Looking for the right ways to turn to data science? Well, those degrees will give you a huge advantage. And definitely a degree at C-S qualifies you for this satisfying and demanding career. Welcome to this 3-6-5 series of videos on data science where we will explore how to get into data science. We’re going to make the transition from Computer Science today and discuss the steps that you need to take to join one of the hottest career areas. We’re going to answer some of the most important questions that go through your brain, like: “Can I,” “Should I” and “How can I” make this changeover.
We’re going to talk about the pros and cons and give you some tried and tested tips for moving into data science. Let’s start with “Can I make the changeover? “Well, no one else can, if you can’t. A degree in C-S trains you to be a code-savvy professional with good critical thinking, and a passion for innovative software solutions-making you the top choice for employers in data science. you score : The first and the most important advantage a C-S background gives you is spectacular problem-solving skills. Computer scientists excel in times of difficulty. And the resolution of complex issues is just a daily part of their lifestyle! In essence, what they do every day is recognise a issue,
Translating it to your computer, and finding the smartest way to do it. Then again and again. A graduate of C-S rushes in and seeks approaches where others are scared to tread making them a leading figure in every data science team. Second-Writing a code which others can access and understand. This is one of the most important skills for someone who works in data science. What is that for? For one thing it saves everyone associated a lot of time. If your code is hard to follow, nobody’s going to want to use it..
Especially in a fast-paced business environment where teammates from data science should be running like a well-oiled machine. On the other side, volumes is spoken by writing readable code that follows best practices. It shows you are excellent at communicating to others your way of thinking, which is undeniably important for a data scientist working within a cross-functional team. You obviously know how to do that as a C-S person so this box is ticked! And third – to provide an incredibly flexible toolbox. Data scientists never travel solo. That said, the ability to work with TTD or version control systems, such as Git, is important to manage the code:
Including past updates, pace of execution and project creation. A data science team needs someone who knows how to track the timelines or test if the code is properly labeled. Not many people are highly skilled at that, but a graduate of the C-S has the understand-how that gives them an edge for sure. Just perfect. We believe you now know that transitioning from computer science into data science is not a matter of “Can I? “Instead of” Will I? “Well, each person is different, their career choices are different. Data Science has been “discovered” recently and it seems a challenge to give it a worldwide definition. Comprehending the data science industry is a difficult task because of that..
We might conclude that becoming a Data Scientist in most cases would allow you to work in a unpredictable, constantly evolving and demanding environment. And, yes, there wasn’t a Data Science work 20 years ago … So you can wonder “Why? “The biggest explanation is that there wasn’t that much evidence to deal with. Yet now this is not the case. There are 2.5 quintillion bytes of data generated daily and companies are in desperate need of people working on it to better our lifestyle, wellbeing and more … However, the demand for data science talent is so high that it will be difficult for the supply to catch up for many years to come! It also describes the annual base salary of $100,000 + and why statistics like Glass door’s 50 Best Jobs have consistently named Data Science the winner for the past few years.
Consider this – today’s data science is very similar to how computer science was viewed back in 2005. Currently D-S and C-S are very close in that they obey the same laws of demand and supply … but only with a delay of 20 years. And, you might might as well take advantage of that before the market is overcrowded with highly qualified data scientists and wages start plateauing up. So, how do you do it? Knowing how to code you’ve already put the DS job on the fast track. In terms of intelligence, what you might skip is: Statistics –Computer scientists boast a deterministic mentality.
This drives them to want to have explored all the possibilities. And that’s fine, but for you to be a data scientist, you need to switch to a statistical or even better mentality – a probabilistic one. Why? For what? Ok, regardless of how data science works-things obey distributions and for every probability there are probabilities. So, adapting to that is a whole new way of thought. Computer and machine learning are typically not included in the C-S program, you were correctly. But it will offer you a huge competitive edge, namely sharp predictive modeling skills and advanced deep learning technologies.
Fortunately, there are plenty of post-graduate qualifications and online trainings that will help you get there.