The good news for software engineering students is that the job prospects have never been better. Today, every company is a software company, no matter the industry or what it sells, so demand for your skills remain high.
But in addition to keeping up-to-date with an always changing technology industry, there’s a new type of intelligence that today’s students need to succeed—the artificial type.
Artificial intelligence (AI), machine learning, chatbots. These are not only some of the hot new areas of software development, but they’re also the future of the industry. Now that we can train software to perform tasks that previously required human intelligence—like recognizing patterns, speech and images—companies can predict outcomes, provide better customer service, or gain greater insights. The value of AI can’t be overstated and it’s being used everywhere, from providing personalized customer advice to banking customers and predicting potential product defects, to increasing airport safety and identifying potential cancer treatments.
Today and well into the future, data will be king. All these AI apps revolve around data—the more, the better—and require data scientists to develop algorithms to make sense of this data, enable it to be analyzed and allow the apps to think like humans. It’s critical to know how to leverage open source programs for gathering data from multiple sources, managing it and building the AI algorithms.
The new world of data
According to a study by IBM, by 2020 the number of annual job openings for all data-savvy professionals in the United States will increase from 364,000 openings to 2,720,000. So, what does that mean for you and how do you need to prepare for this new world of data and analytics? Here are some ways you can increase your value and marketability when you graduate:
- Shift your mindset. Today it’s really all about business. The days of developing sophisticated and elegant programs because you could, are over. Now, the most important criteria for an app is how it can solve real-world problems and help to move a company’s business forward. That means understanding the needs of a business and how technology can be applied to address critical needs.
- Learn about open source. Understand how it works and how you can contribute to it. Open source will be a critical tool, and essential for developing Deep Learning apps, which are the future of AI and have the ability to teach themselves.
- Gain math knowledge. So much of developing AI apps involves math. You need to develop algorithms and determine probability. Now’s the time to not only brush up on your math skills, but also take higher-level courses.
- Go deep. Knowing a little about a broad range of technologies is helpful to have a good overview of the industry, but the real value is developing deep knowledge in a specific area, such as deep learning, web development, or front-end development.
- Take master’s level or online courses. Many universities provide a good overview into the new technology, but don’t offer a deep dive in any of them. To get a leg up in the market, supplement your studies with online learning or some master’s level courses. It’s a good habit to get into since remaining relevant and valued in technology requires ongoing, lifelong learning.
As software engineering students begin a fresh new academic year, it’s time to not only enter the classroom with brand-new materials, it’s also time to gather new skills in emerging areas such as AI, machine learning and deep learning—as well as keeping an eye toward a practical, business-oriented approach to technology. It’s a winning strategy that will increase your value and marketability for years to come.