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Q: What are the prerequisites for this program?

A: You should have US high school math down pretty well: algebra, basic statistics (mean, median, mode), functions and plotting. You should have sufficient English speaking ability to communicate your questions and ideas, and you should have sufficient English listening comprehension ability to learn from a native speaker speaking at a conversational speed. You should be self-motivated to find and pursue ways to create value in the workplace. You should be open-minded to alternative learning practices and a diverse body of course attendees. You should be willing to bring sufficient energy to fully engage in the material.

Q: If many of your course participants will join other professions, why do you use software engineering and data science hiring processes as your models for evaluating their learning? Why not just use traditional tests like most online courses?

A: Our thesis is that knowing software engineering and data science well enough to conceive, evaluate, and execute small projects is helpful in any profession. We also believe that it is possible to spend significant time learning data science and software theory without getting to the point of practical utility, and we want to avoid that. Our goal is to make every second of the program count. Employers who plan to capitalize on the abilities of software engineers and data scientists are constantly working on new and more effective ways to quickly evaluate whether a job candidate can deploy their knowledge to create value. They don’t want to spend any more time than necessary evaluating anyone, but they also don’t want to overlook a great candidate. Their evaluation methods are therefore optimized for time efficiency and evaluation of practical utility of candidate skill. For these reasons, we believe they are a good source for our own evaluation criteria, even for those who do not plan on pursuing jobs with titles such as “software developer” or “data scientist”.


Q: If I attend the course, do I have to complete a capstone independent project, and do I have to publish my project online?

A: You do not have to do either, but both are highly encouraged. In fact, the published individual capstone project is arguably the most valuable component of the course. It proves to the world that you know software engineering and/or data science well enough to have conceived of and carried out something that works and that solves a real problem. If someone looks at your course certificate, they might still be left wondering whether you can really execute. If they click a link you provide to a functioning piece of code, however, it is much harder to have doubts.

Q: This program seems geared towards professionals. I am still a student. Is this course right for me?

A: This is certainly professional training, but so is a part of traditional education, too. Students are encouraged to register. We're happy to discuss with you individually to make sure there is a good fit before you commit. The aspect of the program that students might find challenging is the requirement of what we call professional motivation. Whereas most academic programs teach toward tests and provide a key final metric of quantitative achievement against a standard, this program teaches toward professional success and therefore emphasizes more qualitative feedback throughout. As a result, the type of motivation required is different. Students should be seeking to build a capacity to contribute to the working world rather than to ace a test. Students do not need to already understand where the specific opportunities are for automation and data science to add value in the workplace. We devote significant time to exploring this. There is not room in the course, however, for us to help cultivate motivation for that goal.

Q: I have decades of working experience and am new to building software or doing data science. Can I handle this program?

A: Absolutely. There seems to be a pervasive view that building software and executing data science is extremely challenging and therefore only available to some exclusive group. The reality is that patience, logic, and a clear sense of purpose can take you very far in both areas. We often work with teams of expert data scientists and developers struggling to find specific professional problems to address. Your strong understanding of your profession and workflow will give you the ability to very clearly identify opportunities to add value. Many of our program attendees do not plan to become professional data scientists or process automation specialists; they plan on contributing a new kind of value within their existing profession. The opportunity to begin to specialize in data science and automation may present itself in the workplace, however, once you start to show what you can do.

Q: This looks interesting, but the timing doesn't work for me. Will you offer this again?

A: We plan to continue to offer courses. The best way for us to know what courses are of value is to hear from you. If you like the look of this program and are unavailable, contact us and we'll take your ideas into consideration as we continue to develop our programming.

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