Rajendra

I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing ...

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I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing

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Making sense of data

By Rajendra |Email | Nov 20, 2017 | 5328 Views

There is no better time to study data science than now

"Data! Data! Data! I can't make bricks without clay," exclaims Sherlock Holmes, in Sir Arthur Conan Doyle's The Adventure of the Copper Beeches (1892).

Given that data was held in such high regard even in the late 19th century, it is no surprise that this would be the case in the age of Internet and information overload. In fact, simply having data will no longer cut it; you need to know how to interpret it and how to derive actionable insights from it.

While data has been piling up for as long as cheap storage has been available, the number of people with skills to make sense of it has not been growing at a comparable pace. This talent gap is more conspicuous in North America. Canada's Big Data Consortium, in October 2015, published a white paper entitled Closing Canada's Big Data Talent Gap. For positions like chief data officer, data scientist and data solutions architect, they found a gap of 10,500 to 19,000, and a supply-demand difference of 150,000 for roles like business manager and business analyst.

This could be due to the limited number of education options for those who want to launch a career in data science. The field is highly inter-disciplinary, lying at the intersection of statistics, mathematics, and computer science; and studying just one of these disciplines cannot entirely prepare you for a subsequent data science career. There are, however, up and coming options.

Focused courses

Simon Fraser University (SFU) and the University of British Columbia (UBC) are one of the few universities in Canada, and likely the only two in the Western provinces, to offer out-and-out data science degree programmes. Both are industry, rather than research-oriented.

While UBC offers a 10-month accelerated programme, SFU's is a 16 to 20-month course, which includes a semester (or more) of work through a co-op placement. The Master of Data Science programme is at UBC's Point Grey campus, about 30 minutes away from downtown Vancouver, and SFU's Burnaby campus (east of Vancouver) houses the Professional Master's in Big Data.

Milad Maymay, Director, Student Management and Programme Operations - Master of Data Science, UBC, says that their programme emphasises on short-term commitment for long-term gain: "The shorter time-frame helps students enter the job market sooner and begin building their careers. The condensed one-credit courses let you learn in a focused way by covering a limited set of topics in-depth."

Pre-requisites to apply, include a four-year bachelor's degree in any discipline, even from the arts or business. But there are some mandatory courses you should have completed - at least one undergraduate-level course each in programming, probability or statistics, and calculus or linear algebra. While prior work experience is recommended, it isn't necessary.

Through a capstone project, students work with real-world datasets from across domains to prepare for the industry. "Our first cohort graduated in July 2017. Out of the 19 graduates, 18 have reported having found employment within four months of graduation including three international students," shares Milad.

Tuition fees for this programme are around CAD 42,436 for international students. "A $5,000 entrance scholarship is offered annually to an international student in this programme. The scholarship recognises a student who has demonstrated academic and leadership achievements in their undergraduate or graduate programme, field or industry," says Milad.

For SFU's programme, students need to have a bachelor's degree (first class or first division) in computer science or a related discipline. And again, while work experience isn't a strict requirement, it helps, since most admitted students have worked at least two years in an allied field. "Successful applicants normally have high marks from a well-respected university, can code in Java and Python, and have taken intermediate courses in data structures and algorithms, databases, and operating systems," says Mohamed Hefeeda, Program Director.

He adds, "SFU's master's programme develops full-stack data scientists who can not only gather insights from data but also engineer collection and storage solutions, process, clean and transform massive data, employ machine learning algorithms and statistical methods, as well as visualise the data and operationalise decision-making."

Tuition for this programme comes to about CAD 38,220 for 16 months. Since it is a professional programme, there is no funding, but students will be paid for the co-op placement. In fact, most graduates go on to accept full-time offers from their co-op employers, finding work at companies like Amazon, Hootsuite, Tableau, SAP, Royal Bank of Canada, and Scotiabank.

Experiences

Ruturaj Patel, a second-year student, completed a co-op with the Royal Bank of Canada and got the opportunity to participate in various hackathons during his time at SFU so far, thus gaining valuable practical experience. But he does urge potential applicants to be prepared to put in their own work: "This programme gets more competitive with each passing year, so I would advise anyone applying to prepare in advance for topics like machine learning."

First-year students, Anindita Saha and Supreet Takkar, too, echo his thoughts. "The coursework is quite intensive. Also, the way things take place here is quite different from India. You can't just google the answers to projects and assignments. I personally feel that it is a very good approach, as it prepares you well for the industry. Some of us have already landed co-op offers," says Anindita.

Supreet adds: "You need to be on your toes and ready to accept challenges. For a lot of us, the concepts are new and we invest time to go through other video lectures and online material. I've made friends who help me when I'm stuck and everybody is so nice. That said, there is a definite pressure and competition. Everybody wants to get a co-op quickly. But the co-op coordinators help a lot in that regard. Cover letter, resume and interview sessions run side-by-side with classes."

Besides making the most of the academic and career opportunities on campus, the students also get to experience campus life, and the personal growth that comes with living away from home:

"Hold on to your positivity and team up with people who bring the ??happy vibe' into your life. Learn to cook and clean - it'll come handy. Also, learn to manage money and multi-task," says Supreet Takkar, first-year student. On the beauty of campus living, Anindita Saha, another first-year student, adds, "I have thoroughly enjoyed the fall colours, the first snowfall of the year and the chilly morning weather. At times, the campus looks so beautiful that I feel that it is right out of a fairytale!"

Source: The Hindu