As a data analyst, your job is to help stakeholders derive meaningful insights from data. Although many data analysts use math, statistics, and probability on a daily basis, data analysis is actually both an art and a science. By carefully choosing the colors, labels, and format of visualization, you can lead people to notice outliers […]

When will demand for a certain product spike during the holiday season? Can we detect fraudulent ordering patterns? How do we reduce wait time in the call center? These are all questions machine learning (ML) engineers can answer through Amazon Web Services (AWS), a comprehensive cloud computing platform that creates accurate and scalable ML predictions, […]

UX writing is the practice of creating user interface (UI) copy that guides users within a digital product. The purpose of UX writing is to provide a smooth and intuitive user experience while minimizing friction. Friction occurs when an interface is confusing, important items are hard to find, or the user isn’t sure what to […]

Most user experience research falls into one of two categories: quantitative research and qualitative research. While both are concerned with data collection, gaining insight into the problems that might exist within a product or service, and understanding the experience of users, the qualitative approach is more focused on understanding user motivation and behavior.  Where quantitative […]

The best design is the design that knows its users. When it comes to creating UX designs that feel easy, functional, and intuitive, teams should aim to create experiences with their ideal audience in mind. It’s more than just anticipating a user’s needs and pain points, it’s actually more about understanding who your specific user […]

If you’ve spent some time browsing technical job boards, you’ve likely noticed the word “agile” appear in quite a few job descriptions. The Agile methodology is a popular concept in the technical world—and while it’s most commonly used in the software development cycle, non-engineer teams also frequently rely on the method as a framework to […]

According to Gartner, 85 percent of machine learning projects fail, leaving most organizations without a positive ROI. To avoid spending unnecessary time, money, and energy reinventing the wheel, many organizations have started employing machine learning frameworks. These frameworks simplify the process of algorithm development for engineers, making ML easier, more scalable, and more accessible.  Machine […]

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