Skip to main content

5 Tips for Computer Science Students

5-tips-img
You are in college now so I am skipping the basics the go to class do your homework study for tests stay out of the hospital. These are not all important pieces of advice but I am sure you have heard them. Instead, let’s talk computer science. Here are some tips I have specially collected by talking to students who wish they’d heard them when they were students. Listen up.

  1. Seek help when you need it. Your classes are going to get harder, they are going to test your knowledge but that’s why you are there for. Some people find attending office hours or seeking extra help to be embarrassing. But these resources are there for a reason. Taking advantage of the help you are offered will not only help you prepare for future classes and learn the material better but a lot less harmful than bad grades or any other consequences of struggling.
  2. Don’t let yourself intimidated by large projects. The best thing to do, sit down a day at the assignment and break it up into smaller tasks. A lot of times it’s looking at the smaller tasks that help you realize the solution and even if it does not, you’ll only have to face one small problem at a time instead of a huge and overwhelming one.
  3. Error can be unpredictable for don’t procrastinate even if you see the solution right away. You still can’t really predict the types of errors you are going to face. It’s time to compile or if there’d logical errors when you run it. Sometimes it may be the slightest error that can be the hardest to catch. So make sure you leave yourself enough time to tackle it.
  4. Silly errors are no small things is computer science. One silly error can ruin the entire program and likewise, you are great. It is not uncommon for computer science classes to skip partial credit. If your code does not work you make it nothing for it. A more compassionate professor might throw you off 50% but the truth is that one little missing semicolon that you were too tired to find before returning your homework can be all it takes to turn an A into an F. So, don’t miss the semicolon.
  5. Stop and compile regularly. If you compile your projects on regular basis, you can solve errors as they appear and locating them would be easy because they could only appear since the last time you compiled. I know it can be annoying to get your program to a stopping point or you can do this but it’s definitely worth it. The alternative is getting all the errors at the end and there could be a lot of them. All hidden throughout your code, the code you wrote who knows how long ago and make sure you test sample code before you use it. There is nothing worse than just assuming that it works only to find out it’s the source of your problem and the one place you didn’t look.

Subscribe for more.

Comments

Popular posts from this blog

Introduction to Data Science: What is Big Data?

What Is Big Data First, we will discuss how big data is evaluated step by step process. Evolution of Data How the data evolved and how the big data came. Nowadays the data have been evaluated from different sources like the evolution of technology, IoT(Internet of Things), Social media like Facebook, Instagram, Twitter, YouTube, many other sources the data has been created day by day. 1. Evolution of  Technology We will see how technology is evolved as we see from the below image at the earlier stages we have the landline phone but now we have smartphones of Android, IoS, and HongMeng Os (Huawei)  that are making our life smarter as well as our phone smarter. Apart from that, we have heavily built a desktop for processing of Mb's data that we were using a floppy you will remember how much data it can be stored after that hard disk has been introduced which can stored data in Tb. Now due to modern technology, we can be stored data in the cloud as well. Similarly, nowadays we noticed …

How Big Data Analytics Can Help You Improve And Grow Your Business?

Big Data Analytics There are certain problems that can only solve through big data. Here we discuss the field big data as "Big Data Analytics". The big data came into the picture we never thought how commodity hardware is used to store and manage the data which is reliable and feasible as compared to the costly sources. Now let us discuss a few examples of how big data analytics is useful nowadays. When you go to websites like Amazon, Youtube, Netflix, and any other websites actually they will provide some field in which recommend some product, videos, movies, and some songs for you. What do you think about how they do it? Basically what kind of data they generated on these kind websites. They make sure to analyze properly. The data generated is not small it is actually big data. Now they analysis these big data they make sure whatever you like and whatever you are the preferences accordingly they generate recommendations for you. If you go to Youtube you have noticed it kn…

AI Vs Machine Learning Vs Deep Learning

AI Vs Machine Learning Vs Deep Learning Artificial intelligence, deep learning and machine learning are often confused with each other. These terms are used interchangeably but do they do not refer to the same thing. These terms are closely related to each other which makes it difficult for beginners to spot differences among them. The reason I think of this puzzle is that AI is classified in many ways. It is divided into subfields with respect to the tasks AI is used for such as computer vision, natural language processing, forecasting and prediction, with respect to the type of approach used for learning and the type of data used. Subfields of Artificial Intelligence have much in common which makes it difficult for beginners to clearly differentiate among these areas. Different approaches of AI can process similar data to perform similar tasks. For example Deep learning and SVM both could be used for object detection task. Both have pros and cons. In some cases Machine Learning is …