written for people who are already programmers and computer scientists, solving problems that you've never heard of and don't care about.
Programming is not some form of magic that only wizards can do. It's just another tool, like the ones you use every day in your research. And if you can find the right way to learn it, it will transform your research and your career.
Need to run the same analysis on a hundred different datasets? No problem. Got a ton of data sitting in a big ugly spreadsheet and no tool to deal with it? Write your own. Want to change an analysis half an hour before your lab meeting? Edit your program and let the computer do its thing.
And when it's time for your next job, no more skimming the listings looking for one that doesn't mention programming.
Learning to code can be slow and frustrating when you rely on whatever random tutorial you can find on the web. Most of the time you don't even understand the examples, and "asking for help" consists of posting a message to stackoverflow and hoping it doesn't get deleted.
The online Python for Biologists course is tailored exactly for people like you. We won't waste time with calculating factorials or learning irrelevant bits of the language. Instead we'll focus with laser-like accuracy on the things that you need to know for biological research. Learning to code will still take a chunk of time - there's no way round that. But you'll actually enjoy spending the time learning something new, rather than staring at error messages. And when you need help, you'll have a real person on the other end of an email address.
For years I've been teaching this course in person, and a classroom course can be a great way to learn. But classroom courses are expensive - even before you factor in travel and accommodation. And the chances that you can find a course on a date to suit you is unlikely. If you've got a project starting next week, it's not much help signing up for a course in six months.
You can sign up for the Python for Biologists online course right now and get your first lesson in your inbox in five minutes. I've taken the core stuff that you need to know, and turned it into a one-week course, starting with the absolute basics. You'll get one email per day for five days, with lessons, exercises, solutions, and help via email if you get stuck with anything.
I've taught this material to thousands of people like you - from PhD students to PI's - with absolutely no previous programming experience. I've yet to find anyone who is incapable of learning to code - you can do this.
Start learning Python today, knowing that the course you're taking has already helped thousands of people advance their projects and careers.
What you'll get
- Complete set-up instructions to help you install Python and all the extra packages you'll need
- Interactive lesson notebooks that you can read and edit as many times as you like
- Code examples which are ready for you to run and modify as the basis for your own programs
- Exercise files with detailed solutions
- Email support in case you run in to any problems
- Instant delivery of your files via email
- No-questions-asked refund if the course turns out not to be right for you
🛒 Click here to buy the complete package now for $169
intro_course.md