Is Data Science For All the New Computer Science For All? (berkeley.edu)

UC Berkeley's fastest-growing class is their introduction to data science. (The Wall Street Journal calls it a combination of computer science and statistics "to mine the growing troves of data on everything from traffic patterns to the habits of social-media users.") But that's only the beginning. UC Berkeley plans to create a new Division of Data Science -- one of their biggest reorganizations in decades -- and this fall they even began offering a major in data science. "The division will enable students and researchers to tackle not just the scientific challenges opened up by pervasive data, but the societal, economic and environmental impacts as well."

"We need to consider the ethical implications of these technologies as they are being developed," says Data 8 instructor David Wagner -- "what does the world look like when decisions are made by algorithms rather than people, and how do we ensure that when we analyze data our decisions reflect not just numbers but the humans behind them?"

Slashdot reader theodp writes: With a reported 1,295 students enrolled this semester, Berkeley's Data 8: The Foundations of Data Science boasts even bigger numbers than Harvard's most popular course, the more traditionally CS-focused CS50, which saw 724 students enroll this Fall....

Berkeley's embrace of Data Science coincidentally comes as Code.org is giving kudos to partners Microsoft, Facebook, Google, and Amazon for helping it convince lawmakers and tens of thousands of educators that more traditional computer science is what's needed for the K-12 masses, including the adoption of a new AP Computer Science program for high school students (an AP CS version of CS50 was funded by Microsoft).

So, is Data Science for All the new Computer Science for All? And, if so, will U.S. schools be looking at a major case of buyer's remorse?

Comments

Capitalism

[Anonymous Coward]

As with all things, education needs to be tied to reality.

Society needs (or wants!) certain things, and the only sustainable and humane way to figure out what society wants, how much of it society wants, and who should be paying for it is Capitalism.

Data science for all? Let those businesses who are seeking data scientists recruit promising folks, and pay for their education in an apprentice-style program. The government has business playing around with this nonsense.

Can't you people see it? It's right in the goddamn summary:

Berkeley's embrace of Data Science coincidentally comes as Code.org is giving kudos to partners Microsoft, Facebook, Google, and Amazon for helping it convince lawmakers and tens of thousands of educators that more traditional computer science is what's needed for the K-12 masses

Government corrupts business, not the other way around. They are just using their deep pockets to pay Big Government to swing its pistol this way and that; there needs to be a Separation of Business and State; there needs to be a Separation of Education and State.

Re: Capitalism

[RhettLivingston]

If that is the case, then it has become to specialized. I switched from computer science to computer engineering mid-program back in the 80s, but both had multiple statistics classes as well as database classes (different but related).

Data Science should be part of the fundamental base for any science or engineering curriculum. It is kind of hard to perform any science or engineering without it.

This just in: computers use math

[xxxJonBoyxxx]

>> Is Data Science For All the New Computer Science?

Sure, change the name if it helps you attract funding and place graduates. I've been doing what we currently call "big data" or "data science" since the mid-nineties...and that was with a comp sci degree...issued by a math department.

Re:This just in: computers use math

[ShanghaiBill]

Sure, change the name if it helps you attract funding and place graduates.

Exactly. UC is getting less and less of its funding from the state, and more from tuition. So they need to run the university like a business. If the applying students (customers) want data science degrees, then that is what you sell to them.

If the students learn skills that businesses want, everyone is happy, and it doesn't really matter what the degree is called.

Splitting of diciplines.

[jellomizer]

Computer Science is an Area of Discipline that was an offshoot of Mathematics. So Computer Science was made as a discipline, which is lighter on Mathematics, then a full Math Major, however more focus on Computational and algorithm design. A Computer Science is a Math Light Degree, but it isn't a light degree, just different topics. So Data Science, is an off shoot of computer science, as it allows more for data analysis and less on algorithms.
So me as a Computer Scientist, I do a lot of data analysis, but it is a learned form experience skill more them a taught skill. Just as the generation before me, who had Math Degrees, became Computer Scientists not because it was taught in school at such degree, but because of work experience got them good at such job.

Re:Splitting of diciplines.

[garcia]

Data Science is more than the math-heavy side of CS; it should include a lot of business courses too as the single most important part of being a Data Scientist is understanding the business context of the models being built.

Business Analytics courses try to make a Business-heavy Data Science program; however, there can be balance there, IMO.

I have worked in the field (Data Engineering/ETL focus) for a decade and watched the massive changes in tools, need and understanding. These sorts of programs are doing a great job but still need to do more, based on what Iâ(TM)ve seen to date.

Re:Splitting of diciplines.

[AHuxley]

The US is still going to need a really great math education system.
Calling it Data Science still results in the need for math. Sooner or later the students will have to learn a lot more advanced math.
People who entered on merit will do well as they know how to study and can learn more math.
People who got selected on considerations other that the ability to study math will have a lot of math to do.

If it's a trendy major it's already too late

[Hognoxious]

Four years from now the alumni of these courses will be able to take data about the number of college courses, the number of graduates emerging therefrom, the number of jobs available and the salaries offered and spot some really interesting patterns.

Because one thing's for sure - they'll have the time.

Re:If it's a trendy major it's already too late

[SaBumNim]

It's not trendy because it sounds cool. It's trendy because it's a tremendous need. Touchpoints for data are going to grow exponentially as we have an Internet of more things. We're only at the beginning of the amount of data we're going to store and have available to analyze. We have a long way to go before we make good, data driven decisions in even everyday cases (Daylight Savings Time, anyone).

Re:If it's a trendy major it's already too late

[Hognoxious]

Is that mathematical exponentially or journalistic exponentially?

Will these students be the next ...

[WoodstockJeff]

... group of employees to complain that their hard work is being used for evil government surveillance and hold walk-outs to protest their work being used for evil purposes, other than marketing?

The basics

[Tablizer]

Logic, set theory, factoring patterns/relationships to remove repetition, and statistics should be among the basics. Specific languages often get one mired down in syntax and symbols. Save that for later.

Re:Berkeley, eh?

[Brett Buck]

Or identify speakers to run off campus with a riot, in the cause of "free speech"?

Heh... "ethics"

[MikeRT]

How about a basic course in logic, like the people who objected to Amazon's AI resume reviewer preferring men getting taught what "post hoc ergo propter hoc" means.

The only thing that should concern us even more than black box algorithms is knowing that the people above will not rest until the algorithm gives them the expected output. Even if that means effectively demanding "garbage out, no matter the input."

Re:Infomatics is Bullshit

[sfcat]

You keep thinking that. I'll keep collecting my rather large pay cheques for being engaged in machine learning research all day.

Then you aren't doing data science. Data science is applied ML. You are either inventing new algorithms (ML research) or data science (applied ML). Which is it?

Re: data science

[K. S. Kyosuke]

Or science, because it's actually mathematics.

Re:Infomatics is Bullshit

[q_e_t]

Data science and machine learning overlap, but there are elements of data science that are concerned with plain old statistics, rather than machine learning.

Re:Infomatics is Bullshit

[q_e_t]

I am trying to get back into the area after a gap, and it is proving to be tough, even with 20 years of prior experience.

The problem is industry doesn't know what it wants

[Shadow of Eternity]

Every single job I see with the word "data" in the name has some of the most comically excessive and overbroad requirements along with every adjective in the thesaurus for "expert". Positions described as "entry level" demand 5+ years of experience in a half dozen technologies ranging from python and SQL to tensorflow, hadoop, spark, and you have be a ninja, wizard, expert, and rockstar in all of them. As for degrees? That's the most hilarious part. They'll take anything from computer science to economics as long as it's a "highly quantitative field".

Personally I'd rather take someone who proves they understand how to work with noisy and ugly real world data, and tell when the numbers are bullshit, and teach them to code than take someone who knows how to code and try to teach them to grok data.

Called it

[enrique556]

On Slashdot not too long ago, there was some question about whether everyone should be taught programming in school, and I commented that statistics would be far more useful.
Well, here we are, assuming "data science" is just a wanky name for statistics.

Easy

[aglider]

No.

Re: data science

[Hognoxious]

The general rule is that any subject with 'science' in its name will not have much science in it, computer science is an exception

I used to take some courses in the CS department. Never once saw a single test tube, microscope or Bunsen burner.