The number of education options available to would-be data scientists starting their careers has risen dramatically over recent years. Business and academia alike are seeking to take advantage of the rising demand for data science professionals, and have made effective use of innovations in online learning to do so. These learning options are roughly divided into two groups:

Over 40 years ago, in 1978, the academic paper that coined the term ‘impostor phenomenon’ was published. In this case, the term, which referred to a perception of fraud or phoniness by a person experiencing success in a senior business role, was being used to describe the way high-achieving women were feeling in what was a male-dominated business world.

As you walk towards your car you type a text message on your smartphone. After you tap the first two or three letters of each word the phone constantly suggests potential words you might be looking for. Once a few words are on the screen, it starts making suggestions for the next word before you even begin to type.

Machine learning technology has made major advancements over the last ten years, turning concepts that were previously relegated to science fiction into real-life applications. But this progress isn’t the result of a single innovation in how to teach machines, it represents the combined achievements of many different approaches to the discipline. In this article, we’ll discuss the four machine learning concepts that sit at the heart of machine learning: supervised learning, unsupervised learning, deep learning, and reinforcement learning.

What started as a means of making people laugh turned into a coronavirus coping mechanism before becoming the most viral sensation of 2020. Made up of short video clips typically set to audio clips of music or movie scenes, TikTok has taken the attention-capturing short-form video format from Vine and claimed its top spot among social media apps.

Financial Technology (FinTech) is a rapidly growing industry. If you have professional experience in finance, or a keen interest in disruptive technology, there’s a good chance FinTech might interest you as a career.

Perhaps you’ve been wondering how to create a FinTech startup or how to build a FinTech app. You might even be thinking about taking advantage of changes in legislation to start your own FinTech bank. Maybe you’re simply considering how you can start a career in FinTech generally.

According to a PwC survey, 88% of large, well-established financial institutions (incumbents) feel that part of their business is at risk to standalone financial technology (FinTech) companies. Incumbents appeared to be immune to competition from startups for a long time; they had loyal long-term clients and the systems in place to manage constantly-evolving and onerous regulations.

The role of Chief Financial Officer (CFO) is highly valued for the success of an organisation. The CFO role requires specific technical and soft skills developed through professional experience and postgraduate education, such as the online Master of Applied Finance at UNSW.

User Interface (UI) design has long been a priority for the computing industry, as companies have sought to differentiate themselves from their rivals by making their products easier to use or by providing new ways to use them. However, until relatively recently, the evolution of UIs was limited by the fact that the only meaningful way to use a computer was through mouse clicks, keystrokes, and screen touches. 

For talented and driven individuals, opportunities abound in the booming data science and analytics field. Career paths are broad and varied and cover almost every industry.