Recently, I wrote a blog post stating that I’m starting to use Python for most of my data science work. And I’m starting to recommend Python as the data science language to use for most beginners. But is it always best? No. As always, it depends: As I like to ask people: “Who are you … Read more
There are multiple data science languages to choose from. The most popular being R and Python. Many people will tell you to learn both. Learn R AND Python. I think this is probably terrible advice. Let’s discuss why. “Learn Them Both” And Other Bad Ideas There are multiple data science languages that are available to … Read more
Data visualization is extremely important in data science. Although you often hear about the importance of data manipulation (i.e., “80% of data science is data manipulation”), data visualization is just as important. I explained why in a recent blog post about why you need to master data visualization. That blog post has a detailed explanation … Read more
If you’ve been reading the Sharp Sight blog for a while, you’ll know that I’m a big fan of elite performers: Navy SEALs, grandmaster chess players, elite athletes, etcetera. I want to understand how elite performers operate across multiple disciplines, so that I can find what makes them special. The techniques. The training methods. The … Read more
One of the biggest questions from data science students is what to focus on. All of us have limited time and there is a lot to learn in data science. Many overzealous students throw caution to the wind, and immediately try to learn advanced topics like machine learning. As I’ve said many times, this is … Read more
If you’re interested in data science and want to become a data professional, you’re probably going to need to make a choice. I think that the industry is going to split – and in fact, it probably already has. This split that I’m referring to is the divide between the top performers – the top … Read more
Here at Sharp Sight, we teach data science. And in particular, we show people how to master data science extremely fast. Exceptional results, as fast as possible. Our training methodology borrows heavily from elite performers and “ultra learners,” wherever we can find them. But our promise of “exceptional results, as fast as possible” sometimes confuses … Read more
Here at Sharp Sight, I frequently use the word “fluent” to describe an ideal skill level with data science. When you join our courses, our goal is to help you become “fluent” in data science, or “fluent” in a particular skill. We want to help you become fluent in data science as fast as possible. … Read more
One of the common questions that I get from my readers is about “big data.” This is particularly true of beginners, who frequently read or hear the term “big data,” and think that it’s extremely important, and that being able to work with big data is necessary for a job in the data industry. For … Read more
This tutorial will show you how to use the NumPy mean function, which you’ll often see in code as numpy.mean or np.mean. It will teach you how the NumPy mean function works at a high level and it will also show you some of the details. So, you’ll learn about the syntax of np.mean, including … Read more