Machine learning reinvents industries and runs the world. Harvard Business Review calls it “the most important general-purpose technology of our era.”
But while there are so many how-to courses for hands-on techies, there are practically none that also serve the business leadership of machine learning – a striking omission, since success with machine learning relies on a very particular project leadership practice just as much as it relies on adept number crunching.
Why cover both sides? Because both sides need to learn both sides! This includes everyone leading or participating in the deployment of ML.
Rather than a hands-on training, this Machine Learning Rock Star – the End-to-End Practice Specialization offered by Coursera in partnership with SAS serves both business leaders and burgeoning data scientists with expansive, holistic coverage.
Before jumping straight into the hands-on, as quants are inclined to do, consider one thing: This curriculum provides complementary know-how that all great techies also need to master.
How ML works, how to report on its ROI and predictive performance, best practices to lead an ML project, technical tips and tricks, how to avoid the major pitfalls, whether true AI is coming or is just a myth, and the risks to social justice that stem from ML.
Applied Learning Project
Problem-solving challenges: Form an elevator pitch, build a predictive model by hand in Excel or Google Sheets to visualize how it improves, and more (no exercises involve the use of ML software).
Get more detailsVisit official programme website
- The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats
- Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership
- Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls
Check out the full curriculumVisit official programme website
- 3 months
- 4 hrs/week
Start dates & application deadlines
DisciplinesComputer Sciences Artificial Intelligence Machine Learning View 620 other Short Courses in Computer Sciences in United States
Explore more key informationVisit official programme website
We are not aware of any academic requirements for this programme.
We are not aware of any English requirements for this programme.
- Accessible to business-side learners yet also vital to techies. Engage in the commercial use of ML – whether you're an enterprise leader or a quant.
Make sure you meet all requirementsVisit official programme website
InternationalFreeTuition FeeBased on the tuition of 0 USD for the full programme during 3 months.
NationalFreeTuition FeeBased on the tuition of 0 USD for the full programme during 3 months.
You can choose from hundreds of free courses, or get a degree or certificate at a breakthrough price. You can now select Coursera Plus, an annual subscription that provides unlimited access.
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
Double-check all feesVisit official programme website
Apply and win up to €10000 to cover your tuition fees.