I'm working on my PhD with a focus in Computational Biology, so I may be biased toward the academic side of things, but I love to sling code so I'll give answering this a shot.
You say that you are mainly interested in web development, so I will try to focus on that world.
For client side dev, Javascript is really the only choice these days. If you have any experience with pure Javascript, you probably know that it is a ridiculous mess of a language. It has been made (reasonably) useful by several frameworks in recent years. You will want to look into angular, backbone or react in order to make anything useful. The big thing to get clear in your head with modern Javascript is how to handle asynchronicity.
On the app server side, the new hotness appears to be Go. It is popular because it makes concurrency easier. Most of the push these days has been taking advantage of concurrency and the ascendant languages (Go, Node, Julia) generally in some way try to make this easier. For interpreted languages, Julia looks really interesting and IMHO has a good shot at being very popular in the near future. It has a smart, friendly community and you might get in on the ground floor of a language that will be hot when you are done.
You should learn to use some NoSQL datastore, and more importantly when and where you want to use a one.
Of course, C/C++ is essential to understanding (almost) any modern programming language, not to mention Data Structures. If you believe you need brushing up on these, then that should be your first stop. Take a systems class your first semester and you should get a nice refresher on what is actually going on under the hood with most of the rest of the languages.
One thing to keep in mind is that all programming languages go through periods of growth and decay. You should focus on concepts, with the languages being merely tools that have certain niches which sometimes map better to certain concepts than others. The key concepts of the future are concurrency, distributed and heterogeneous architectures(cloud/devices/IoT), data management and security.
That said, you asked for a top ten, so if I was looking for Masters with a focus on web dev at this point in time, my top 10 would be- C/C++, Javascript(Client side), Go, Julia, Python(probably less important in the future, but I feel there is nothing better for rapid prototyping), Node, Java( I don't like Java, but it is very versatile), Haskell(token functional lang), SQL, HTML/CSS.
Again, the languages themselves are less important than the concepts. The future is asynchronous, concurrent, distributed, heterogeneous and data rich. Prepare yourself for that world and you should be in good shape
Second on Starcluster. Very easy to get up and running quickly.
It is well documented with a good plugin system. If you do scientific computing, then you are probably familiar with most of the tools that are built in; SGE, ipython, nfs, etc.
Aside from the provided Amazon tools, I find the boto(python) library to be helpful if I need to interact with s3 or sqs.
Slashdot Mirror
The Symposium on Computational Geometry recently voted to leave the ACM for this reason( https://sympa.inria.fr/sympa/arc/compgeom-announce/2014-07/msg00003.html), Not only is the ACM almost completely irrelevant to practitioners, it is quickly losing relevance to academics.
I'm working on my PhD with a focus in Computational Biology, so I may be biased toward the academic side of things, but I love to sling code so I'll give answering this a shot. You say that you are mainly interested in web development, so I will try to focus on that world. For client side dev, Javascript is really the only choice these days. If you have any experience with pure Javascript, you probably know that it is a ridiculous mess of a language. It has been made (reasonably) useful by several frameworks in recent years. You will want to look into angular, backbone or react in order to make anything useful. The big thing to get clear in your head with modern Javascript is how to handle asynchronicity. On the app server side, the new hotness appears to be Go. It is popular because it makes concurrency easier. Most of the push these days has been taking advantage of concurrency and the ascendant languages (Go, Node, Julia) generally in some way try to make this easier. For interpreted languages, Julia looks really interesting and IMHO has a good shot at being very popular in the near future. It has a smart, friendly community and you might get in on the ground floor of a language that will be hot when you are done. You should learn to use some NoSQL datastore, and more importantly when and where you want to use a one. Of course, C/C++ is essential to understanding (almost) any modern programming language, not to mention Data Structures. If you believe you need brushing up on these, then that should be your first stop. Take a systems class your first semester and you should get a nice refresher on what is actually going on under the hood with most of the rest of the languages. One thing to keep in mind is that all programming languages go through periods of growth and decay. You should focus on concepts, with the languages being merely tools that have certain niches which sometimes map better to certain concepts than others. The key concepts of the future are concurrency, distributed and heterogeneous architectures(cloud/devices/IoT), data management and security. That said, you asked for a top ten, so if I was looking for Masters with a focus on web dev at this point in time, my top 10 would be- C/C++, Javascript(Client side), Go, Julia, Python(probably less important in the future, but I feel there is nothing better for rapid prototyping), Node, Java( I don't like Java, but it is very versatile), Haskell(token functional lang), SQL, HTML/CSS. Again, the languages themselves are less important than the concepts. The future is asynchronous, concurrent, distributed, heterogeneous and data rich. Prepare yourself for that world and you should be in good shape
Wish I had mod points. Thanks.
Second on Starcluster. Very easy to get up and running quickly. It is well documented with a good plugin system. If you do scientific computing, then you are probably familiar with most of the tools that are built in; SGE, ipython, nfs, etc. Aside from the provided Amazon tools, I find the boto(python) library to be helpful if I need to interact with s3 or sqs.