For those interested in a practical, hands-on course, we just released one at Kaggle https://www.kaggle.com/learn/overview
Berkeley offers its data science course online for free
71–80 of 164 posts
Re: Berkeley offers its data science course online for free
#72I find it curious that there are so many courses for data-science related subjects, which superficially seem to cover the same material, and relatively few courses covering more traditional CS topics such as computer systems, networks, OS. I suppose it has to do with the market, but also feels like colleges are skating to where the puck is, rather than where it will be (or perhaps, where it could be).
I'm just curious -- where do you think the puck will be? I've had a number of younger acquaintances ask for career advice. Pursuing some kind of data science seems like an obviously smart direction now, but I've wondered if this, as well as traditional CS career paths, may be in danger of becoming over-saturated areas, now that everyone views them as sure paths to a job that pays well.
By its nature data science work is very undefined. There is not yet a widely established design path for data science as there is for software development. The risk for someone starting their career in data science is that they will end up in an organization that doesn't know how to data science. So I'd recommend steering young folk to larger teams that have PhD level Statisticians.
Re: Berkeley offers its data science course online for free
#73Earlier quoted context omitted.
Every graduate that doesn't find a high paying job in the field is an excellent candidate for the next level of education. After you have given a university hundreds of thousands of dollars and a decade-plus of your life, you will then be ready to teach the next crop of students.
> Every graduate that doesn't find a high paying job in the field is an excellent candidate for the next level of education. 1. You really think Berkeley's top-ranked PhD program is recruiting people who couldn't find jobs? No. Not only can 100% of successful top-tier PhD applicants find jobs, 100% of them are strong candidates for the top echelon on entry-level jobs. If you disagree, go look up the people in Berkele…
You really think Berkeley's top-ranked PhD program is recruiting people who couldn't find jobs?
It is well known that PhD programmes churn out far more PhDs than can reasonably be employed in their field.
I mean, including friends and former colleagues I probably know maybe 300 people with PhDs. Of those I can count on my fingers those actually doing research in academia, probably one hand those on tenure track. But do you really think any of them slogged through the programme in Physics or Biology just to get a software job writing CRUD apps, or prettying up BI reports?
Re: Berkeley offers its data science course online for free
#74What exactly is Data Science? It seems like such an overused term and the value of the subject really gets diluted for me when I see charts in Tableau being offered as examples of "data science". What's the difference between, say, a Master's program in Computer Science where one studies machine learning and a Master's program in Data Science? Am I wrong for thinking the Data Science program weaker?
The CS program should focus more on data structures and algorithms (and possibly UX and good ol' software dev as well) and the DS program should focus more on statistical/analytical methods and their particular nuances and limitations. If the DS program is done well, with a lot of stats classes, then it is not a weaker program.
Re: Berkeley offers its data science course online for free
#75Earlier quoted context omitted.
I have also found this interesting. What I don't understand is that the amount of data science jobs are no where near the levels that people make it seem. I am not sure where all these people will end up working if they want to be a data scientist. There is not a need to hire huge teams of data scientists like you might for dev roles, it doesn't scale the same way.
Every job that involves data in any way is being relabeled a data science job. Most of them are just generating dashboards and posters in Excel or Tableau for people who are data illiterate. I know many people with maths/stats/comp-sci backgrounds who end up in these sorts of jobs. “Just add a bunch of green up arrows and red down arrows, your manager will love it” was advice from a co-worker of mine. Sadly, she was…
Where can I get a job like that? I'd be happy to take it at this point.
Re: Berkeley offers its data science course online for free
#76Earlier quoted context omitted.
There's a lot of value in your posts. Mathematizing problems, when successful, brings elegant solutions with well understood properties. Hence, I don't understand the downvotes you are usually getting. I'm a pure CS / logician by training, but I've spent a few years trying to expand my expertise into probability theory and stochastic processes. Lots of your advice resonates with me. My MSc advisor recommended I shoul…
In most academic fields, work that mathematizes the field is regarded as the best. Neveu is elegant beyond belief. I keep my copy close. I was aimed at Neveu by a star student of E. Cinlar, long at Princeton and before that at Northwestern -- long editor in chief of Mathematics of Operations Research . Neveu was a student of M. Loeve at Berkeley. So was the current darling of machine learning, L. Breiman, because of…
you could make that argument even for basic applied math, ... don't expect to be hired ... because the people hiring don't know why they are hiring or what to look for
Re: Berkeley offers its data science course online for free
#77What exactly is Data Science? It seems like such an overused term and the value of the subject really gets diluted for me when I see charts in Tableau being offered as examples of "data science". What's the difference between, say, a Master's program in Computer Science where one studies machine learning and a Master's program in Data Science? Am I wrong for thinking the Data Science program weaker?
What exactly is Data Science?
Data Science and DevOps are both just labels for things people have been doing under more mundane terms for 40-odd years.
Even Machine Learning is just a trendy buzzword for what used to be called Predictive Statistics.
Re: Berkeley offers its data science course online for free
#78I find it curious that there are so many courses for data-science related subjects, which superficially seem to cover the same material, and relatively few courses covering more traditional CS topics such as computer systems, networks, OS. I suppose it has to do with the market, but also feels like colleges are skating to where the puck is, rather than where it will be (or perhaps, where it could be).
I have also found this interesting. What I don't understand is that the amount of data science jobs are no where near the levels that people make it seem. I am not sure where all these people will end up working if they want to be a data scientist. There is not a need to hire huge teams of data scientists like you might for dev roles, it doesn't scale the same way.
I disagree with this. Every enterprise company has an analytical department, even more so in the public sector. My municipality has 8 guys working on analytics for instance.
They are mostly economics or (I’m not sure what it’s called in English, but it’s a degree in societal administration), but they really ought to be data scientists because everything they do is based on huge sql data sets.
We pay private contractors a lot of money to turn our data into cubes and manageable models because none of our analytics know how.
In 10 years I suspect anyone with that job title will need data science on their resume. Not just to manage the data, but also to start doing machine learning on it.
By comparison we have one network guy to run the network for 10.000 employees and 5000 students, with a backup guy who knows everything the first guy does but works with something else, you know, in case the first guy quits.
Re: Berkeley offers its data science course online for free
#79Earlier quoted context omitted.
> Every graduate that doesn't find a high paying job in the field is an excellent candidate for the next level of education. 1. You really think Berkeley's top-ranked PhD program is recruiting people who couldn't find jobs? No. Not only can 100% of successful top-tier PhD applicants find jobs, 100% of them are strong candidates for the top echelon on entry-level jobs. If you disagree, go look up the people in Berkele…
You really think Berkeley's top-ranked PhD program is recruiting people who couldn't find jobs? It is well known that PhD programmes churn out far more PhDs than can reasonably be employed in their field. I mean, including friends and former colleagues I probably know maybe 300 people with PhDs. Of those I can count on my fingers those actually doing research in academia, probably one hand those on tenure track. But…
You're arguing against a point that the OP didn't make.
Re: Berkeley offers its data science course online for free
#80Okay, here's a view of what appears to be part of the course: We have a course (right a school application of stuff taught in school!) with two teachers, that is, two sections of the course, each section with its own teacher and its own students. At the end of the two courses, that is, the two sections, we want to compare the teachers. So we give the same test to all of the students from both courses. Suppose one sec…
I loved your post man. I think you are right about the rebranding of Applied Stat as ML|AI. I love stuff like these. I did take 3 Stat course in university. Currently I am working as a dev.I took a course in my free time http://codingthematrix.com/ and loved the programming part of it. Do you happen to know some courses where one would have stat part as well as the programming par?
For this statistics and applied math, at least anywhere near the level of the Berkeley course in the OP, it's by now old stuff, older than nearly all living programmers! Well from various subroutine libraries, some open source, some from, IIRC, the US National Bureau of Standards and Technology, SPSS (Statistical Package for the Social Sciences), SAS (Statistical Analysis System), R, Matlab, Mathematica, LINPACK, CART (Classification and Regression Trees, by L. Breiman and others), and more, there's a LOT of code from quite good up to highly polished. Mostly now people use such code instead of writing it. For stochastic processes, there's code, e.g., the fast Fourier transform for which there is a huge pile of code, for all the different flavors of that curious algorithm.
Well, there is more code to write, but IMHO that would be for relatively advanced techniques or, say, working with terabytes of data instead of megabytes.
If you want to write code for applied statistics, then maybe so indicate, have a portfolio of code, and contact the usual suspects -- US national security and medical research. I'm not optimistic. I've given my opinion -- find a good application and found a startup to monetize it.
It is true that today there is a WSJ article on how technical, with algorithms for trading, Wall Street has become. The article has next to nothing on what applied math is being used but does have lots of names, maybe some you could contact. Actually, the article mentions that Goldman Sachs (GS) got hot on such applied math. Well, that was about when I wrote Fisher Black, of Black-Scholes, there at GS asking about applied math at GS, and I got back a nice letter from Black saying that he saw no such opportunities. Well, the WSJ article today claims that that time was when GS was getting hot on applied math.
If you want to know about applied math on Wall Street, then try to get an opinion or overview from, say, James Simons.
Again, IMHO, it's academics, US national security, medical research, maybe a few other situations, but best of all, start a business, the money making kind.