are programmers good at math?
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You don't have to be good at math. However, you have to be good at logic, and problem solving. However people who are good at logic and problem solving are usually good at math also. ... But if you have trouble with Discrete Math and Set Theory, you would probably find a lot of aspects of programming quite hard.
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Creativity is not just something owned by artists, creativity is required across all disciplines. And many artists have mathematically profound knowledge too. ... Creative people aren't bad at math. They are bad at math in school, but that doesn't mean they are bad at math.
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INTP's also have the highest IQ on average, so most have advanced cognitive ability. ... Some INTP's are not good in math, whether they just don't care about it or if it's not what they're good at. But INTP's often try to learn, if they have interest in trying.
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Specifically, computational skills are defined as the abilities to calculate basic addition, subtraction, multiplication, and division problems quickly and accurately using mental methods, paper-and-pencil, and other tools, such as a calculator. This requires the selection of the appropriate arithmetic operation.
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In short, programmers focus on creating functional code, while software engineers design software from an engineering perspective with consideration for end-users, clients, and business needs. Software engineers are also programmers themselves.
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People who are good at mathematics are usually intelligent when it comes to the logical intelligence sphere hence some assume that there is a correlation between a math grade and a person's IQ. ... Mathematical people tend to be good at physics, chemistry, and other sciences because they are logical and often math based.
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Quantitative aptitude includes operations related to logic and expressions whereas numerical ability relates to numbers. A particular problem can be solved by both quantitative aptitude and numerical ability which depends on the skill set of the solver.
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Yes, Jeff Bezos does know how to code and therefore can be called a 'programmer'. Like many CEOs of tech companies, Bezos was always what people would call a bit of a nerd.
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['Mathematician.', 'Statistician.', 'College Math Professor.', 'Actuary.', 'Market Research Analyst.', 'Economist.', 'Aerospace Engineer.', 'Financial Analyst.']
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Generally, because of our NF combo, we don't naturally gravitate toward hard subjects like chemistry or math. ... But, given that my theory has no weight to it all (which it probably doesn't because, well, it's a theory) - then no, INFJs don't always have to be generally bad at math.
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AI won't replace programmers. ... Of course, it will take time before AI will be able to create actual, production-worthy code that spans more than a few lines. Here's how AI will impact software development in the near future.
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Learning to code for designers is not necessary. But if they know a bit about code, they can understand a developer's perspective. It doesn't mean that they have to be an expert coder. But it would greatly benefit them if they knew a little about how to code HTML and CSS, maybe a little bit of JavaScript.
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UX designers don't necessarily need to code at an expert level, but it's ideal for one to learn enough to establish an understanding and appreciation. ... Sure, if you're curious about learning a language like PHP, Rails or Python, it's not going to be time wasted—learning a new skill rarely is.
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You will have to have a good foundation in calculus, linear algebra, and statistics in order to help you to develop algorithms. You will also need a good knowledge of Python and Python for data science track as it is the predominant language used in machine learning.
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Any computer program is basically composed of if-else, go-to and arithmetic operations - that's how computer works. So, if you ask about AI in terms of computer programming, there's no difference at all.
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There's no such thing as an all-around perfect programming language. The best language can do is hope to do one or two things better than all the other languages around. For Go, the most obvious strengths are clear. Its ease of use, combined with its high adoption at Google makes it a promising young language.
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Mastering mathematics is helpful in almost any career. Learning math helps workers analyze and solve problems—abilities that most employers value. And math teaches other important practices, including how to approach tasks methodically, pay attention to detail, and think abstractly.