3 months
Duration
Free
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About

By filling that gap, this Machine Learning Rock Star – the End-to-End Practice Specialization offered by Coursera in partnership with SAS empowers you to generate value with ML. It delivers the end-to-end expertise you need, covering both the core technology and the business-side practice.

Visit the official programme website for more information

Overview

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).

Programme Structure

Courses included:

  • 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

Key information

Duration

  • Part-time
    • 3 months
    • 4 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online

Academic requirements

We are not aware of any academic requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Beginner Level

  • 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.

Tuition Fee

To alway see correct tuition fees
  • International

    Free
    Tuition Fee
    Based on the tuition of 0 USD for the full programme during 3 months.
  • National

    Free
    Tuition Fee
    Based 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.

Funding

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.

Our partners

Machine Learning Rock Star – the End-to-End Practice
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Coursera

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