Introduction to Python - Data Analysis and Programmin
Date:
16/12/2019 - 20/12/2019
Organised by:
Goldsmiths, University of London
Presenter:
The course is directed by Dr Will Lawrence, who completed his PhD at the department of Electronics and Computer Science at the University of Southampton, and who has a background in psychology. Will has rich experience in delivering training in both Python and R, to diverse audiences.
Level:
Entry (no or almost no prior knowledge)
Contact:
Teemu Toivainen
020 7078 5468
air@gold.ac.uk
Description:
Learn how to manipulate and shape your data, automate process or write bespoke programs on our practical introduction to programming using Python.
Aimed those new to programming, our week-long course aims to give you a hands-on introduction to Python, a general-purpose programming language.
Python can be used for nearly everything and continues to grow in popularity with organisations like NASA, Google, YouTube and the New York Stock Exchange all using it for different things. Through the use of excellent numerical packages, Python can also compete against more statistical and mathematical packages such as R.
Throughout your course, you’ll learn about:
- General introduction to programming
- Programming in Python
- Using the interpreter in iPython
- Writing Python scripts
- Loop and control flow (for-loops, if-statements)
- Data-types: strings, lists and dictionaries
- Using and writing functions
- Functions for scientific programming: Numpy and SciPy
- Finding problems in code
- Data manipulation project using Python
By the end of the course, you’ll be able to write useful programmes, understand more complex Python programmes written by others as well as how to use Python for more advanced data analysis.
Cost:
£750
Website and registration:
https://www.gold.ac.uk/short-courses/introduction-to-python/
Region:
Greater London
Keywords:
Quantitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis, ICT and Software, Research Skills, Communication and Dissemination
Related publications and presentations:
Quantitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis
ICT and Software
Research Skills, Communication and Dissemination