Assignment 1 - Introduction to Python
(Assignment due on 08/11)
In this assignment, we will be covering the fundamentals of the Python programming language.
As programming is a skill that is best developed through self-study, we will use a platform called Datacamp, which provides interactive learning materials for Python and other scientific programming tools.
You should have already received an invitation (in your Imperial College email address) to join a Datacamp organization called CIVE60008 - Transport Systems (21-22).
We have made arrangements for you to receive access to the entire library of Datacamp modules for six months. Feel free to explore further once you complete this assignment.
You should complete the following modules before the assignment deadline:
The modules consist of a series of videos and brief coding exercises, which you can attempt using an online coding environment provided by Datacamp. You will be told immediately whether your answers are correct.
Assessment & Marking
Note that Datacamp keeps track of your progress using XP units - you should be able to receive a possible total of 15700 units for these three modules. You will receive fewer units if you request hints or peek at the solutions.
Your mark for this assignment will be calculated as follows:
- 30% of the mark will be awarded for the timely completion of all three modules.
- 70% of the mark will be awarded based on your total XP units (as a proportion of the possible total of 15,700)
Further study (Optional)
We believe that these three modules, in combination with the tutorials and the assignment exercises, will give you all the Python skills that you need (and more!) as far as this module is concerned.
However, should you want to further develop your Python skills, you might want to have a look at the following courses:
Complete your training on Python fundamentals
The following modules cover a wider set of essential skills that you might need to be familiar with if you want to use Python for your own projects.
- Python Data Science Toolbox (Part 2)
- Introduction to Data Visualization with Matplotlib
- Writing efficient Python Code
Further transport analytics
The following modules will help you extend your knowledge of some theoretical concepts that we covered in this module.
- Introduction to Network Analysis in Python
- Supply Chain Analytics in Python
- Vizualising Geospatial Data in Python
- Intermediate Network Analysis in Python
Learn to work with big datasets
Transport engineering is synonymous with the analysis of vast datasets, which will often require extensive processing before it can be used in your models. The next step in your training would be to learn how to deal with real-world datasets:
You should now have a good command of Python fundamentals. If you would like to expand your skill set, consider completing the following modules: