Introduction Programming

Introduction

Don't panic

• this is a programming course
• we know that many of you are not too keen on computers (beyond MS Office)
• this will be a gentle introduction to open source software
• it will not become too sophisticated
• it is meant for everyone to understand
• especially, if you never did any programming before

Why this course?

• mainly to teach you to use your computer better
• to be able to use open source ("free") software
• to solve problems together with readable documentation on how you solved it ("reproducible research")
• on this last point, office products like excel score rather badly
• you will use R and python in courses in the years to come

Who teaches this course?

• In 2018-2019 this course is taught by:
  • Santiago Bohorquez Correa
  • Jan Boone
  • Mark Klik
  • Misja Mikkers
  • Marius-Lucian Prisacuta
  • Cheyenne Ramada

How do we teach this course?

• on line lectures on Datacamp
• tutorials: with plenty of time to ask questions
  • there are a number of "regular" tutorials and one in the computer lab
  • if you do not have a laptop, attend the tutorial in the computer lab
  • if you do have a laptop, attend your regular tutorial group
  • no need to attend both!
  • we may drop some tutorial groups, so check Blackboard!
• schedule can be found here
• we can track your progress on datacamp
• assignment notebooks to be made before the class
• class notebooks that we do together in class (to allow you to ask questions)

Information about the course

• all information about the course can be found here
• pay attention to:
  • the schedule: explaining when you need to do what
  • the rules for the exam explaining how the exam works and a practice exam

Your grade

There are two separate ways to earn your grade

• regular route:
  • midterm on python
  • end of semester exam on R
• resit
  • exam on python and R combined

You cannot use grades from one route for the other one.

Exam

• for more information see the exam page
  • check the instructions for the exam
  • do not open your exam file after you have finished
  • if you do, your exam will not be graded (even if you did not change anything)
• at the exam you can freely copy and paste from the assignments we did in class
• we will not post answers to the assignments
• make sure you attend the tutorials and pay attention in class!

Datacamp

• you need to sign up for Datacamp!
• for details see the heading Important
• note the deadline for filling in the webform!
• if you miss the deadline, you will have to pay for premium content on Datacamp yourself

Github

• github allows you to store files "in the cloud"
• signing up for github is optional
• if you do sign up, you can ask us questions via the issues page also during the exam

markdown

syntax

• markdown allows you to create structure in a simple way
• examples are:

    # this is a heading


    ## subheading


    * first bullet
    * second bullet

    [link text](actual link, e.g. http://www.etc)

    ![Alt text for image](/path/to/img.jpg "Optional title")

• look on the web for other syntax like footnotes etc.
• equations you can type in latex

latex

• latex is great word processing software
• for now, we only need it to write math
• you can guess what the following will do:

$x^2$, $\beta$, $\sqrt{9}$, $\frac{1}{2}$, $\bar x$

\begin{equation}

a^2 + b^2 = c^2

\end{equation}

• if you need something, just google; e.g. "google latex phi" or "google latex empty set" etc.
• and try it out in the jupyter notebook

Second part of lecture

go to the server and start a jupyter notebook

• link to the server
• address to copy/paste in the google form
• importing the python material
• (this is also the way you will import your exam)
• evaluating cells
• you can choose python/R kernel
• getting help: ? and TAB
• code vs. markdown cell
• type some latex

before you leave

• do the steps under the heading Important