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  • Computer science advances in the past 5 years

    - by Doug Stanhope
    I don't have a computer science background and only have a rudimentary knowledge of what CS is all about. However, I wonder, what are the most significant CS advances of the last five years? To give you an idea of how clueless I am, I couldn't name one of these advances. But, please don't spare me all the gory details. I'm not looking for an education in CS or a story about the history of CS. As far as this question is concerned only the past five years matter! :-)

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  • Best computer-science universities in Europe?

    - by Tom
    I am in 11th grade and only one year left when I finish my school. I am sure I want to dedicate my life to programming. In my country the education's level is not so high as in Europe, so I want to emigrate and study not just for a diploma, but for knowledge too. So, what universities would you suggest me which has subject Computer-Science? I prefer web programming. Please do not delete this message though it is quite offtopic, but it's the best place for me to get suggestions from advanced programmers who have already finished their university. And I hope here comes also teenagers who can make the best decision choosing university. Thank you. Please read the whole my message before voting to close this thread, thanks.

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  • Which set(s) of video lectures for computer science?

    - by SebKom
    As most of you know a couple of top universities (MIT, Stanford, etc) around the world are now publishing videos of their lectures online. I am advancing to the third and final year of my computer science degree this September and I was thinking about spending some time during the summer to watch a couple of lectures, in order to improve my understanding of algorithms, complexity, programming, software engineering, etc. Now I don't have infinite time to spend so I can't watch all of the lectures from all of the universities so I was wondering if you could suggest me which sets to watch from each one (something like "Algorithms from MIT", "Programming from Yale", etc).

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  • Keeping Computer Science Writing Accessible and Eloquent

    - by Federer
    This question is particularly aimed at descriptions and explanations of what is happening in a computer program, as well as any general advice or approaches for undertaking technical reports in Computer Science at both undergraduate and graduate levels. You see, I am having particular difficulty in the best way to explain what is happening. As in, given any given program from a multi-agent system to a standard webservice, the best and most eloquent way to say exactly what is going on, the logic behind it and it's respective justifications. Should I avoid saying class names? Avoid specifying methods? Keep referring to class variables and any particular references? I'm banging my head against the wall at trying to keep a solid technical foundation and making it accessible to people of all backgrounds. Apologies for the rather vague question. Cheers.

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  • Understanding Data Science: Recent Studies

    - by Joe Lamantia
    If you need such a deeper understanding of data science than Drew Conway's popular venn diagram model, or Josh Wills' tongue in cheek characterization, "Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician." two relatively recent studies are worth reading.   'Analyzing the Analyzers,' an O'Reilly e-book by Harlan Harris, Sean Patrick Murphy, and Marck Vaisman, suggests four distinct types of data scientists -- effectively personas, in a design sense -- based on analysis of self-identified skills among practitioners.  The scenario format dramatizes the different personas, making what could be a dry statistical readout of survey data more engaging.  The survey-only nature of the data,  the restriction of scope to just skills, and the suggested models of skill-profiles makes this feel like the sort of exercise that data scientists undertake as an every day task; collecting data, analyzing it using a mix of statistical techniques, and sharing the model that emerges from the data mining exercise.  That's not an indictment, simply an observation about the consistent feel of the effort as a product of data scientists, about data science.  And the paper 'Enterprise Data Analysis and Visualization: An Interview Study' by researchers Sean Kandel, Andreas Paepcke, Joseph Hellerstein, and Jeffery Heer considers data science within the larger context of industrial data analysis, examining analytical workflows, skills, and the challenges common to enterprise analysis efforts, and identifying three archetypes of data scientist.  As an interview-based study, the data the researchers collected is richer, and there's correspondingly greater depth in the synthesis.  The scope of the study included a broader set of roles than data scientist (enterprise analysts) and involved questions of workflow and organizational context for analytical efforts in general.  I'd suggest this is useful as a primer on analytical work and workers in enterprise settings for those who need a baseline understanding; it also offers some genuinely interesting nuggets for those already familiar with discovery work. We've undertaken a considerable amount of research into discovery, analytical work/ers, and data science over the past three years -- part of our programmatic approach to laying a foundation for product strategy and highlighting innovation opportunities -- and both studies complement and confirm much of the direct research into data science that we conducted. There were a few important differences in our findings, which I'll share and discuss in upcoming posts.

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  • Computer science final year project ideas

    - by roul
    I'm a Computer Science undergraduate student in UK and should be deciding the subject of my final year project soon. The school is pretty flexible with the subject... "The topic can be any area of the subject which is of mutual interest to both the student and supervisor. Topics can range from purely theoretical studies to practical work building a system for some third party, although most projects aim to provide a balance between the theoretical and practical aspects of the subject." ...so I'm a bit lost since I want to do something in software engineering but have no idea what (subject) or with what (languages)! :) a) Languages: I've had experience with Java, C# and ASP.NET mostly but I would definitely be interested in learning new languages/frameworks. I'm kind of drawn by the idea of dynamic languages at the moment so IronPython seems likely. b) Subject: Anything that will keep me interested through the year and will give me the opportunity to learn a lot of stuff. Maybe something that has to do with music, or a fancy website, or a website about music :P anything really. Open to any thoughts/ideas, geeky or cool! Edit: Professors do usually supervise projects in their research areas but I currently have the choice to approach any of them according to my interest - whatever that is.

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  • Masters in Computer Science

    - by reko
    Hi, My name is Gautam. I come from India. I am extremely passionate about Web Development.. I like to build web applications all the time.. Can I make this web application building a full time profession? I have just graduated from bachelors... Is there a Master of Computer Science in Web Development? Can I choose Masters in Web Development? Is it a bad choice? Is there a course very close to it Web Development that I can choose? Should I just keep Web Development as a part time thing to do?? Could you please let me know any good universities which offer this course/ close to this course for Spring 2010? Please advice on what I should do because my mind keeps throwing millions of questions on what I should do and my only hope is STACKOVERFLOW helps me as it always does to solve problems.. Looking forward for your reply.. Thanks in advance Regards, Gautam

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  • Will a Ph. D. in Computer Science help?

    - by Francisco Garcia
    I am close to my 30s and still learning about programming and software engineering. Like most people who like their profession I truly believe that I should aim to improve and keep updated. One of the things I do is reading technical papers from professional publications (IEEE and ACM) but I admit there are very good bloggers out there too. Lately I started to think (should I say realize?) that Ph. D people actually are expected to expand constantly their knowledge, but little is expected from lower classes once they know enough This made me think that maybe having a Ph. D will help to have more... respect? but I also believe that I am already getting old for that. Futhermore I see many master and doctor programs that does not seem to add any value over hard experience and self learning. I belive that a degree in computer science, althought not necessary, can lay out a good base for programming work. However: What can a Ph. D. degree give you that you cannot learn on your own? (if you are not into something VERY specific and want to work in a non academic environment)

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  • Computer Science taxonomy

    - by Bakhtiyor
    I am developing web application where users have collection of tags. I need to create a suggestion list for users based on the similarity of their tags. For example, when a user logs in to the system, system gets his tags and search these tags in the DB of users and showing users who have similar tags. For instance if User 1 has following tags [Linux, Apache, MySQL, PHP] and User 2 has [Windows, IIS, PHP, MySQL] it says that User 2 matchs User 1 with a weight of 50%, because he has 2 similar tags(PHP and MySQL). But imagine the situation where User 1 has [ASP, IIS, MS Access] and User 2 has [PHP, Apache, MySQL]. In this situation my system doesn't suggest User 2 as a "friend" to User 1 or vice versa. But we now that these two users has similarity on the the field of work, both works on Web Technology (or Web Programming, etc). So, that is why I need kind of taxonomy of computer science (right now, but probably I would need taxonomy of other fields also, like medicine, physics, mathematics, etc.) where these concepts are categorized and so that when I search for similarity of ASP and PHP, for example, it can say that they have similarity and belong into one group(or category). I hope I described my problem clearly, but if something wrong explained would be happy for your corrections. Thanks

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  • Computer Science Degree or Computer Engineering Degree?

    - by Paul
    Hello everyone, I'm 23 years old living in Italy and this year I will be getting my high school diploma. I'm interested in pursuing a collage degree and work in the IT field. At the moment I'm self teaching myself Java (I also know python, html, css and mysql). I'm also learning about algorithms and OO design. I'm curious how important a college degree is for me, considering my age and if there is a big difference between computer science and computer engineer. There is a computer science university where I currently live but not a computer engineer one. For some reason universities that offer computer engineering courses are only in bigger cities such as Milan, Bologna, Roma. Cost wise, it would be cheaper for me to study near home at a computer science school. Career wise, would a computer engineering university offer me more work opportunities instead of a computer science degree ? Is it easier transiting from CS to CEN or vice-versa? I'm not exactly sure what type of job I want to pursue in the future since I'm still a bit undecided but definitely not system/network administrator, database administrator, game developer.

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  • Computer Science Fundamentals - Recommended books

    - by contactmatt
    Hey, I'm looking to see if anyone can recommend any books in fundamentals of computer science. I obtained my associates degree as a programmer/analyst a couple years ago and I know a good amount about programming on the .NET framework. I'm even certified on the .NET 4 framework as a web application developer. However, since I was only able to obtain my associates degree, I was deprived at my college on the low-level basics and operations of computers and basic computer science information. I'm really interesting in learning about the low-level operations of a computer and in programming (bytes, bits, memory management, etc.) Can anyone recommend any good computer science books for someone who is decently experienced in programming? Thank You

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  • Computer Science Career Advice: Master's in Computer Science vs. Software Engineering?

    - by Everton
    Hello, I am a college student and I am majoring in Computer Science and Applied Mathematics. As I get closer to my senior year I have noticed that continuing my studies is the best choice right for me now. I see that several universities offer an Computer Science Master's Degree and an Software Engineering degree. What are their pros and cons? I feel that while the Computer Science master's degree seems a little too broad the Software Engineering is too restrictive. I did not decide yet between an career of Software development or research ( algorithm development among other things ). Any advice would be greatly apreciated!

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  • What is the biggest weakness of students graduating with degrees in Computer Science?

    - by akobre01
    This question is directed more toward employers and graduate student advisors/professors but all opinions are welcome. What do you find is a common weakness of new hires and/or new grad students? Is it entirely variable dependent on the student and his or her university? Is there a particular skill or skillset that you wish new hires/researchers had expertise in and how can we remedey this deficiency? I realize that this question is general and really encapsulates two questions, one more about the weaknesses of new software engineers and one about the weaknesses of new researchers. However, both types of people tend to come from similar courses of study so I'm wondering if there is any overlap. Note: I am not a professor but I'm interested in how best to revise the undergraduate curriculum in CS.

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  • How to Avoid Your Next 12-Month Science Project

    - by constant
    While most customers immediately understand how the magic of Oracle's Hybrid Columnar Compression, intelligent storage servers and flash memory make Exadata uniquely powerful against home-grown database systems, some people think that Exalogic is nothing more than a bunch of x86 servers, a storage appliance and an InfiniBand (IB) network, built into a single rack. After all, isn't this exactly what the High Performance Computing (HPC) world has been doing for decades? On the surface, this may be true. And some people tried exactly that: They tried to put together their own version of Exalogic, but then they discover there's a lot more to building a system than buying hardware and assembling it together. IT is not Ikea. Why is that so? Could it be there's more going on behind the scenes than merely putting together a bunch of servers, a storage array and an InfiniBand network into a rack? Let's explore some of the special sauce that makes Exalogic unique and un-copyable, so you can save yourself from your next 6- to 12-month science project that distracts you from doing real work that adds value to your company. Engineering Systems is Hard Work! The backbone of Exalogic is its InfiniBand network: 4 times better bandwidth than even 10 Gigabit Ethernet, and only about a tenth of its latency. What a potential for increased scalability and throughput across the middleware and database layers! But InfiniBand is a beast that needs to be tamed: It is true that Exalogic uses a standard, open-source Open Fabrics Enterprise Distribution (OFED) InfiniBand driver stack. Unfortunately, this software has been developed by the HPC community with fastest speed in mind (which is good) but, despite the name, not many other enterprise-class requirements are included (which is less good). Here are some of the improvements that Oracle's InfiniBand development team had to add to the OFED stack to make it enterprise-ready, simply because typical HPC users didn't have the need to implement them: More than 100 bug fixes in the pieces that were not related to the Message Passing Interface Protocol (MPI), which is the protocol that HPC users use most of the time, but which is less useful in the enterprise. Performance optimizations and tuning across the whole IB stack: From Switches, Host Channel Adapters (HCAs) and drivers to low-level protocols, middleware and applications. Yes, even the standard HPC IB stack could be improved in terms of performance. Ethernet over IB (EoIB): Exalogic uses InfiniBand internally to reach high performance, but it needs to play nicely with datacenters around it. That's why Oracle added Ethernet over InfiniBand technology to it that allows for creating many virtual 10GBE adapters inside Exalogic's nodes that are aggregated and connected to Exalogic's IB gateway switches. While this is an open standard, it's up to the vendor to implement it. In this case, Oracle integrated the EoIB stack with Oracle's own IB to 10GBE gateway switches, and made it fully virtualized from the beginning. This means that Exalogic customers can completely rewire their server infrastructure inside the rack without having to physically pull or plug a single cable - a must-have for every cloud deployment. Anybody who wants to match this level of integration would need to add an InfiniBand switch development team to their project. Or just buy Oracle's gateway switches, which are conveniently shipped with a whole server infrastructure attached! IPv6 support for InfiniBand's Sockets Direct Protocol (SDP), Reliable Datagram Sockets (RDS), TCP/IP over IB (IPoIB) and EoIB protocols. Because no IPv6 = not very enterprise-class. HA capability for SDP. High Availability is not a big requirement for HPC, but for enterprise-class application servers it is. Every node in Exalogic's InfiniBand network is connected twice for redundancy. If any cable or port or HCA fails, there's always a replacement link ready to take over. This requires extra magic at the protocol level to work. So in addition to Weblogic's failover capabilities, Oracle implemented IB automatic path migration at the SDP level to avoid unnecessary failover operations at the middleware level. Security, for example spoof-protection. Another feature that is less important for traditional users of InfiniBand, but very important for enterprise customers. InfiniBand Partitioning and Quality-of-Service (QoS): One of the first questions we get from customers about Exalogic is: “How can we implement multi-tenancy?” The answer is to partition your IB network, which effectively creates many networks that work independently and that are protected at the lowest networking layer possible. In addition to that, QoS allows administrators to prioritize traffic flow in multi-tenancy environments so they can keep their service levels where it matters most. Resilient IB Fabric Management: InfiniBand is a self-managing network, so a lot of the magic lies in coming up with the right topology and in teaching the subnet manager how to properly discover and manage the network. Oracle's Infiniband switches come with pre-integrated, highly available fabric management with seamless integration into Oracle Enterprise Manager Ops Center. In short: Oracle elevated the OFED InfiniBand stack into an enterprise-class networking infrastructure. Many years and multiple teams of manpower went into the above improvements - this is something you can only get from Oracle, because no other InfiniBand vendor can give you these features across the whole stack! Exabus: Because it's not About the Size of Your Network, it's How You Use it! So let's assume that you somehow were able to get your hands on an enterprise-class IB driver stack. Or maybe you don't care and are just happy with the standard OFED one? Anyway, the next step is to actually leverage that InfiniBand performance. Here are the choices: Use traditional TCP/IP on top of the InfiniBand stack, Develop your own integration between your middleware and the lower-level (but faster) InfiniBand protocols. While more bandwidth is always a good thing, it's actually the low latency that enables superior performance for your applications when running on any networking infrastructure: The lower the latency, the faster the response travels through the network and the more transactions you can close per second. The reason why InfiniBand is such a low latency technology is that it gets rid of most if not all of your traditional networking protocol stack: Data is literally beamed from one region of RAM in one server into another region of RAM in another server with no kernel/drivers/UDP/TCP or other networking stack overhead involved! Which makes option 1 a no-go: Adding TCP/IP on top of InfiniBand is like adding training wheels to your racing bike. It may be ok in the beginning and for development, but it's not quite the performance IB was meant to deliver. Which only leaves option 2: Integrating your middleware with fast, low-level InfiniBand protocols. And this is what Exalogic's "Exabus" technology is all about. Here are a few Exabus features that help applications leverage the performance of InfiniBand in Exalogic: RDMA and SDP integration at the JDBC driver level (SDP), for Oracle Weblogic (SDP), Oracle Coherence (RDMA), Oracle Tuxedo (RDMA) and the new Oracle Traffic Director (RDMA) on Exalogic. Using these protocols, middleware can communicate a lot faster with each other and the Oracle database than by using standard networking protocols, Seamless Integration of Ethernet over InfiniBand from Exalogic's Gateway switches into the OS, Oracle Weblogic optimizations for handling massive amounts of parallel transactions. Because if you have an 8-lane Autobahn, you also need to improve your ramps so you can feed it with many cars in parallel. Integration of Weblogic with Oracle Exadata for faster performance, optimized session management and failover. As you see, “Exabus” is Oracle's word for describing all the InfiniBand enhancements Oracle put into Exalogic: OFED stack enhancements, protocols for faster IB access, and InfiniBand support and optimizations at the virtualization and middleware level. All working together to deliver the full potential of InfiniBand performance. Who else has 100% control over their middleware so they can develop their own low-level protocol integration with InfiniBand? Even if you take an open source approach, you're looking at years of development work to create, test and support a whole new networking technology in your middleware! The Extras: Less Hassle, More Productivity, Faster Time to Market And then there are the other advantages of Engineered Systems that are true for Exalogic the same as they are for every other Engineered System: One simple purchasing process: No headaches due to endless RFPs and no “Will X work with Y?” uncertainties. Everything has been engineered together: All kinds of bugs and problems have been already fixed at the design level that would have only manifested themselves after you have built the system from scratch. Everything is built, tested and integrated at the factory level . Less integration pain for you, faster time to market. Every Exalogic machine world-wide is identical to Oracle's own machines in the lab: Instant replication of any problems you may encounter, faster time to resolution. Simplified patching, management and operations. One throat to choke: Imagine finger-pointing hell for systems that have been put together using several different vendors. Oracle's Engineered Systems have a single phone number that customers can call to get their problems solved. For more business-centric values, read The Business Value of Engineered Systems. Conclusion: Buy Exalogic, or get ready for a 6-12 Month Science Project And here's the reason why it's not easy to "build your own Exalogic": There's a lot of work required to make such a system fly. In fact, anybody who is starting to "just put together a bunch of servers and an InfiniBand network" is really looking at a 6-12 month science project. And the outcome is likely to not be very enterprise-class. And it won't have Exalogic's performance either. Because building an Engineered System is literally rocket science: It takes a lot of time, effort, resources and many iterations of design/test/analyze/fix to build such a system. That's why InfiniBand has been reserved for HPC scientists for such a long time. And only Oracle can bring the power of InfiniBand in an enterprise-class, ready-to use, pre-integrated version to customers, without the develop/integrate/support pain. For more details, check the new Exalogic overview white paper which was updated only recently. P.S.: Thanks to my colleagues Ola, Paul, Don and Andy for helping me put together this article! var flattr_uid = '26528'; var flattr_tle = 'How to Avoid Your Next 12-Month Science Project'; var flattr_dsc = 'While most customers immediately understand how the magic of Oracle's Hybrid Columnar Compression, intelligent storage servers and flash memory make Exadata uniquely powerful against home-grown database systems, some people think that Exalogic is nothing more than a bunch of x86 servers, a storage appliance and an InfiniBand (IB) network, built into a single rack.After all, isn't this exactly what the High Performance Computing (HPC) world has been doing for decades?On the surface, this may be true. And some people tried exactly that: They tried to put together their own version of Exalogic, but then they discover there's a lot more to building a system than buying hardware and assembling it together. IT is not Ikea.Why is that so? Could it be there's more going on behind the scenes than merely putting together a bunch of servers, a storage array and an InfiniBand network into a rack? Let's explore some of the special sauce that makes Exalogic unique and un-copyable, so you can save yourself from your next 6- to 12-month science project that distracts you from doing real work that adds value to your company.'; var flattr_tag = 'Engineered Systems,Engineered Systems,Infiniband,Integration,latency,Oracle,performance'; var flattr_cat = 'text'; var flattr_url = 'http://constantin.glez.de/blog/2012/04/how-avoid-your-next-12-month-science-project'; var flattr_lng = 'en_GB'

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  • Computer science undergraduate project ideas

    - by Mehrdad Afshari
    Hopefully, I'm going to finish my undergraduate studies next semester and I'm thinking about the topic of my final project. And yes, I've read the questions with duplicate title. I'm asking this from a bit different viewpoint, so it's not an exact dupe. I've spent at least half of my life coding stuff in different languages and frameworks so I'm not looking at this project as a way to learn much about coding and preparing for real world apps or such. I've done lots of those already. But since I have to do it to complete my degree, I felt I should spend my time doing something useful instead of throwing the whole thing out. I'm planning to make it an open source project or a hosted Web app (depending on the type) if I can make a high quality thing out of it, so I decided to ask StackOverflow what could make a useful project. Situation I've plenty of freedom about the topic. They also require 30-40 pages of text describing the project. I have the following points in mind (the more satisfied, the better): Something useful for software development Something that benefits the community Having academic value is great Shouldn't take more than a month of development (I know I'm lazy). Shouldn't be related to advanced theoretical stuff (soft computing, fuzzy logic, neural networks, ...). I've been a business-oriented software developer. It should be software oriented. While I love hacking microcontrollers and other fun embedded electronic things, I'm not really good at soldering and things like that. I'm leaning toward a Web application (think StackOverflow, PasteBin, NerdDinner, things like those). Technology It's probably going to be done in .NET (C#, F#) and Windows platform. If I really like the project (cool low level hacking), I might actually slip to C/C++. But really, C# is what I'm efficient at. Ideas Programming language, parsing and compiler related stuff: Designing a domain specific programming language and compiler Templating language compiled to C# or IL Database tools and related code generation stuff Web related technologies: ASP.NET MVC View engine doing something cool (don't know what exactly...) Specific-purpose, small, fast ASP.NET-based Web framework Applications: Visual Studio plugin to integrate with Bazaar (it's too much work, I think). ASP.NET based, jQuery-powered issue tracker (and possibly, project lifecycle management as a whole - poor man's TFS) Others: Something related to GPGPU Looking forward for great ideas! Unfortunately, I can't help on a currently existing project. I need to start my own to prevent further problems (as it's an undergrad project, nevertheless).

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  • What topic in computer science is this?

    - by jasonbogd
    Hi, I am trying to figure out what 'topic' this is called, so I can learn more about it. Basically, I'm talking about designing my applications's architecture. I'm not talking about algorithms. More like -- this class should have these methods and these instance variables, and communicate with this class in this way, this class should have these responsibilities etc. Can anybody tell me what the name of this topic is called and how I can get better at doing this? Thanks.

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  • Mathematics for Computer Science Students

    - by Ender
    To cut a long story short, I am a CS student that has received no formal Post-16 Maths education for years. Right now even my Algebra is extremely rusty and I have a couple of months to shape up my skills. I've got a couple of video lectures in my bookmarks, consisting of: Pre-Calculus Algebra Calculus Probability Introduction to Statistics Differential Equations Linear Algebra My aim as of today is to be able to read the CLRS book Introduction to Algorithms and be able to follow the Mathematical notation in that, as well as being able to confidently read and back-up any arguments written in Mathematical notation. Aside from these video lectures, can anyone recommend any good books to help teach someone wishing to go from a low-foundation level to a more advanced level of Mathematics? Just as a note, I've taken a first-year module in Analytical Modelling, so I understand some of the basic concepts of Discrete Mathematics. EDIT: Just a note to those that are looking to learn Linear Algebra using the Video Lectures I have posted up. Peteris Krumins' Blog contains a run-through of these lecture notes as well as his own commentary and lecture notes, an invaluable resource for those looking to follow the lectures too.

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  • Mathematics for Computer Science

    - by jiewmeng
    I am going into university next year. I think maths would be one of the more important aspects of computer science? I recently saw the MIT Intro to Algorithms video on YouTube and the maths required is quite hardcore. I wonder what parts of maths do i need, probability, calculus, trigo etc. Will the book Concrete Mathematics - it claims to be foundation for computer science - on Amazon cover most of whats required?

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  • from MS Biology to BS Computer Science [on hold]

    - by Air Borne
    I'm Marco from Italy and I'd like to ask you a piece of advice about my career. I hold a Ms degree in Biology, I enjoyed a lot studying it and I got very good grades but I didn't know what to do with my degree in the real life. Few months ago, I began to read a book about Python programming (Introduction to Computer Science, Zelle J.) and I've great fun learning Python as a beginner, I wake up in the morning thinking about doing excersies and writing simple programs with python :) I'm also watching free lectures from MIT open courseware, and I'm feeling a certain degree of regrets for never asking myself what was computer science, since it seems to me it's a magic world. After weeks of doubts, I made a move :) I applied for a CS bachelor degree abroad, I got an interview and I'm going to start this great adventure next September. I feel incredibly excited at it, but a little bit scared too. Scared because sometimes I think I'm making a great mistake for my life restarting from a bachelor in a completely different area of study. Sometimes I hear people saying the IT market is bad, sometimes I hear other ones saying quite the opposite instead. Moreover, some colleagues of mine suggested me to try to get into Bioinformatics, instead of CS. My question is: I want to really discover if CS is for me, I mean the passion of my life. I know I'm just a beginner and I can't say nothing about it yet. What do you suggest me: CS or Bioinformatics? If I get a Bs in CS, could I get into bioinformatics without relevant experience, taking into account I have a Ms Biology degree? Any comment is appreciated, thanks in advance.

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  • Why are invariants important in Computer Science

    - by Antony Thomas
    I understand 'invariant' in its literal sense. I also recognize them when I type code. But I don't think I understand the importance of this term in the context of computer science. Whenever I read conversations\white papers about language design from famous programmers\computer scientists, the term 'invariant' keeps popping up as a jargon; and that is the part I don't understand. What is so special about it?

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  • Laser Cutter Plays Portal Theme Song While Cutting Aperture Science Logo [Video]

    - by Jason Fitzpatrick
    We’re at a total loss to think of anything more geeky than a laser cutter programmed to simultaneously laser cut the Aperture Science logo while playing “Stile Alive” from Portal. If you’re unfamiliar with the original tune, check out this video. [via Boing Boing] The HTG Guide to Hiding Your Data in a TrueCrypt Hidden Volume Make Your Own Windows 8 Start Button with Zero Memory Usage Reader Request: How To Repair Blurry Photos

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  • Career path to get into computer science research

    - by srinathhs
    I taught this question will be appropriate to ask here. I am currently a software engineer working mainly on Java stuff , along with some android. My question : I want to be a researcher in "computer science" down the line 6 - 7 yrs, what do you folks suggest should be my path to reach it ? Constraints : I cannot cannot do formal MS or PHD , I simply cant afford it. I can dedicate certain amount of time per day to study and research.

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