This course will guide you to lead or participate in the end-to-end implementation of machine learning (aka predictive analytics). Unlike most machine learning courses, it prepares you to avoid the most common management mistake that derails machine learning projects: jumping straight into the number crunching before establishing and planning for a path to operational deployment.
Whether you'll participate on the business or tech side of a machine learning project, this course delivers essential, pertinent know-how. You'll learn the business-level fundamentals needed to ensure the core technology works within – and successfully produces value for – business operations. If you're more a quant than a business leader, you’ll find this is a rare opportunity to ramp up on the business side, since technical ML trainings don’t usually go there. But know this: The soft skills are often the hard ones.
Learn How To
Apply ML: Identify the opportunities where machine learning can improve marketing, sales, financial credit scoring, insurance, fraud detection, and much more.Plan ML: Determine the way in which machine learning will be operationally integrated and deployed, and the staffing and data requirements to get there. Greenlight ML: Forecast the effectiveness of a machine learning project and then internally sell it, gaining buy-in from your colleagues.Lead ML: Manage a machine learning project, from the generation of predictive models to their launch.Prep data for ML: Oversee the data preparation, which is directly informed by business priorities.Evaluate ML: Report on the performance of predictive models in business terms, such as profit and ROI.Regulate ML: Manage ethical pitfalls, such as when predictive models reveal sensitive information about individuals, including whether they're pregnant, will quit their job, or may be arrested – aka AI ethics.
Before this course, learners should take the first of this specialization's three courses, The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats.