Machine Learning Course
Machine Learning Leadership and Practice: End-to-End Mastery
Take this online course anytime – or to ramp up before the conference…
… if you’re new to ML and predictive analytics
… or if you’re a data scientist pursuing the business side of ML
… or if you’re a data scientist pursuing special advanced topics
While there are 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.
By filling that gap, 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.
Accessible to business-level learners and yet vital to techies as well, this course will guide you to lead and launch machine learning.
This course also serves as prep for Machine Learning Week’s advanced, in-person workshops.
An Extremely Extensive Curriculum
THREE COURSES IN ONE. An extensive curriculum worth 3 times the price:
- Gain a strong foundation in only 6 hours
- Optionally keep learning for 12 more hours on special topics
- If you’re already a data scientist, you may skip right to the advanced topics
- Earn up to three certificates of completion (all included)
END-TO-END. This course covers both the technical side and the business side – both the cutting edge modeling algorithms and the business-side best practices needed for successful deployment.
THE RARE SKILLS. Above and beyond the core tech and its value to business, this course presents the two rare skills that all professionals must master in order to launch ML both profitably and equitably: 1) astute bullshit detection to sniff out the magical thinking that compromises the entire field and 2) fluency with a collection of uncomplicated ML fundamentals that, astonishingly, are seldom known by either business leaders or data scientists – but are essential for them both.
NO HANDS-ON AND NO HEAVY MATH. Rather than a hands-on training, this course serves both business leaders and burgeoning data scientists alike with expansive, holistic coverage of the state-of-the-art techniques and business-level best practices. There are no exercises involving coding or the use of machine learning software.
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. It contextualizes the core technology, guiding you on the end-to-end process required to successfully deploy a predictive model so that it delivers a business impact.
IN-DEPTH YET ACCESSIBLE. Brought to you by industry leader Eric Siegel – a winner of teaching awards when he was a professor at Columbia University – this course stands out as one of the most thorough, engaging, and surprisingly accessible on the subject of machine learning.
Here’s what you will learn:
– How machine learning – aka predictive analytics – works
– How it actively improves major business operations to boost business, accumulate clicks, fight fraud, and deny deadbeats
– How to report on the increase in profit, ROI, and predictive performance it achieves
– What the data needs to looks like
– Leadership: gold standard practices for managing a machine learning project
– The technical tips and tricks – and how to avoid the most prevalent pitfalls
– Whether true artificial intelligence is coming or is just a myth
– Ethical AI: the risks to social justice that stem from machine learning
DYNAMIC CONTENT. Across this range of topics, this course keeps things action-packed with case study examples, software demos, stories of poignant mistakes, and stimulating assessments.
VENDOR-NEUTRAL. This course includes several illuminating software demos of machine learning in action using SAS products, plus one hands-on exercise using Excel or Google Sheets. However, 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.
After taking Machine Learning Leadership and Practice: End-to-End Mastery, you will be able to:
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 ethical AI
For those who are involved in managing the machine learning lifecycle or team, this class is a must. With well over 100 videos, tons of readings, and quizzes, all leaders in data need to be well-versed in everything presented here. Take it: treat yourself, don’t cheat yourself.
—Sam Coyne, Director of AI, Georgia-Pacific
An exceptionally insightful and unique course by none other than the maestro of predictive analytics, Dr. Eric Siegel. It elucidates us how launching machine learning – aka predictive analytics – improves marketing, financial services, fraud detection, and many other business operations. I thank SAS for collaborating with Eric for this amazing initiative.
—Ajith Nair, Graduate of Fr. Conceicao Rodrigues Institute of Technology
If you have any interest in machine learning from a technical or even a business/management position, take this course by Eric Siegel, the guy who wrote the book on predictive analytics.
—Jason Green, Data Engineer, Proofpoint
I have to say that this course stands out among the others. This instructor is presenting the material in a clear, fresh and truly engaging way making this topic accessible to everyone.
—Christina Morgenstern, University Lecturer, University College of Teacher Education Carinthia (Austria)
Sample Course Videos
Welcome video – machine learning in 20 seconds
Why learning about overall ML helps you with deep learning
This concentrated entry-level program is totally accessible to business-level learners – and yet also vital to data scientists who want to secure their business relevance. It’s for anyone who wants to participate in the value-driven use of machine learning, no matter whether you will do so in the role of enterprise leader or quant. Since there is no hands-on and no heavy math (other than one spreadsheet-based exercise, as well as optional hands-on opportunities with SAS software), this program serves business professionals and decision makers of all kinds, such as executives, directors, line of business managers, and consultants – as well as data scientists.
But technical learners should take another look. Before jumping straight into the hands-on, as data scientists are inclined to do, consider one thing: This holistic curriculum provides complementary know-how that all great techies also need to master. It contextualizes the core technology, guiding you on the end-to-end process required to successfully deploy a predictive model so that it delivers a business impact.
- Business leaders. Project managers, directors, CXOs, vice presidents, investors and decision makers of any kind involved with the deployment of machine learning.
- Technology experts. Data scientists, data engineers, developers, DBAs, data warehousers, and consultants who wish to extend their expertise.
- University students. These three courses are also a good fit for college students, or for those planning for or currently enrolled in an MBA program. The breadth and depth of this course is equivalent to one full-semester MBA or graduate-level course. It also complements degree programs, since it covers rare aspects of both the business and technical sides of ML.
Register for Online Access
COURSE PARTICIPANTS RECEIVE:
- Six months of unlimited access (provided within two business days of paid registration).
- Three courses in one. When you register, you will gain access to a three-course series (together called a specialization).
- Free book. The instructor’s bestselling book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die – your choice of paperback, Kindle, or audiobook.
- Certificates of completion. A certificate of completion issued by Machine Learning Week, plus eligibility to receive up to three Digital Badges from SAS by way of passing course quizzes.
- Demos and hands-on exercises. Relevant ML software demos and exercises serve to illuminate machine learning in action. These are provided by the leading analytics company SAS and are fully optional. They complement the instructor’s curriculum, which itself is entirely 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.
- Extensive materials. A total of 18 hours of course videos, optional readings, and stimulating quizzes.
Registrants receive a copy of the instructor’s bestselling book.
Registrants receive a certificate of completion, plus eligibility to receive up to three Digital Badges.
Instructor: Eric Siegel
Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who bridges the business and tech sides of machine learning. He is the founder of the Predictive Analytics World and Deep Learning World conference series, which have served more than 17,000 attendees since 2009. As the instructor of the acclaimed online course Machine Learning Leadership and Practice: End-to-End Mastery, a winner of teaching awards as a professor, and a popular speaker, Eric has given more than 110 keynote addresses. The executive editor of The Machine Learning Times, he wrote the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has been adopted for courses at hundreds of universities. Eric has appeared on numerous media channels, including Bloomberg, National Geographic, and NPR, and has published in Newsweek, HBR, SciAm blog, WaPo, WSJ, and more – including op-eds on analytics and social justice. Follow him at @predictanalytic.
About Machine Learning Week
Founded in 2009 by this course’s instructor, Eric Siegel, Machine Learning Week is the leading cross-vendor conference series covering the commercial deployment of machine learning, with events taking place in both the U.S. and Europe.