Dear Microsoft, I’m confused.

Last year I heard about your Professional Program for Data Science.

I’ve been following along, albeit slowly, as I’ve been supplementing your content with other MOOCs. But the point is I’ve been following along and still intend to.

Your content is good. Not the best, but good.

Here’s the thing though: Why suddenly announce Microsoft Advanced Analytics?

On the surface it looks all shiny and new with the focus on Cortana Intelligence and Machine Learning.

Looking under the hood though, I see the course catalog and certifications mirror those of the original program.

What gives?

Are these two different, or the same? Are they meant to be complementary? Where does one stop and the other begin?

SO. MANY. QUESTIONS.

Microsoft DAT208x: Introduction to Python for Data Science, a review

In my quest to complete the Microsoft Professional Program for Data Science, I took their course Introduction to Python for Data Science earlier this month to disappointing results.

It could be that I had very different expectations, or that I already have too much background in Python for another introductory course, but I wasn’t impressed and I’m loath to pay for the verified certificate.

This felt more like an overview than a proper introduction. If this was a university, this would have been the first day when the instructor gives out the syllabus and walks through the course expectations.

Would I discourage you from taking the course? Yes actually.

(To follow my progress on the program, check out the Microsoft Professional Program tag)

 

The Structure

DAT208x claims to “cover Python basics and prepare you to undertake data analysis using Python”. Similar to the Microsoft courses that come before it, it is a self-paced course comprised of video lectures and lab exercises.

The modules are as follows:

  1. Python Basics
  2. Lists
  3. Functions and Packages
  4. Numpy
  5. Plotting with Matplotlib
  6. Control Flow and Pandas

This course is brought to you by a partnership between Microsoft and Data Camp, the latter an online Data Science school similar to DataQuest. In an old post I mentioned my apprehension with Data Camp as I’ve heard they favor R over Python, but I decided to give them the benefit of the doubt and give their Python course a try.

Its due to this partnership that most of the lab activities are outside of edX. i.e., we’re redirected to DataCamp’s interface for the lab exercises.

These exercises are the meat of the course. If you’ve tried DataQuest before then the DataCamp interface should be familiar:

Instructions are to the left, interactive Python shell to the right. After submitting your answer DataCamp verifies if your code is correct.

Unlike other Microsoft courses I’ve tried, this one has a final exam. In this exam you are given 4 hours to answer 50 questions: a mixture of knowledge checks, pseudo coding, and actual coding.

Considering the quizzes, exercises, and final exam, you need to score at least 70% to pass the course. Pretty easy considering 40% is just course surveys.

 

Continue reading “Microsoft DAT208x: Introduction to Python for Data Science, a review”

Udacity CS101: Intro to Computer Science, a review

I’ve been trying to learn how to code in Python for a while now. Of all the beginner resources I’ve tried, Udacity’s Intro to Computer Science (UD CS101) has been my favorite.

To clarify: I’m not learning Python with the intention of becoming a software developer. Rather, I like analyzing data, and I hear Python can help with that. R too, but Python is 1: recommended for beginners, and 2: has more applications outside of big data.

I do have some programming experience, though never anything formal, never to this depth, and never in Python.

 

THE STRUCTURE

UD CS101’s premise is for you to create “The Next Google” by teaching you how to build your own search engine.

The self-paced course is broken down into 7 modules*. Each module introduces a new concept to help improve on your search engine.

Each module contains:

  • Videos. Here the instructor explains the theory behind the concepts and demonstrates how to use them on the search engine.
  • Q&As. These help nail down the concepts. These aren’t too difficult and are usually similar to the demonstrations.
  • Problem sets. These are machine problems that build on the concepts you’ve learned so far and are more challenging than the Q&As.

At the end of the course you would have built a search engine with a similar algorithm to AltaVista–what was once the #1 search engine in the 90s before Google took over.

For your class project you then build a mini social network based on the concepts you learned from the course.

*As of writing Udacity has revamped their classrooms so this modular approach may no longer apply.

 

Continue reading “Udacity CS101: Intro to Computer Science, a review”

How to file for a lost Philippine passport in 10 steps

Earlier this year I had to file for a lost passport. The loss was stressful enough by itself, but was made worse because I couldn’t find much information about it. I was lost on how to file for loss!

So I called up their main office and got a list of initial requirements: Affidavit of loss and Police report.

The specifics, and the rest, I figured out along the way.

I’ve written down my experience here, step by step, in the hopes that it would make things a bit easier for anyone who experiences this loss.

1. File an affidavit of loss.

  • In your affidavit, write a detailed explanation of when, where, and how the passport got lost. Here’s a sample template I found online. If you can, best to have a lawyer write it for you.
  • Make 3 copies of the original.
  • Have all four (original + 3 copies) notarized. Technically you’ll only need 3, but you might accidentally mix them up so I say play it safe and notarize everything.

2. File for a police report.

  • Go to the police station nearest where you lost your passport and file a police report.
    TIP: Only investigators can write the report, and not all police stations have an investigation unit. If your first police station doesn’t have one, ask them to redirect you to the right station (usually the bigger ones).
  • To save you the trouble of explaining yourself to the investigator, hand them a copy of your affidavit of loss. They can then base their police report off the affidavit, ensuring all the facts are consistent across both documents. They’ll need to keep the copy though, which is why I said you’ll “technically” only need to notarize three.
  • Thank your police officers! I read in another blog post that they had to pay a P50 fee, but our officers told us this kind of service doesn’t need payment.
  • Make a copy. Or two. The extra copies weren’t needed from my experience, but you know, just in case.

3. Go to the DFA main office

  • In Aseana Business Park in Parañaque. Not along Roxas Boulevard.
  • And no, they don’t process lost passports in satellite offices (I asked).
  • Ensure you have the documents from #s 1 and 2. Optionally, bring a copy of the first page of your lost passport if you have one (I did) and your birth certificate (I didn’t).
  • You do NOT need an appointment. Just go right up to the entrance, tell the guard you’re filing for a lost passport. He’ll ask you if you have the above documents, then direct you to the information counter.
  • At the information counter, they’ll request for documents #1 and #2 again. They’ll arrange your documents, and hand you a passport application form tagged for lost passport. You then proceed to a different room for processing.
  • You don’t have to fill up the form now, but I did so anyway.

Continue reading “How to file for a lost Philippine passport in 10 steps”

Storytelling with Data: a book review and my takeaways

As a child, I loved telling stories. I’d take my favorite book and TV characters and create a world where they would oh-so-conveniently meet. Say, a magical anime girl wanders Narnia until she encounters the now-villainous Power Rangers.

As an adult in the corporate world, I still want to tell stories. But now I find that people are more critical of which stories I tell them.

It must be in the form of numbers, they said.

It’s a data-driven world, they said.

In Cole Nussbaumer Knaflic’s book Storytelling with Data, she argues we can do just that: tell stories with numbers.

language + math = data storytelling

She takes traditional storytelling concepts then re-interprets them for “adult-appropriate” tables and charts. She teaches us to edit our charts, the same way authors do their stories, by borrowing principles of visual design.

My key takeaways from the book can be found below (click for larger size), but they can be summarized as follows:

  1. Context is king. The form your data will take depends on your audience and what you want them to do with the data.
  2. Choose the right graph to best express the key message (I’ve made a flowchart in my notes to help with that).
  3. Following on #1, design around this message.
  4. Present your data as you would a story, with a beginning, middle, and end.
storytellingwithdata1
“Storytelling with Data” notes, by dannaisadork

P.S. Sorry about the terrible handwriting. My normal penmanship’s already pretty bad, but writing on a tablet made it worse!

 

Continue reading “Storytelling with Data: a book review and my takeaways”