Python is a general-purpose programming language that is becoming ever more popular for data science. In our hands-on Introduction to Python course, you will learn about powerful tools to store and manipulate data, and to begin conducting your own analyses. You will harness the power of such data structures as lists, sets, dictionaries, and tuples to store collections of related data. You will write your own custom functions and scripts, and handle errors. Lastly, you will learn to find and use modules in the Python Standard Library and numerous third-party libraries for data processing and visualization.
Prerequisite:
- No previous experience required
- Access to computer/laptop
Instructors:
Alex Razoumov, Visualization & Training Coordinator, WestGrid
Marie-Helene Burle, Research Computing Training Assistant, WestGrid
Format:
- This is a hands-on learning experience
- Any material will be provided to you with more details sent to you once registered and closer to the session date
- There will be breaks scheduled during the session with 1 hour lunch break
- Q&A will be available at the end of the each session
You will learn:
- The fundamental design cycle of computer science and computer programming: writing code, executing it, interpreting the results, and revising the code syntax based on the outcomes.
- Usage of the fundamental atoms of programming: variables, mathematical operators, logical operators, and boolean arithmetic.
- Control structures for developing dynamic programs, including Python libraries: conditionals, loops, functions, and error handling.
- The core data structures for creating useful Python programs: strings, lists, dictionaries, and file manipulation.
- Plotting with matplotlib or plotly libraries (your choice), and a preview of 3D visualization landscape in Python.
- Speeding up your calculations with numpy arrays.
- Working with two-dimensional tables in pandas data frames.
- Working with multidimensional labeled arrays and datasets in xarray, and with modern scientific data formats such as NetCDF and HDF5.
Who should take this course?
This course is suitable for anybody looking to progress quickly with the Python language.