Artificial intelligence is the new electricity. Data is the new oil. You would be forgiven for thinking these statements were hyperbolic, but they’re not as far off as they might first appear. The applications of AI-powered analytics reach across practically every sector. Over a third of organizations have already deployed AI-based processes. Analysts forecast global spending on AI to grow 25 percent in the next four years, from $85 billion in 2021 to $204 billion in 2025.
AI isn’t coming to take your job, but it’s probably going to change it. Early indicators suggest that an AI-powered future is one where humans and intelligent technologies work collaboratively. But the largest barrier to realizing that future and the further advancement of AI is the current dearth of talent in the field. This goes beyond the lack of AI engineers: Deloitte’s 2020 State of AI in Enterprise Survey—the latest data available as of June 2022—found that the most significant corporate need was finding more AI-literate business professionals.
Thanks to online degree programs and DIY skill-builders, it’s never been easier to get started in artificial intelligence. Educational options are available at every possible starting point: from the working software engineer to the absolute layman.
Read on if you’re ready to explore this dynamic, impactful, and rewarding career.
Lewis University (MS Computer Science)
Lewis University offers an online MS in computer science program with a concentration in artificial intelligence. Students learn how to design and implement computing systems that perceive, act, and learn.
Concentration courses cover artificial intelligence, natural language processing, robotics, statistical programming, and machine learning. Each class goes in-depth on multiple technical areas, including Bayesian networks, Markov Decision Processes (MDPs), and reinforcement learning control. Before graduation, students will design and conduct a faculty-advised research thesis that results in publication-worthy documentation. The program consists of 33 credits.
Stanford University (Graduate Certificate)
Stanford University’s online graduate certificate in artificial intelligence gives students a chance to learn from the leaders of the artificial intelligence revolution. The curriculum covers both foundational and advanced skills in the principles and technologies that define artificial intelligence.
Designed for working software engineers, the program is fast-paced and academically rigorous. Applicants should be able to demonstrate mastery of mathematical and programming prerequisites. The program takes an average of one to two years to complete.
Colorado State University (MS Artificial Intelligence)
Colorado State University’s online MS in artificial intelligence and machine learning teaches students how optimal system analysis and design can solve complex, organization-wide issues. The curriculum addresses the latest deep-learning libraries and technologies and how they can be applied in various industries.
Courses cover topics such as the design and analysis of algorithms; the foundations of artificial intelligence; the foundations of computer vision; principles of machine learning; and neural networks. The program consists of 39 credits.
Massachusetts Institute of Technology (Professional Certificate in ML and AI)
MIT Professional Education offers a professional certificate in Machine Learning (ML) and Artificial Intelligence (AI). This program aims to meet the rising needs for AI-knowledgeable professionals to help organizations leverage the power of ML safely and efficiently. This course requires 16 days to complete and is designed for computer science professionals with or without bachelor’s degrees.
Once registered, students take classes online or on-campus at MIT during the summer months. Once students complete their qualifying course, they have 36 months to complete additional courses. Core courses include machine learning for big data and text processing: foundations or advanced. Elective courses include advanced reinforcement learning and deep learning for AI and computer vision.
Johns Hopkins University (Graduate Certificate and MS in Artificial Intelligence)
The Whiting School of Engineering at Johns Hopkins University offers two online AI graduate programs. These programs include theoretical and real-world instruction on the applications of AI in robotics, natural language processing, and image processing.
To be considered for admission to either program, applicants must be able to prove coursework in calculator and statistics and computer programming languages such as Python. Once accepted, students in the certificate program must finish four courses within three years and can choose to apply credits earned in this program to the master’s degree. Students in the master’s degree program must complete 10 courses in five years and choose courses from the applied or theoretical AI tracks.
University of Michigan (MS in Artificial Intelligence)
The College of Engineering & Computer Science at UM offers a master of science in artificial intelligence. Students can complete on-campus, online, or a hybrid of in-person and computer-based learning. This 30-credit program offers four concentration areas: intelligence interaction; machine learning; and knowledge management and reasoning.
Applicants to this program must have a bachelor’s degree in a STEM field with an average GPA of B or higher and completed prerequisite courses in computer science, data structures and algorithm analysis, and calculus. To graduate, students must complete a coursework, project, or thesis final project.
University of Texas at Austin (Certificate in AI and ML: Business Applications)
The McCombs School of Business offers a six-month online certificate program in artificial intelligence and machine learning. Students in this program take advantage of online learning with live mentorship, career support, and project-based learning. Emphasis areas include applications of AI in neural networks and natural language processing.
Once admitted, students have access to a boot camp-style intensive course that teaches foundational basics. Students spend 8-10 hours per week on recorded lectures and live learning sessions. In addition, students learn from eight hands-on learning projects during the program, which can be used later as evidence of proficiency for career advancement.
Online education is evolving almost as quickly as artificial intelligence. Whether you’re looking for a quick level-up in a specific technical area or for a broader understanding of the field of artificial intelligence, today’s DIY skill-building is more accessible than ever before. These online modules are quick, cheap, up-to-date, and, in some cases, attached to heavyweights of industry and academia.
Coursera is an online learning platform co-founded by AI revolutionary and Stanford professor Andrew Ng.
As a repository of Massive Online Open Courses (MOOCs), Coursera has one of the most extensive offerings of DIY skill-building options for artificial intelligence. Each course is sponsored by either a university or a corporation. As a result, students can choose between highly targeted classes like those offered by Google Cloud or generalized overviews of AI from IBM.
They can also mix and match: course packages range from individual classes to professional certificates to specialization tracks and full-on degrees.
Founded by Harvard and MIT, edX is an online learning platform that brings together over 20 million learners and partners them with top-ranked universities and industry-leading companies. Students can access low-cost courses in artificial intelligence that come backed by Harvard, Columbia, IBM, and the University of Pennsylvania.
Groups of courses can culminate in MicroMasters degrees and professional certificates or be taken a-la-carte to boost a particular skill set.
Google offers free online certificate programs in machine learning (ML) for true beginners and seasoned professionals. For example, in their “Using AI for Social Good” course, participants learn to understand organizational problems that they can solve with ML and how to identify and prepare data sources to implement ML responsibly.
Examples of socially conscious projects that can leverage AI include flood forecasting, plant disease, wildlife conservation, and more.