This course represents our fourth at Noroff and the first with some real practical challenges that are sure to relate to what we will face in the real world. Learning to code was an initial idea I dismissed whilst trying to solve an issue in an old job. It was daunting but now after playing around with a few tools and devouring lectures and books on the subject (in a general sense) I can say my enthusiasm isn’t just genuine but also well considered in the understanding of what it should mean. For me learning to code, learning to manipulate data and becoming a data scientist is about learning to think more logically, to think things through more and not just dive in and rely on intuition. To me learning to code is vital if you really want to understand how much of the world works at a deeper level as software touches every single domain. Despite the hyperbole, I still feel like the skill is undervalued and like maths it certainly isn’t for everyone. Silicon Valley entrepreneur Naval Ravikant says it best:

Code is power. It is the new literacy. The personal computer is the most powerful tool ever invented by mankind since maybe the fire or the stone axe. And I would put it above the steam engine. I would put it above flight. I would put it above cars. I would put it above electricity. The reason is that all those other things were group efforts. You needed somebody else’s permission to use those tools. Even the printing press. No individual could run the printing press on their own. Or you would have publishers in the way. The personal computer and the internet are the first time since the invention of fire or the stone axe where you can do it all by yourself with nobody else’s permission.” — Naval Ravikant

My first baby steps into coding were to dabble unsuccessfully with some CSS on a WordPress website. This led me to spending time attempting tasks on Free Code Camp and code academy. Since then I’ve used a bootstrap template to create my blog/portfolio site at using the VS code editor. The most relevant experience I have for this course was a Udemy Python course by Jose Portilla. It was really helpful to code along with an example repo from Github and see him work on screen. After this I was emboldened to play around a little with the NLP (natural language processing) toolkit using the standard Stanford corpus, due to an interest in chatbots. There are so many helpful people in the world of coding but it means there are too many distracting and contradictory pieces of information out there. With this course I look forward to having a central reference point for progress.

Completing day ones tasks was very similar to what I’ve done before so I had no problems. I had to make sure there was no conflict with the older version of Python I had installed and the Conda Navigator setup I have for running Juptyr Notebooks. I found PyCharm intuitive after using VScode before. I’ve also setup the three recommended books in a second browser tab as they are all PDF’s and look forward to reading through them.

Seven weeks is a tricky time frame to judge expectations. A two week course is clearly too short for anything more than some fundamentals whilst typical coding bootcamps that cost thousands of dollars and promise employment last only twelve. So in seven I think a lot can be achieved. What appeals to me about coding is the physical output from prototype to concept, there is something to show for your efforts. I’d love to master some of the fundamentals before Christmas rolls around.Pictured below are three books I bought for the degree in general. I guess I hope to have a much clearer understanding of them once I’ve been through this class,.


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