Level up with Massive Open Online Courses (MOOC)

Last week I was attending the IDC FutureScape, an annual event where IDC, a leading market research, analysis and advisory firm, shared their top 10 decision imperatives for the 2015 CIO agenda.

The keynote speaker, Sandra Ng, Group Vice President at ICT Practice, went through the slides mentioning the newest technologies and keywords like Big Data and Analytics, Data Science, Internet of Things, Digital Transformation, IT as a service (ITaaS), Cyber Security, DevOps , Application Provisioning and more.

IDC Predictions

Eight years ago when I’ve completed my M.Sc in Computer Science, most of these technologies were either very new or didn’t exist at all. Since the IT landscape is evolving so fast, how can we keep up and stay relevant as IT professionals?

There is obviously the traditional way of registering for an instructor led training, be it PMP, Prince2, advanced .NET or Java, sitting in smaller groups for a couple of days, having a nice lunch and getting a colorful certificate.

But there are other options to access a world-class education.

A massive open online course (MOOC) is an online course aimed at unlimited participation and open access via the web. In addition to traditional course materials such as videos, readings, and problem sets, MOOCs provide interactive user forums that help build a community for students, professors, and teaching assistants (TAs).
http://en.wikipedia.org/wiki/Massive_open_online_course

Are you keen to learn more on how Google cracked house number identification in Street View, achieving more than 98% recognition rates on these blurry images?

StreetviewWhy don’t you join Stanford’s Andrew Ng and his online class of 100,000 students attending his famous Machine Learning course? I took this course two years ago, and this guy is awesome! So awesome that Baidu, the Chinese search engine, just hired him as a chief scientist to open a new artificial intelligence lab in Silicon Valley.

You can also join Stanford’s’ professors, Trevor Hastie and Robert Tibshirani, teaching Statistical Learning, using open source tools and a free version of the text book An Introduction to Statistical Learning, with Applications in R – yup, it’s all free!

There is a huge variety of online classes, from Science to Art to Technology, from top universities like Harvard, Berkeley, Yale and others – Google the name of the university plus “MOOC” and start your journey.

Level Up!

 

 

 

How Individualized Medical Geographic Information Systems and Big Data will Transform Healthcare

The modern healthcare system is experiencing a significant disruptive change consistent with the technological shifts that have altered the communications, publishing, travel, and banking industries. The roots of this transformation can be found across many topics including the Quantified Self movement, mobile technology platforms, wearable computing, and rapid advances in genomic and precision medicine.

Here are some conclusions and thoughts following a seminar held last week at the Institute of Systems Science at the National University of Singapore (NUS).

Dr. Steven Tucker, MD, shared his view of how individualised medical Geographic Information Systems (GIS) will transform medicine:

“This is a medical Geographical Information Systems, compared to a Google map of the individual. We can do this with biology and health”.

Dr. Tucker presenting the medical Geographic Information Systems (GIS)
Dr. Tucker presenting the medical Geographic Information Systems (GIS)

There’s much more to it than just collecting data points from your mobile phone or from a wearable device:

“Your DNA plus your bacteria and your epigenome (a record of the chemical changes to the DNA and histone proteins of an organism) exposures, protein and unique appearance go to making you a unique biological individual. We are not in a standard distribution anymore… That is transformative” said Dr. Tucker.

These singular, individual data and information set up a remarkable and unprecedented opportunity to improve medical treatment and develop preventive strategies to preserve health.

But how is this related to Big Data?

Michael Snyder of Stanford University was one of the first humans to have such a construct made of himself. Snyder had not only gene expression analysed, but also proteomic and metabalomic sequencing as well, as described in Topol’s recent article in Cell, “Individualized Medicine from Prewomb to Tomb” (March 27, 2014).

template_cell

The procedure required one Terabyte of storage for the DNA sequence, two Terabytes for the epigenomic data, and three Terabytes for the microbiome, the article said. Storage requirements grow quickly to one Petaybytes (1,000 Terabytes) for 100 people, so do the math of how many Petabytes of storage are required for storing the individual data of millions of people.

“The longer you can follow a person, the more you’ll learn about their health states, the more you can do to help them stay healthy. That’s the way it should be.” (Michael Snyder, Making It Personal).

Comments, questions?

Let me know.