It's a simple way to make it clear to everyone that you have some baseline of knowledge and are not some random wanker. The same way a degree in math gives you street cred in the data science world. The reason to get an MBA is to get street cred with other MBA's. The metric has had lots of baskets of goods or assets chopped out of it over the years to make it appear better than it is. However, to put it short, inflation is drastically under-reported. It's too big of a topic to discuss here and I'm already writing too much. Software engineering and data science jobs are the new middle class factory job so you're guaranteed a decent living wage. Wage growth tends to stagnate for technical staff after that time. The new parent company more often than not throws down lots of cost controls, and treats the engineering staff as a cost center rather than a revenue center. Anyone can promise a thing, but it falls on the technical staff to actually deliver it.Īcquisition by larger businesses can also lead to the pattern. It appears to higher-ups that the PMs or sales staff are driving revenue when it's really the people delivering on promises or making the product better that are responsible. Long story short, the visibility of who gets a thing done changes. It usually goes to shit for the technical staff since they're now communicating through PMs or managers rather than direct to the executives or shareholders. It's mostly corporations beyond a certain size where this pattern starts-when they start hiring a large number of sales, marketing and MBA types. Either way the point is there is a bias towards assigning credit to leaders rather than teams. It's not always an MBA stealing credit for something, sometimes it's a engineer that switched tracks to management. I should have qualified my statement some more. Otherwise it's a politics game, some engineers get promoted because they learned to navigate MBA-land. There is only 1 right answer for each function type. OLS just tweaks the required parameter(s) to minimize regression. I understand that both use algorithms to optimise parameters but the neural network does so in a way that much more clearly falls under "learning" as it finds a solution that works as well as it can (depending or set up factors). ![]() However, optimising a single parameter by minimizing it for a given data set doesn't obviously define itself as learning.Ī neural network, in contrast optimises in an iterative process that by design mimics learning. I don't find that too much of a stretch but it doesn't strike me as self evident. ![]() ![]() Whilst of course much easier (and only really scalable by machine) I don't see why it requires a machine by definition, unless all computational maths (such as algorithms and iterative methods) falls under machine. Forgive me, but I encountered this much earlier in stats than I have in data science. All rights reserved.Well OLS would be the minimisation of a single parameter. In site-based programs, students will be required to take a substantial amount of coursework online to complete their program. View DeVry University’s complaint process Program availability varies by location. Unresolved complaints may be reported to the Illinois Board of Higher Education through the online compliant system. ![]() 120, Arlington, VA 22202. DeVry University is authorized for operation as a postsecondary educational institution by the Tennessee Higher Education Commission, Naperville Campus: 1200 E. DeVry is certified to operate by the State Council of Higher Education for Virginia. DeVry University is accredited by The Higher Learning Commission (HLC), The University’s Keller Graduate School of Management is included in this accreditation. In New York, DeVry University operates as DeVry College of New York. For instance, if you earn an MBA with a Specialization in Finance, you are choosing a program with a blend of business and finance classes over a Master's Degree in Finance, which would be more exclusively geared toward that discipline. You should, of course, consider whether an MBA is a better fit for your career goals compared to a more specialized master's degree in your chosen field. This means that it covers a wide range of business concepts and skills, making it easier for you to apply these concepts across many different business career paths. Compared to specialized master’s degrees, such as a Master’s in Accounting, an MBA degree takes a more generalized approach to business education. Depending on the career path you have in mind, earning an MBA degree can prepare you to pursue a variety of roles, as well as hone your business skills. Advancing your education is a great way to gain new insights, explore current technologies and network within your industry. There can be many potential benefits to earning an MBA degree.
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