If you are looking for a powerful programming language, you should learn Python, a language with a simple syntax and a powerful set of libraries.
It is easy for beginners to learn Python and it is widely used in many scientific fields for data exploration.
This workshop is an introduction to the Python programming language and, in particular, is geared toward people who are new to the language and who have relatively little experience with other programming languages. So, for beginners and people with little experience in programming, this course would be an excellent choice.
The content of this workshop is as follows:
Python Overview
- What is Python? (a Brief History of Python)
- Why Choose Python?
- What can you do with Python?
Installing Python
- Install Anaconda Distribution for Python.
- Briefly running Jupyter Notebook.
- Exploring “no install” online options
Running Python Code
- Brief introduction to Text Editors and Full IDEs
- Notebook Environments
- Jupytor notebook
- A quick tour in Jupyter notebook
Python Coding
- Python Object
- Python Data Structure Basics
- Python Comparison Operators
- Python Statements
- Methods and Functions
- A very quick tour in NumPy, Pandas and Matplotlib libraries.
Participants are requested to install Anaconda Distribution for Python in advance (before class). Software is available online.
In case, you have trouble installing, watch the Tutorial video for installing anaconda on Windows:
https://www.youtube.com/watch?v=aN6OVm0mTHo
and Tutorial video for installing anaconda on MacOS:
Lecturers
Mahdi Shafiee Kamalabad
Target audience
Researchers, students, engineers, analysts, programmers who are interested in an introduction to the Python programming language.
For an overview of all our summer school courses offered by the Department of Methodology and Statistics please click here.
Aim of the course
The aim of this course is to provide basic and fundamental knowledge of Python for all who wish to learn the Python programming language such as students, researchers in data science and statistics, system analysts, etc.
Please note that there are no graded activities included in this course. Therefore, we are not able to provide students with a transcript of grades. You will obtain a certificate upon completion of this course.
Costs
- Tuition fee for PhD students from the Faculty of Social and Behavioural Sciences from Utrecht University will be funded by the Graduate School of Social and Behavioural Sciences.
- The tuition fee for staff off the Faculty of Social and Behavioural Sciences from Utrecht University will be funded by FSBS
Utrecht Summer School does not offer scholarships for this course.
Contact details
Irma Reyersen | E: ms.summerschool@uu.nl