Any non-technical professional who is interested in learning more about AI, machine learning, and data science - and would like to know how they can contribute to this field

More specifically: The course is for working professionals without a background in computer science or statistics, who want to develop the skill sets to compete in an economy where a working familiarity with the fields of data science, machine learning, and AI is increasingly essential.

This includes - but is not limited to - analysts, marketers, salespersons, managers, executives, or other stakeholders who regularly work with data.

No! This course has been specifically designed to be accessible - and immediately relevant - to working professionals who do not have prior experience in programming or machine learning.

You don’t even need to be particularly good with computers. The central idea behind this course is that you can leverage your existing skill set to directly contribute to data science projects, without spending months or years developing new technical skills or writing a single line of code.

While we could charge much more than we do, it is our mission to help as many people as possible become fluent in AI. Our research and my own experience has led us to the conviction that far too few people understand data science. This field is too important to be left to a small number of technical experts alone. That’s why we’re offering this course for only 197 dollars - so anyone with an interest can take it, regardless of budget.

We offer a 30-day, 100% money-back guarantee. If for any reason, find this course is not for you, we will refund the full cost of the course.

The world needs more non-technical people who are fluent in AI.

There is a tremendous need at nearly every organization for people who know how to leverage their existing experience and skill sets to partner with data scientists. Yet, only a very small proportion of working professionals who can do so. We believe this presents you with a tremendous opportunity to differentiate yourself and increase your market competitiveness, with a relatively small investment of your own time and energy.

Our own experience and research into the responsible and ethical use of AI - informed by industry practitioners, data scientists, technology providers, consultants, regulators, and academics - has left us convinced that there is an urgent shortage of people on the business side who know how to partner with the technical people building AI applications.

If you have lots of time on your hands and want to change career entirely, you may want to learn to build AI applications. However the claims others sometimes make that you can learn machine learning in 30 days and suddenly get a job as a data scientist are unrealistic. 

We believe that what you can accomplish in a month is to gain a deep understanding of the fundamental principles behind machine learning, become familiar with the processes and methodologies that data scientists use to build AI applications, and learn how to leverage your existing skill sets to make meaningful contributions to data science projects.

The course contains four parts, 12 modules, and 11.5 hours of video content across 55 lessons. It also comes with free and downloadable supplemental materials. We’ve designed it so that you can tackle one part a week, and complete it in less than a month. But nothing would prevent you from completing it much faster, if you're so inclined.

Much of the education one can find in the fields of machine learning and data science is sponsored or created by organizations that want to push their own products or services. The idea is that by teaching you how to do data science using their own tools, you’ll become dependent on them to perform your work in the future. 

We have no interest in promoting any third-party products, technologies, or organizations. Our only motivation is to help as many possible become fluent in AI and become effective partners with data scientists, and users of AI.

Whether or not ‘AI’ exists today depends on how you define it. The important thing is that a suite of technologies and methodologies are poised to transform every aspect of the global economy. Whatever you call them, it is important that you should know how they work, how they are built, and how to work effectively with them.