Machine Learning

End to End Practice Specialization

An End-to-End Guide to Leading and Launching ML. This expansive machine learning curriculum is accessible to business-level learners and yet vital to techies as well. It covers both the state-of-the-art techniques and the business-side best practices.

What You’ll Learn

Lead ML: Manage or participate in the end-to-end implementation of machine learning

➤  Apply ML: Identify the opportunities where machine learning can improve marketing, sales, financial credit scoring, insurance, fraud detection, and much more

➤  Greenlight ML: Forecast the effectiveness of and scope the requirements for a machine learning project and then internally sell it to gain buy-in

➤  Regulate ML: Manage ethical pitfalls, the risks to social justice that stem from machine learning – aka AI ethics

Skills You’ll Gain

Machine Learning Algorithms

Artificial Intelligence

ML Strategy and Leadership

Machine Learning

Predictive Analytics

Ethics of Arrificial Intelligence

Data Science

About the Specialization

Machine learning reinvents industries and runs the world.

This course 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.

Why cover both sides? Because both sides need to learn both sides! This includes everyone leading or participating in the deployment of ML.

NO HANDS-ON. Rather than a hands-on training, this specialization serves both business leaders and burgeoning data scientists with expansive, holistic coverage.

WHAT YOU’LL LEARN. 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.

BUT TECHNICAL LEARNERS SHOULD TAKE ANOTHER LOOK. 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 this specialization works:

Take the Course

This Specialization is a series of courses that helps you master a skill. Review its courses and choose the one you’d like to start with. It’s okay to complete just one course — you can pause your learning and resume it at any later time.

Earn a Certificate

When you finish every course and complete the hands-on project, you’ll earn a Certificate that you can share with prospective employers and your professional network.

Hands-on Project

Every Specialization includes a hands-on project. You’ll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you’ll need to finish each of the other courses before you can start it.

There are 3 Courses in this Specialization

Frequently Asked Questions

1. Is this course completely online ?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

2. Is this Specialization for data Scientists or non-technical business level learners ?

It’s for both. To run a successful machine learning project, business leaders need to learn how machine learning works – even if they’re not going to be doing the number crunching themselves. On the other hand, data scientists also benefit from a holistic curriculum that covers not only the core analytical methods, but contextualizes those methods in business terms. This curriculum serves both business leaders and data scientists, but it will not prepare you to be a hands-on practitioner – you’ll need additional training for that. Rather, it is complementary to hands-on training, covering topics usually skipped there, including machine learning project management, how to prepare the data to serve business-level requirements, evaluation – calculating and reporting on the performance of a predictive model in business terms – and a deep dive into ethical issues, identifying risks to social justice and civil liberties that arise with a machine learning project and presenting options to avert these risks.

3. How Technical is this Specialization and is math involved ?

This curriculum is fully accessible to non-technical learners, business managers, and newcomers. No heavy math or coding is involved and no background in statistics or programming is required. The most technical course of this three-course specialization is the last one, which delves into the predictive modeling methods themselves. It does so in as revealing and concrete a manner as possible so as to remain relevant and understandable to non-technical learners.

4. Are the Learnings Specific to SAS Software?

No, the curriculum is vendor-neutral and universally-applicable. The contents and learning objectives apply, regardless of which machine learning software tools you end up choosing to work with. However, this specialization includes several illuminating software demos of machine learning in action using SAS products.

5. Is the Course for Industry Professionals or University Students ?

Time to completion can vary widely based on your schedule. Most learners are able to complete the Specialization in 4-5 months.

6. Do I Need to take the Course in any Specific Order ?

The ordered sequence of three courses is intentional and important. The first one covers the basics and sets the foundation. Then the second focuses on the business side of machine learning and the third on the tech side. Take them in this order:

Course 1 – The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats

Course 2 – Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership

Course 3 – Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls