Deep Learning MOOC

As I have already mentioned, it’s not easy being me. In addition to my already formed nice and balanced ‘curriculum’ I have enrolled in yet another MOOC on Deep Learning, or DLMOOC. It begins in a week’s time, on 20 January and it ends on 21 March. It is another instance of a so-called mechanical MOOC, similar to Python MOOC, and also created by P2PU. This one is for educators. Well, as a person who has already launched two data-expeditions and is totally resolved to keep doing it in the future, I thought it might be a good idea to kind of learn a bit more about education in general. And this seems to be a very nice chance, because this MOOC has already collected more than 600 participants, that is educators from all over the world.

To be honest, I don’t think I’ll be able to be a very valuable contributor in terms of active participation, because I still have to work, learn pre-calculus and data analysis. And yes, we’ll have to launch our next expedition one day too (in spring I hope). But I’m sure I’ll still receive lots of valuable experience. I already have. I do like the communication system of DLMOOC with a G+ community as central platform. Although I’m not sure yet if it is appropriate for data-expeditions. It also has a flexible cooperation mechanism with an option to choose whether the participants want to work in ‘offline’ (friend-to-friend) groups or join into virtual groups. And it’s very interesting to see how it is going to develop and work. I will try to make notes on the way and share them here.

Python MOOC – Week 1

So, a new (the fourth, as far as I understand) sequence of Python Mechanical MOOC officially started a week ago. This week happened to be extremely busy in my case, so I actually had less time for learning than I hoped I would. But thanks to the Codecademy lessons I took some time ago, the first bunch of tasks didn’t contain too much new information for me. But at the same time it contained quite a number of fascinating and revealing details. For one, I found out from this video lecture that some languages allow using false indentation. That is, unlike Python where indentation is the only way to make a script work properly, many other languages use punctuation to separate statements. But indentation is still required by convention to make a programme clearly readable and its semantics more obvious from its structure. So to make people think that the programme does something different from what it really does, some coders may use this false indentation e.g. in Java or C. But not in Python however.

Also, as I think that during these 8 weeks’ period Python is supposed to be my primary learning focus, I decided to take into account some additional Python courses that might provide a better understanding of what’s going on. One of them is Python Programming 101 at P2PU. And actually there’s a lot of additional information there. For instance, there’s a list of Python compatible text editors. What I like best about it is peer reviews of the editors they tried. So I’ll have to save this for the future:

• Geany
• gEdit
• Ninja IDE
• Notepad ++
• PyDev
• PyPE
• Python ToolKit
• pyScripter
• Spyder

But for now I’m using IDLE, because I don’t have enough time to try all of them right now. Although I’ve installed Notepad ++ just in case.

Also I’m looking forward to getting involved in OpenStudy communication, but I haven’t yet, because I’ve been a bit overloaded (like a + operator) with work.

Getting good ideas from peers: Handwritten Python

A really nightmarish thing is learning too many subjects at a time. In my case, it normally results in learning nothing and quitting everything. Which is why having made the first step in the Webcraft course (which is creating a blog and finding some very interesting people) I have to overcome the urge to continue with HTML and get back to my unfinished stuff with Python and data.

But as I expected, following the P2PU people is very helpful, because it’s a source of great ideas. For instance, as I guess from several blog posts, one of the upcoming tasks in the course is writing an HTML code by hand in order to better understand the syntax. Well, at my beginner’s level in Python syntax is one of the worst problems. Unless I learn it, it always becomes some guess work (often rather successful, because tasks are still very simple). Not long ago I realized that surprisingly enough the idea of learning new words and phrases by heart in order to remember them seems to me absolutely obvious and normal when it comes to human languages (I’m currently learning Greek for instance), but it feels really infuriating when it comes to machine languages. While there’s actually not so much difference, only the machine languages must be much easier in terms of vocabulary and syntax.

Now, I really liked the idea of writing a code by hand in order to remember the syntax and I decided to try it with Python. To that end, I used a short simple code from a Codecademy task that I’ve already successfully done. It’s about dictionaries and lists. Well, I tried to reproduce a similar syntactically correct code on paper. It took me 4 attempts to complete it without any mistakes (I hope)! But now I feel a bit more comfortable with it.

Thanks for sharing good ideas, peers.

UPD: Oops. Just noticed one mistake. It should have been “list1” or something like that… not just “list”…

Brave New World

I created this blog for participating in the Webcraft 101 project and also in order to get a closer look at how P2PU functions, how its badge system works and what this is all about.

Now, let me introduce myself. I live in Russia and I work as a journalist and translator. I also used to work as a teacher. I’ve been interested in open/free movements since I learnt about their existence several years ago. I also like P2P communities of different kinds and I’m always curious about how they function. Right now, I am trying to learn some basics of data journalism and, broader, about data science, because this area seems to me extremely exciting. Searching for more information about it led me to Coursera (great courses in Statistics, Python and Data Science), Codecademy (I’m currently learning Python) and School of Data / P2PU projects (I’m a happy member of an online Data Expedition). Which means that right now I’ve got a  brave new world huge complicated area of knowledge ahead and, to my surprise, I find it inspiring, rather than frustrating. So I think finding some peers to share my observations and exchange experience would make it even more inspiring and efficient. And I do hope that this great P2PU initiative works out.

I’m also interested in various approaches to e-learning, especially those open massive distant educational projects. As well as open libraries and generally open knowledge.