CCB Bioinformatics Bootcamp
The Center for Computational Biology offers a 5-day “Introduction to Programming for Bioinformatics” bootcamp. The goals of this course are to introduce students to Python, a simple and powerful programming language that is used for many applications, and to expose them to the practical bioinformatic utility of Python and programming in general.
The course will allow students to apply programming to the problems that they face in the lab and to leave this course with a sufficiently generalized knowledge of programming (and the confidence to read the manuals) that they will be able to apply their skills to whatever projects they happen to be working on. While there are no prior programming experience needed or prerequisites for the course, it would be helpful to have some basic understanding of programming prior to the course. Participants should expect an intense 5 days of learning python.
The next “Introduction to Programming for Bioinformatics” bootcamp will be offered both online and in-person from August 4 - 8, 2025. Click here for more information and how to register for the course.
Please check our FAQ page for any questions you might have.
If you have any further questions, please contact us at ccbadmin@berkeley.edu.
The schedule below shows an approximation of what is covered in the course.
| Day 1 |
Morning: Intro to Google Colab; Python basics – data types, built-in functions Afternoon: Simple data structures, built-in functions & methods, basic logic & control flow |
| Day 2 |
Morning: Review control flow & data structures; intro to NumPy arrays Afternoon: Continuation of NumPy methods & functions: shapeshifting, masking, filtering, etc. |
| Day 3 |
Morning: Review NumPy; intro to data exploration: importing, cleaning Afternoon: Continuation of data exploration: summarizing, visualizing; mini-project
|
| Day 4 |
Morning: Intro to Pandas: compare/contrast with NumPy, parsing data frames Afternoon: Continuation of Pandas: parsing, basic data science, intro to wrap-up project |
| Day 5 |
Morning: Introduction to Machine Learning Afternoon: Introduction to Machine Learning |