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Friday, July 31, 2015

Education - the past and the present

Hello everyone, I am here with yet another blog post and this time the topic is rather vast and difficult, if I may say.

So, let me start with this famous quote from Swami Vivekananda - "Education is the manifestation for perfection already in man."

The great philosopher from India assumes that perfection is inherent to mankind and just remains to be realized. This realization is brought about by proper education.

Now, one would think - How different this is from the education an average Indian receives today. Is it just about degrees and diplomas and placements? Where did knowledge go? Without knowledge how self-realization is even possible, let alone perfection.

No, the intent of this article is not to impart philosophical gyan to my esteemed readers. I am aware that most, if not all, of you are immensely knowledgeable, so my humble article does not intend to influence you in any manner.

However, my observation has been - the mode of education is changing thick and fast. I shall try to focus a little bit about education in pre-historic India and then gradually move to modern times.

Prehistoric education [Vedic age - 1500 BC – 500 BC]

We learn from Brittanica that in those days education mainly aimed to "guide children to becoming good members of their tribe or band."
The Brittanica article is immensely informative, so readers are advised to certainly take a look. I shall focus a bit on India here. Well, owing to caste system and division of labor in ancient India, only the brahmins were allowed to study as per Gurukul pratha. [I shall not discuss caste system in this article which has been long abolished in India.]
Gurukul System


Per Brittanica -

The boy would leave his father’s house and enter his preceptor’s ashrama, a home situated amid sylvan surroundings. The acarya would treat him as his own child, give him free education, and not charge anything for his boarding and lodging. The pupil had to tend the sacrificial fires, do the household work of his preceptor, and look after his cattle.
The study at this stage consisted of the recitation of the Vedic mantras (“hymns”) and the auxiliary sciences—phonetics, the rules for the performance of the sacrifices, grammar, astronomy, prosody, and etymology. The character of education, however, differed according to the needs of the caste. For a child of the priestly class, there was a definite syllabus of studies. The trayi-vidya, or the knowledge of the three Vedas—the most ancient of Hindu scriptures—was obligatory for him. During the whole course at school, as at college, the student had to observe brahmacharya—that is, wearing simple dress, living on plain food, using a hard bed, and leading a celibate life.
The period of studentship normally extended to 12 years. For those who wanted to continue their studies, there was no age limit. After finishing their education at an ashrama, they would join a higher centre of learning or a university presided over by a kulapati (a founder of a school of thought). Advanced students would also improve their knowledge by taking part in philosophical discussions at a parisad, or “academy.” Education was not denied to women, but normally girls were instructed at home.
The method of instruction differed according to the nature of the subject. The first duty of the student was to memorize the particular Veda of his school, with special emphasis placed on correct pronunciation. In the study of such literary subjects as law, logic, rituals, and prosody, comprehension played a very important role. A third method was the use of parables, which were employed in the personal spiritual teaching relating to the Upanishads, or conclusion of the Vedas. In higher learning, such as in the teaching of Dharma-shastra (“Righteousness Science”), the most popular and useful method was catechism—the pupil asking questions and the teacher discoursing at length on the topics referred to him. Memorization, however, played the greatest role.


Classical period [4th Century CE - 8th Century CE]


Per Brittanica -
The 500 years from the 4th century ce to the close of the 8th, under the Guptas and Harsha and their successors, is a remarkable period in Indian history. It was the age of the universities of Nalanda and Valabhi and of the rise of Indian sciences, mathematics, and astronomy. The university at Nalanda housed a population of several thousand teachers and students, who were maintained out of the revenues from more than 100 villages. Because of its fame, Nalanda attracted students from abroad, but the admission test was so strict that only two or three out of 10 attained admission. More than 1,500 teachers discussed more than 100 different dissertations every day. These covered the Vedas, logic, grammar, Buddhist and Hindu philosophy (Sankhya, Nyaya, and so on), astronomy, and medicine. Other great centres of Buddhist learning of the post-Gupta era were Vikramashila, Odantapuri, and Jagaddala. The achievements in science were no less significant. Aryabhata in the late 5th century was the greatest mathematician of his age. He introduced the concepts of zero and decimals. Varahamihira of the Gupta age was a profound scholar of all the sciences and arts, from botany to astronomy and from military science to civil engineering. There was also considerable development of the medical sciences. According to contemporaries, more than eight branches of medical science, including surgery and pediatrics, were practiced by the physicians.
These were the main developments in education prior to the Muslim invasions, beginning in the 10th century. Nearly every village had its schoolmaster, who was supported from local contributions. The Hindu schools of learning, known as pathasalas in western India and tol in Bengal, were conducted by Brahman acaryas at their residence. Each imparted instruction in an advanced branch of learning and had a student enrollment of not more than 30. Larger or smaller establishments, specially endowed by rajas and other donors for the promotion of learning, also grew in number. The usual centres of learning were either the king’s capital, such as Kanauj, Dhar, Mithila, or Ujjayini, or a holy place, such as Varanasi, Ayodhya, Kanchi, or Nasik. In addition to Buddhist viharas (monasteries), there sprang up Hindu mathas (monks’ residences) and temple colleges in different parts of the country. There were also agrahara villages, which were given in charity to the colonies of learned Brahmans in order to enable them to discharge their scriptural duties, including teaching. Girls were usually educated at home, and vocational education was imparted through a system of apprenticeship.
Ruins of Nalanda University

*** Please note that the world famous centre of learning Nalanda university was demolished by Bakhtiyar Khilji, a Turkic chieftain around 1200 CE, but thankfully has been re-opened in 2012 with help from international bodies. ***

Now, let me skip the middle portion. Assume that I ride a time machine, have a long journey, a real comfortable sleep and land directly in 2015.

Education today


As per 2012-2013 statistics,
There are 700 degree granting institutions and 35,500 affiliate colleges in India which provide full-time, part-time as well as distance education.



The new trend

Now the trend that I have been noticing is - with the advent of internet, gradually online education is becoming popular. Welcome to virtual education, they say. Now, these do not offer degrees or diplomas. They may or may not even provide certificates. But some salient points about these options are -

  • You study at your own pace, unless there is a homework to submit
  • You receive world-class education from renowned universities from the confines of your home.
  • The credibility of some of these facilitators like EDX, Coursera, Khan Academy, Udemy, Codecademy etc. etc. is gradually being recognized even by various organizations. 
  • Many of the top-notch universities are also providing these programmes directly.
  • You have to go through the drill. The focus is not on memorizing sentences but on grasping concepts and applying them to real-world situations. The knowledge quotient is high.

So, now, dear readers - Did you ever take such a course? Would like to know your experiences and how it helped you in your career.

Conclusion


Education has evolved a lot over the years - specially, the focus and the importance of subjects of study. One thing, that however has remained unchanged is the importance of knowledge and the way students can apply it in real world situations. The evaluation techniques are also evolving with many courses allowing open book tests. The main focus seem to be on skill building and application of skills acquired. The mode is immaterial, more informal and should I say, smart. Even grading techniques have changed a lot. It remains to be seen how this can evolve further. Hopefully, the purpose of education will continue to stay the same - "...to drive the manifestation for perfection already in man. "


PS. The views expressed in this article are my own and may not reflect the thoughts of the organization I work for. All feedback appreciated.




Image sources - 
http://comps.canstockphoto.com/can-stock-photo_csp19320315.jpg
http://thumbs.dreamstime.com/x/class-room-under-banyan-tree-3478088.jpg
https://nalandauniversity.files.wordpress.com/2011/03/nalanda_university.jpg

Monday, July 27, 2015

Big break and big data !

My last article was written well over a year back. So much has transpired since then...

I sometimes sit and wonder how many different things I have been juggling with, in life. I am not even talking about work here.

My current stimulus to blogging comes from the fact that my better half has created a blog of her own, which I honestly believe is awesome. That blog is supposed to be bi-lingual (languages being Bengali and English) and will (probably) focus on history, the subject she did her masters in.

Anyway, so now that I have started to pen this article. I am wondering what to write about. So many things happened within this last one year, that I do not even know where to start and where to end. Micro-blogging and Facebook have taken up more of my time, I would think, the time I used to allocate to my passion for writing.

Let me think for a moment.

I have been thinking about writing a blog based on my learning and work in analytics and the current trends. I believe it will serve as a good exercise for me and a way to gather feedback from my esteemed readers as well.

Machine learning and big data -


Over the past few days, I explored the topics of machine learning. One of the things that I definitely found exciting was the ability for smart systems to learn over time, gather experience and use that experience to make more accurate predictions after adjusting the underlying algorithms. This is smart, almost as smart as a human could get. As long as the initial set up is accurate and thoroughly tested, the end results could be amazing.

So, what is machine learning?
Per Wikipedia,
Machine learning is a subfield of computer science[1] that evolved from the study of pattern recognition and computational learning theory in artificial intelligence.[1] Machine learning explores the construction and study of algorithms that can learnfrom and make predictions on data.[2] Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions,[3]:2 rather than following strictly static program instructions.
I have been exploring some of the popular machine learning technologies in the market today. I checked out BigML the other day. BigML provides a nice user interface where you can create a free basic account, set up a source, create a dataset, create a model and generate predictions. The user interface is really intuitive and you can play with the data even if you do not have vast knowledge in statistics, although, yes a basic knowledge would be expected.

The other technology that I explored was IBM Watson Analytics, floated by the Big blue. Now, this I felt, is huge. Before I go into what I explored about this, take a look at the video from Jeopardy.


IBM Watson participated in this competition, 'his' competitors being the very smart Ken and Brad. However, Watson triumphed.

From the official IBM site, here is what we know about Watson, in brief -
Since its triumph on the television quiz show Jeopardy! IBM has advanced Watson’s capabilities and made it available via the cloud. Watson now powers new consumer and enterprise services in the health care, financial services, retail and education markets.  IBM has also opened the Watson platform to developers and entrepreneurs, enabling them to build and bring to market their own powered by Watson applications for a variety of industries.
So, what I did was I created a basic account on the Watson analytics portal and played a little bit with a sample data set. Although I am not a Watson analytics expert I found it very intuitive and learned new insights about the data. Apart from providing me answers to my own questions, Watson analytics also provided interesting relationship insights between data points. It even allowed me to take a look at the data closely - the quality of the data in the different columns, which ones were good, which ones were not that good, in terms of percentages. So, I was even able to carry out a refinement of the data and that allowed me to get an improved data set which I would again feed into the system and get more accurate insights. I did all of these with a basic account, but I am sure I would have been provided with more options and more detailed capabilities had I had a paid account.
But in summary, did I like it? Yes I did.

I have had an analytics background in the past, having worked with Data Warehousing technologies for well over 9 years and this, I believe, is the next big thing. When you have an intelligent system that is learning from the data and making itself smarter over time, it makes a whole different story than what we have seen in the past. This is the next age - the age of data.

As IBM CEO Ginni Rometty pointed out  -
Data is the globe's next natural resource.
 Data is everywhere. Every keystroke I make. Every phone call. Every mobile text. Every tweet. Every word I say. Everything is data and we call this humongous volume of data as Big Data. How we tap into it to gather insight is the science which we have come to know as "Data Science".

The challenge we have here is to tap into this data in order to gain actionable insights. Every company (well almost every company) today have their own Data Warehouse with capabilities to generate analytics in order to further enhance their footprint on the market. But what next ! Predictive analytics is something that will provide the cutting edge to these organizations.

Take a look at this article on how Google monitors us today. In this age of internet and social networking, one is tempted to go out to the world and make connections, be vocal and every little thing you do is tracked. The advertisements that you see on the gmail sidebar will more likely reflect something related to the last item you searched on Google ! And that is just a tiny example of what Google knows about you. In essence every person browsing the internet and using the hallowed search engine probably has some kind of a profile created - habits, likes, dislikes, beliefs - every little detail that probably even your partner is unaware of. Is that scary? Yes, definitely. Can you do anything about it? Probably not.

Sorry for digressing. So that "Google example" I just gave above is also part of analytics and data and big amount of data or big data.

The fact remains - Yes, data is the next best natural resource and if we know how to churn it well, it can make the world a better place. How?

Could we have predicted the way this gunman opened fire on innocents, yes I am referring to the Louisiana shooting. From the news article it looks like it was a planned out act by the person. If so, how did he plan it? What kind of Internet footprints did he leave? What were his facebook updates or his twitter tweets? What did he message? The police will of course find out everything, but we are working on reactive analytics.

Could we have been proactive? Could we have, based on the real time data, predicted that there was a 80% chance (I just put a number as an example) of this person getting violent and contributing to mass genocide? That is exactly where we wish to do with Big Data, with predictive analytics, with machine learning.

All feedback appreciated.

PS. The views expressed in this article are my own and do not necessarily represent the thoughts of the organization I work for.