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However, 90% of your work as a data scientist will be cleaning data. It’s tempting to get carried away learning specialized topics, like machine learning, neural networks, and image recognition. Take control of your learning by tailoring it to your goals, not the other way around. When you learn by doing, you retain information longer, and you gain experience you can rely on in the future.
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To learn how to do this, I dove into statistics with a passion, and it helped motivate my learning experience. Identify your motivation, and use it to guide your data journey.įor me, this was completing a stock market prediction program.
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The secret to navigating all this information is a reason to learn. That means it can be difficult to determine what you should focus on. The data science field is very broad, and there’s a tremendous amount of available information. So what’s the most effective way to learn data science? I’ve broken it down into five easy steps. However, studies show that most people learn best by doing, not by watching videos or memorizing textbooks. That’s a complicated question - I know from experience. A few years ago, I decided to pursue a data science career, but when I researched what I needed to learn, all I could find were long lists of data science courses to take and books to read.
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The demand for data scientists is at an all time high. If you’re considering a career in data science, now’s the best time to get started.īut what’s the best way to learn data science? ApHow to Learn Data Science in 2022 (A CEO’s In-Depth Guide)