Leveling Up: How to Build Artificial Intelligence Skills
Artificial intelligence is not just sci-fi anymore. It is big business—one with billions of dollars in global funding. While modern AI has a 60-year history, it is only in the last couple of years that we have seen its introduction to the mainstream, with revolutionary applications in healthcare, sales, manufacturing, and transportation coming online, and widespread adoption just around the corner. What started out as a game of checkers is now responsible for self-driving cars, increasing farmers’ crop yields, and understanding the global oil supply.
Despite what dystopian fiction might have us believe, artificial intelligence is expected to create more jobs than it eliminates. Even though there is some mimicry on both sides, humans and computers are inherently different—and excel in different capacities.
Computers and their algorithms are adept at analyzing vast pools of data and unstructured information, while humans have the necessary intuition, imagination, and pattern recognition to point those algorithms in the right direction. As the capabilities of technology increase, the human element is needed to steer AI towards new horizons of applications with real-world impact.
Fortunately, it has never been easier to crack into the field. Artificial intelligence certificate programs, university curriculums, and online learning modules are cropping up with increasing regularity and offering to boost the skill set of engineers and non-engineers alike. As a result, it is now possible to learn from the brightest minds in the industry, regardless of physical location and availability. Read on to learn how to level up your skills in this rapidly emerging and lucrative field.
Fast Facts About Artificial Intelligence
AI is widely applicable
One of the buzz phrases of the last two decades was that, “Every company is a software company.” It might not be long before that phrase replaces “software” with “AI.” From banking to agriculture, by way of manufacturing and maritime trade, applications for AI are in virtually every sector of business. Those with the skills to harness the power of AI can pick their industry, changing the world in whichever area interests them most.
AI is future-forward
According to top research and advisory firm Gartner, AI will create 2.3 million jobs in the next two years. PwC also reported that AI firms seized more than $5 billion in venture capital funding over the last two years. The field is ripe for growth and will only continue to do so, notes Deloitte.
AI is location-independent
Like engineering, artificial intelligence is not anchored to a specific location, and neither are the AI experts. Working in AI requires prudent database management, clever algorithmic development, and a keen understanding of which questions to ask—all skills that can be performed from anywhere in the world with a steady connection to the internet.
Three Artificial Intelligence Gurus to Know
Thomas Malone, PhD – Massachusetts Institute of Technology
Dr. Thomas Malone is a professor of information technology and the founding director of the Center for Collective Intelligence at MIT’s Sloan School of Management. He is the faculty director of the school’s one-course program on artificial intelligence and its impacts on business strategy.
His landmark book, The Future of Work, synthesized two decades of his research into organizational theory and information technology. He holds 11 patents, has co-founded three software companies. He has also written extensively and is frequently quoted in major media outlets such as Forbes, The New York Times, and Wired.
Dr. Malone holds two master’s degrees and a doctorate from Stanford University, in addition to degrees in applied mathematics, engineering-economic systems, and psychology.
Michael Shamos, PhD, JD – Carnegie Mellon University
Dr. Michael Shamos is a distinguished career professor in the School of Computer Science at Carnegie Mellon University, where he is also director of the master of science program in artificial intelligence and innovation.
Upon first being hired as an assistant professor at CMU, Dr. Shamos was nicknamed the “czar of computer programming courses” while teaching a graduate class in algorithm analysis. Throughout his career, he has published many scholarly articles and secured numerous patents. His role as director of CMU’s new master’s program places him at the forefront of the discipline’s entry into traditional academia. Dr. Shamos obtained his doctorate in computer science from Yale in 1978, writing his thesis on fundamental algorithms in computational geometry.
Vivienne Sze, PhD – Massachusetts Institute of Technology
Dr. Vivienne Sze is an assistant professor in the School of Electrical Engineering and Computer Science at MIT, where she also teaches a professional education course in designing efficient deep learning systems. Her research focuses on the joint design of algorithms, architectures, and circuits to build energy-efficient and high-performance systems.
She has collected numerous awards, including winning the Jin-Au Kong Outstanding Doctoral Thesis Prize in 2011, being named one of engineering’s ‘new faces’ by the IEEE-USA in 2012, and earning an Engineering Emmy award in 2017. Dr. Sze completed her bachelor’s degree in electrical engineering from the University of Toronto and her master’s and doctoral degrees in electrical engineering and computer science at MIT.
Degree and Certificate Programs in Artificial Intelligence
CMU’s master of science (MS) in artificial intelligence and innovation degree is the first of its kind. The five-class core curriculum, which includes a capstone project, is specifically designed to uncover new AI applications and develop them into a product suitable for development through classes in artificial intelligence for future markets, law and computer technology, competitive engineering, and enterprise development.
The six-class knowledge module involves courses in applied mathematics, machine learning, natural language processing, applied machine learning, deep learning, and a coding boot camp. Students must then choose three electives that dive deeper into nuanced areas. The 192-credit program can be completed in four four-class semesters. Tuition rates for 2018 are $25,000 per semester.
- Location: Pittsburgh, PA
- Duration: Two years
- Accreditation: Middle States Commission on Higher Education (MSCHE)
- Tuition: $26,900 per semester
Massachusetts Institute of Technology Professional Education
MIT has played a leading role in the prominence of AI across the global stage, and the institute’s professional education arm offers a certificate program in machine learning and artificial intelligence. The goal of the program is to empower businesses and individuals to be able to succeed in the AI era.
Students take two core courses: one in foundations of machine learning for big data and text processing and one in advanced machine learning for big data and text processing. Students may then choose two electives from advances in imaging (virtual reality and augmented reality, machine learning, and self-driving cars), designing efficient deep learning systems, machine learning for healthcare, or modeling and optimization for machine learning. The program consists of four classes that take place at MIT’s campus in Cambridge, Massachusetts.
- Location: Cambridge, MA
- Duration: 16 days
- Accreditation: New England Commission of Higher Education (NECHE)
- Tuition: $7,000 for two core courses
Massachusetts Institute of Technology
MIT’s Sloan School of Management offers a short online program in artificial intelligence and its associated implications for business strategy. Offered in collaboration with MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the program is designed to equip business executives with the knowledge they need to understand the organizational and managerial implications of artificial intelligence.
As it focuses mainly on the business strategy implications, no significant technical expertise is required. The one-course program lasts six weeks, with approximately six to eight hours of self-paced learning expected per week, and may be completed entirely online. The tuition is a flat fee of $2,600.
- Location: Cambridge, MA
- Duration: Six weeks
- Accreditation: New England Commission of Higher Education (NECHE)
- Tuition: $3,200 per six-week course
The Microsoft Certified Azure AI Fundamentals certification proves an individual’s AI skills and is recommended for those with general programming knowledge or experience. Courses teach the basics of machine learning and AI concepts and related Azure services to build deep learning predictive models for AI solutions.
After passing the exam, credential holders can share their certification badge and skills on social media platforms such as LinkedIn. Free and paid preparation courses are available to prepare for this exam which professionals can complete online.
- Location: Redmond, WA
- Duration: Self-paced; timeline varies
- Accreditation: Microsoft
- Tuition: $99 for a test prep course
The artificial intelligence group at the University of Washington Computer Science and Engineering (UW CSE) studies the computational mechanisms underlying intelligent behavior. Their research areas include machine learning, natural language processing, probabilistic reasoning, automated planning, machine reading, and intelligent user interfaces.
UW CSE is one of the world’s leading centers for AI research, as demonstrated by its track record at the top conferences in their field, individual student and faculty honors, and high-profile research collaborations such as its work with the Allen Institute for Artificial Intelligence (AI2).
The Allen School’s campus-wide leadership in data science is also worth mentioning. This burgeoning field intersects with AI in many ways; data science is concerned with all aspects of data management, analysis, and understanding. While the department doesn’t offer a degree, it does offer several undergraduate and graduate-level courses in AI.
- Location: Seattle, WA
- Duration: Courses offered in semesters
- Accreditation: Northwest Commission on Colleges and Universities
- Tuition: $12,076 per semester (residents); $39,906 per semester
Georgia Institute of Technology
The College of Computing at Georgia Tech has an extensive faculty and research interest in artificial intelligence (AI) and machine learning (ML). AI and ML are used to solve various problems, such as constructing top-to-bottom and bottom-to-top models of human-level intelligence, creating adaptive and intelligent entertainment systems, making systems that understand their behavior, modeling and predicting
human behavior, automating creativity, and addressing a variety of other problems.
At the undergraduate and graduate levels, AI and ML are mainly found in two threads: Intelligence and Devices. Commonly taken courses include Introduction to Artificial Intelligence, Machine Learning, Natural Language Understanding, Knowledge-based AI, Game AI and Pattern Recognition. In addition, several robotics and computational perception courses also have an AI or ML aspect. At the graduate level, Georgia Tech advises PhD and master’s thesis candidates researching AI.
- Location: Atlanta, GA
- Duration: Courses offered in semesters
- Accreditation: Southern Association of Colleges and Schools Commission on Colleges (SACSCOC)
- Tuition: $3,048 per semester (residents); $9,308 per semester (non-residents)
University of California, Berkeley
The Berkeley Artificial Intelligence Research (BAIR) Lab at UC Berkeley focuses on computer vision, machine learning, natural language processing, planning, control, and robotics. The lab has over 50 faculty members and 300 graduate students and postdoctoral researchers pursuing research in these areas.
Starting this year, the AI admissions committee will not consider GRE Scores in making decisions. The committee believes diversity leads to better research and decision-making, so they welcome applicants from all backgrounds to apply.
- Location: Berkeley, CA
- Duration: Courses offered in semesters
- Accreditation: Western Association of Schools and Colleges (WASC)
- Tuition: $5,721 per semester
DIY Online Artificial Intelligence Programs
Artificial intelligence is moving faster than traditional academic institutions can keep up. The future of education in the field is online and on-demand. And that is why some of the best educational programs in the area are available through cutting-edge online learning platforms like the ones below.
This elements of AI course, designed by the University of Helsinki, is an excellent place to get started for total beginners. The course aims to explain what AI is, what is and is not possible with it, and how it affects people’s lives. The program consists of six classes, which cover topics like defining AI, solving problems with AI, AI in the real world, machine learning, neural networks, and overall implications.
No heavy math or programming skill is required to take this course; upon completion, graduates of the course earn a LinkedIn certificate. The classes were developed in partnership with the Finnish Center for AI and The Open University, can be completed entirely online, and tuition is free.
Google Machine Learning Crash Course
Why not let Google give you a free AI and machine learning crash course? This 15-hour, 25-lesson class includes lectures from Google researchers, real-world case studies, interactive visualizations, and more than 40 exercises on the subject. Using TensorFlow, students learn about gradient descent, how to build deep neural networks, how to measure a created model’s effectiveness, and how to represent data so that an algorithm can learn from it.
While the prerequisites can be intimidating, there is a roadmap available for everyone, regardless of their starting point, and a healthy library of resources for self-study and further exploration.
Udacity was founded when two Stanford professors decided to host their introduction to AI course online and offer it to anyone for free. So it is only fitting that Udacity remains a reliable resource for DIY learning in the AI space.
The platform provides a three-month nanodegree on the subject spread out over 150 hours. Peter Norvig, a research director at Google, and author of Artificial Intelligence: A Modern Approach, teaches the class alongside Sebastian Thrun, the founder of Udacity who, before starting the online learning company, launched Google’s self-driving car project. To make graduates job-ready, the program focuses on four projects: building a Sudoku solver, building a forward planning agent, building an adversarial game-playing agent, and performing speech tagging. The program costs $999 and may be completed entirely online.
Coursera is an online learning platform that resembles a library of courses and programs in a wide variety of topic areas. Each module acts as an interactive digital textbook, complete with exercises, quizzes, lectures, and videos. In addition to programming classes that can bring students up to speed on their prerequisites, the platform offers specializations in AI that partner with institutions like Stanford University, New York University, and the University of Toronto.
Founded as a collaboration between MIT and Harvard University, edX offers online MOOCs and learning modules prepared in partnership with some of the best schools from around the globe. For example, as a part of its MicroMasters program, edX offers a 12-week course in artificial intelligence taught by a Columbia University computer science professor.
After learning the fundamentals of AI, students design intelligent agents capable of solving real-world problems in areas like search, logic, gaming, and constraint satisfaction. The course can either be taken for free or in the pursuit of a certificate for $199. Massachusetts residents who take the course will be guaranteed an interview in Boston for a full-time job or an internship with GE.
