Though you’ll hear near universal praise for data-driven decision-making, many companies haven’t yet been able to put such a strategy into practice. Why? Well, one barrier, acknowledged by 75 percent of marketers
surveyed by Econsultancy last year, is that too few in the marketing realm have the requisite training and education on data and analytics, particularly in the areas of artificial intelligence (AI) and machine learning.
This situation leads both to hiring challenges and to great opportunities for those who possess or can develop the necessary skill set.
If your company or agency doesn’t already have training programs in place, you’d do well to take matters into your own hands, as there are myriad online offerings that allow you to school yourself on the latest technologies. And they’re not all oriented toward programmers, meaning they can help marketers understand the best use cases and necessary building blocks for employing machine learning and AI to best advantage.
The retail giant decided this week to open up its internal training programs to the wider world. Though Amazon’s own AWS offerings are a focus of a lot of the tutorials, these more than 30 self-service self-paced free digital courses also cover more general concepts that can be applied on other platforms.
The path most suitable for marketers will likely be the one aimed at business decision-makers and perhaps, for the geekier among us, those for data scientists.
Dr. Matt Wood, shown here in his Twitter profile image, heads up AI and machine learning for Amazon Web Services
“Regardless of where they are in their machine learning journey,” wrote AWS’ GM of AI, Matt Wood, “one question I hear frequently from customers is: ‘how can we accelerate the growth of machine learning skills in our teams?'”
Each training path progresses from courses aimed at defining and demystifying artificial intelligence, to classes that explore specific applications of such technologies (using AWS applications, natch). Each course is labeled as foundational/fundamental, intermediate or advanced, so you can proceed at your own pace.
Example courses:
Demystifying DL/ML/AI (fundamental)
Machine Learning for Business Challenges (fundamental)
Machine Learning Use Case: Call Center (fundamental)
Communicating with Chat Bots (intermediate)
Just as Google offers its own cloud services related to machine learning and AI, it also aims to educate developers and business decision-makers about the technologies’ capabilities.
The Google resources include everything from videos to hour-long courses to example code and hands-on guides. As with Amazon, you can select your role to find resources that are most likely to be useful, at the correct depth and applicable to the stage of the AI/machine learning process you’re engaged in. The options here that seem most applicable to marketers include: business decision-maker, data scientist and … curious cat.
Example courses:
Yufeng Guo uses down-to-earth examples to explain AI concepts.
Finnish business consultancy Reaktor, which works with clients like HBO, Airbus, Nokia and News Corp, collaborated with the University of Helsinki to put together this in-depth online course series, which begins with “What is AI” and continues to explore both the applications and implications of the technologies.
Though the curriculum is designed, according to the site, to expect no pre-existing knowledge beyond basic math, the courses will require a significant commitment. Going through the entire series is expected to take 6 weeks or more — though the designers recommend setting yourself a 6-week deadline to get the most out of the material. Each of the six parts is designed to take 5 to 10 hours, depending on how much you explore related links.
Unlike some of the other possibilities, Elements of AI is completely text- and image-based — though there are sections that ask you to interact by making a drawing, taking a quiz or doing something similar — and therefore it may be more difficult than getting a grasp on these concepts with the help of video.
It’s also structured as one course for everyone, regardless of their business role or area of interest, which inevitably means that it’s more general. The positive there is that it’s a great easy-to-understand primer, and you can even get credit for taking the course through the University of Helsinki’s Open University program.
Example courses:
AI Problem Solving — which uses a search engine as an example
4. Resources on MarTech Today
Though we don’t have hour-long courses or quizzes, MarTech Today (Marketing Land’s sister site) is a great place to get specific information on how AI and related technologies can be applied to marketing problems. Following are some of the foundational articles that will help you get up to speed.
And some more advanced articles about putting AI and ML to work for you:
You’ll also find that our Machine Learning & Artificial Intelligence archives hold a wealth of valuable information for marketers.
Do you know about other great resources marketers can use to teach themselves about AI and ML? Send them along and we’ll consider adding them to this guide.
This article originally appeared on MarTech Today, where you can find much more coverage of marketing technology.
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