Assignment 1 - Introduction to Python

Assignment 1 - Introduction to Python #

(Assignment due on 10/02/21, at 12:00 GMT)

The purpose of this assignment is to familiarise you with the fundamentals of the Python programming language.

We believe that programming is a skill that is best developed through self-study. For this reason, we will be using a platform called Datacamp, which contains interactive learning materials on Python, and other data science tools.

Datacamp #

You should have already received an invitation (in your Imperial College email address) to join a Datacamp organization called CIVE927129 - Freight Transport (2020-2021) - please follow the link and sign up.

Datacamp is not free, but we have arranged for you to receive a complimentary 6-month subscription - this provides full access to their entire library of data science courses, so feel free to explore their library (once you have completed this assignment first!).

Your assignment #

You should complete the following modules by the 1st of February:

The modules consist of a series of videos and brief coding exercises that you can attempt using an online coding environment provided by Datacamp. You will be told immediately whether your answers are correct.

Please note that Datacamp keeps track of your progression using XP units - you should be able to receive a possible total of 19350 units for these three modules. You will receive fewer units if you request hints or peek at the solutions when attempting the exercises.

Your mark for this assignment will be calculated as follows:

  • 50% of the mark will be awarded for the timely completion of all three modules.
  • 50% of the mark will be awarded based on your total XP units (as a proportion of the possible total of these four modules)

Frequently Asked Questions #

I already know Python, do I have to carry out this assignment? #

Yes. Not only do we want to be consistent in the way that we assess all students, but you might likely have some gaps in your knowledge of the various toolkits that we are going to be using. Through these modules we will ensure that all students all the programming skills that we need for this course.

If you feel very confident about your Python skills, you can skip the videos (mark them as completed) and go straight to the assessments.

Can I complete the Datacamp knowledge tests instead of completing the modules? #

No. When assessing your performance in this assignment, we will only consider the marks that you attained through the assignments.

I am worried that I might answer the questions wrong and I will lose marks. #

Don’t worry - it is fine to answer a few questions wrong, and the lost points from a couple of questions would only amount to less than 0.02% of the marks in this module.

Something went wrong - I don’t think that I signed up correctly. #

The most usual cause for this is if you signed up with your personal email address, instead of the Imperial one. Get in touch with Dr Angeloudis and we will resolve this.





Further study #

We believe that these four 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:

Step 1 - 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.

  1. Python Data Science Toolbox (Part 2)
  2. Introduction to Data Visualization with Matplotlib
  3. Writing efficient Python Code
  4. Manipulating DataFrames with pandas

Step 2 - Further transport analytics #

The following modules will help you extend your knowledge of some theoretical concepts that we covered in this module.

  1. Introduction to Network Analysis in Python
  2. Vizualising Geospatial Data in Python
  3. Intermediate Network Analysis in Python

Step 3 - 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. As the next step in your training, we recommend the following set of modules:

Step 4 - Advanced skills #

You now have received a solid training in the fundamentals of Python and its applications to Transportation and Logistics. If you want to develop additional skills, and depending on your career aspirations, we recommend the following modules: