The explosion in data collection and storage in every aspect of modern life has been, and will continue to be, astounding. The ability of businesses, governments, and other entities to collect and store small, discrete details about everything from package movements across oceans to the number of times a coffee maker is used in the 4th floor lounge has created a huge demand for storage capacity… a demand that International Data Corporation forecasts will grow to an eye-popping 175 zettabytes by 2025.
Massachusetts Institute of Technology - MIT Sloan Machine Learning in Business - Incorporate machine learning into your business strategy, and explore the value and impact of this technology.
For managers in the firms collecting this information, one inevitable question arises: How do you marshal that data and put it to work?
There is no doubt about the power of big data, but without the systems and know-how to manage it, data collection on that scale can present as many problems as it solves – problems of storage, processing and compliance.
That’s where a short course in machine learning comes into play.
How Understanding Machine Learning Makes You a Better Manager
Machine learning (ML) is one of the premier tools for making use of very large datasets, but it’s a complex subject, steeped in math, theory, and code. It’s an applied aspect of artificial intelligence that allows algorithms to adjust and reshape themselves so as to rapidly assess very large datasets and draw out insights.
By taking human analysts out of the loop, data scientists have achieved major successes in developing self-learning algorithms that exceed the performance of people. One striking example of this came to light in 2019 when a model developed to analyze lung cancer x-rays handily outperformed experienced, professional radiologists with up to 20 years of experience.
Integrating machine learning into business operations can have similarly impressive results, giving companies in any industry a real competitive edge. This means the race is on to identify areas where the technique can be applied and recruit the machine learning experts capable of doing it.
While corporate executives can’t become experts in implementing machine learning techniques, they do need to understand its capabilities, limitations, and requirements, not to mention the vocabulary used to explain it all.
What to Look for in Short Courses on Machine Learning for Managers and Executives
A short course in machine learning could be just the ticket for achieving that level of understanding. Offered by top universities with rock star faculty, and with virtually the same types of courses found in the cutting-edge tech-focused business graduate programs these schools offer, short courses like this will help you keep your head above water in the rapidly evolving world of technology management.
Most short courses won’t last much longer than a month, and most will be offered online, making it easy for you to cover the material in your own time, without impacting your other commitments.
Short courses in machine learning are often created by top universities, including the biggest names in the Ivy League, and made available through popular course aggregators like edX and GetSmarter, as well as directly through the universities themselves via their own platforms. In a lot of cases, this makes identifying a rigorous program as easy as simply considering the reputation of the school itself.
Some of the courses are carved directly from longer certificate programs in data science, allowing you to focus on one specific aspect like machine learning.
Because machine learning is a new field that is still in active development, your best education will come from schools like MIT or Stanford that are pioneering the field. Although you won’t participate in some of the major industry partnerships that such schools bring to the table, your instructors will, and you’ll have the benefit of their experience. These courses make getting an education from very exclusive schools much more accessible.
Instructors are particularly important in such short format classes, so it pays to check the credentials, research specialties, and publications of the professors. Many schools actually promote their programs by showing off their esteemed faculty, so learning about who you’ll be learning from typically only requires that you check out the school’s short course page.
What You Can Expect a Short Course in Machine Learning to Cover
You should expect a course to cover elements of machine learning that include:
Data and sensor requirements – Machine learning algorithms aren’t appropriate to every data problem, and their success can rely to a great extent on the source and quality of the data fed into them. As a manager, you’ll be the person with the resources for developing and improving data collection in your organization, so you’ll need to understand how that affects your machine learning efforts.
Natural language processing – One of the hottest applications for machine learning can be found in the development of AI capable of understanding natural language patterns, whether spoken or written. In a short course in machine learning, you’ll get an overview of the state of the art in this constantly improving field.
Hidden pattern identification and matching – Another strength of machine learning is identifying trends and patterns that a human investigator might never even think to look for in the data… the famous Deep Patient machine learning analysis of patient data at Mount Sinai was successful at predicting diseases that investigators were looking for, such as liver cancer. But it also accurately predicted schizophrenia at a high rate… an unexpected, and still unexplained ability.
Algorithmic bias – Machine learning is not magically successful in every instance. The initial algorithms are crafted by people, and their flawed assumptions can lead machines to flawed conclusions. You’ll learn about failures in creating accurate facial recognition machine learning caused by biases built into the data it was trained on, and how to avoid issues like overtraining.
Operational integration issues – In 2018 the European Union passed the General Data Protection Regulation. One of the less-heralded components of that omnibus package was to give EU citizens a right to explanation of the outcomes of automated decision-making that affects them. But such explanations may not be readily—or ever—available, or even understandable, since they are the result of deep machine learning processes that may be too divergent from how people think and communicate. Executive leaders in organizations that want to take advantage of machine learning have to understand how the technique may disrupt both traditional in-house decision-making processes as well as create legal complications.
Since these courses are so brief, consisting of just over a month of classes and only six to ten hours per week, you shouldn’t expect a deep dive into any of these topics. But an overview of the issues is critical, and you can shop around to find courses that go more or less in depth on the areas you want to focus on without spending too much time on those you don’t.
Going Online for a Machine Learning Short Course
As is only appropriate of programs that are both centered around technology and designed specifically for busy professionals, you’re going to find these kinds of short courses widely available online.
You can find them on platforms like Coursera, edX, or GetSmarter in partnership with outside universities, or sometimes delivered directly through the university itself.
One of the major advantages of taking these courses online is asynchronous course delivery. Not only does this offer the flexibility every working professional needs, it is one of the keys to making the most of your experience. Fitting your classwork into the slots in your schedule when you’re available and able to focus strictly on the course material can really optimize what you take away from the experience.
You can expect to access that course material through platforms designed to keep you plugged in and engaged, with Slack channels, virtual blackboards, digital libraries, and other high tech approaches that keep instructors and students on the same page.
The Long Term Career Benefits of Taking a Short Course in Machine Learning
A short course in machine learning isn’t going to make you a data science expert or earn you an instant promotion to the C-suite if you’re not already there, but it will have positive impacts on your career and salary in any industry, at whatever level of management you happen to be in.
The incredible potential of machine learning in managing big data will only become more important as that data accumulates.
Having the extra experience and expertise in ML that a short course can give you will make you the voice in the room that others will listen to when the hard problems of data analysis and AI come up.
And being that person has real benefits, according to Robert Half, a staffing and consulting firm that has been tracking salary and job trends for more than 50 years. In their 2020 tech industry salary guide, they explain that the top 5 percent of earners in any given job category are distinguished by the experience and expertise they have beyond the average worker. And there is no better way to gain that kind of expertise quickly in the area of machine learning than through a short course.