CS-EV - Machine Learning with Python, 15.04.2019-15.06.2019

Topic outline

• Coding Assignments
  This course consists of six thematic rounds (see Section "The Six Rounds"). Each round covers a certain part of the course book and includes a coding assignment. The coding assignments require you to complete code snippets within a Python notebook. Such a notebook consists of combinations of textual explanations, mathematical formulas, code snippets and figures generated by the code.
  
  The notebooks for the coding assignments will be made available online using a JupyterHub server. A Jupyterhub server allows you to edit, store and execute Python notebooks via a web browser (such as Firefox or Chrome) and a connection to the Aalto network. In order to connect to the JupyterHub you can use the same username and password as used for logging in to the MyCourses page.
  
  The typical workflow for completing a coding assignment is as follows:
  
  

  1. access the Jupyterhub serve by navigating to https://jupyter.cs.aalto.fi/ using your browser

  2. you should be directed to a login page. Use your Aalto credentials to log in.

  

  3. when the Login was successful you arrive at a course list. Choose "MLPython 2019" from this list and click the button "Spawn". This will request JupyterHub to create a new session (providing a virtual programming  environment) for you. Depending on the load to the server, this might take a few seconds up to some minutes (in case of heavy server load).

  
  

  4. You will be directed to the home view of your programming environment. This home view is a web-based file browser for your programming environment at the Jupyterhub server. 

  5. In order to start working on a particular assignment, select the "Assignments" tab highlighted with red arrow.
  

  
  

  
  

  6. Under the assignment tab, you should see a list of all coding assignments available. In order to start working on a particular assignment you have to click the "Fetch" button next to the assignment. You should then see this assignment being added to the list of "Downloaded assignments"

  
  

  7. After you have fetched an assignment, when you select the "Files" tab, a folder named "mlpython2019" should appear. If not, try to do a "Page Refresh" in your browser. 
  

  
  

  
  

  8. you can open the notebook by clicking on the assignment in the Files tab. 

  
  

  9. After you have completed the coding assignment in a notebook, you can submit the notebook on Jupyterhub. The submission is done via the Assignment tab in your Home view. In this Home view, click "Submit". After clicking the submit button, you should see the notebook listed under "submitted assignments" (see screenshot below) 

  
  

  Submissions can be sent multiple times for a particular coding assignment. Only the latest submission is considered as your submission for the exercise. The submission is considered "late" if your LATEST submission exceeds the round deadline.