Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 23 Minute(s)
Language
English
Taught by
Colin Priest
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
The science and art of communicating with non-technical stakeholders in AI projects
This course is about the soft skills and contextualization skills you need to become that go-to person in the office, who can explain the complex ideas about machine learning and artificial intelligence in a manner that is accessible to all.
Why should you improve your machine learning and artificial intelligence communication skills? Communication skills are vital to
● build your career, and
● to help your colleagues and organization become successful,
The hard truth is that facts are not enough. Your wording and style often matter more than your content.
While this course is aimed at data scientists, statisticians, and data analysts, it doesn’t contain any mathematics nor does it require any calculations and coding. Why? Firstly, because there are many courses and tutorials out there that can teach you the mathematics and tools, and I see no need to repeat them. Secondly, and more importantly, because the published research shows that spending time on the mathematical details only leads to confusion, distrust, and errors.
It’s more than 25 years since I started my journey in machine learning and artificial intelligence, and during that time I’ve seen it all. As a technical manager and later a member of the C-Suite, I sat through many presentations from technical staff. Too many of those presentations looked like a Ph.D. research paper rather than effective and trustworthy business advice. So, I started to mentor people in how to communicate better.
For more than a decade now, I have been teaching technical people how to communicate, and how to contextualize the people issues and business environment.
You are going to learn to talk to businesspeople in terms that they understand and that will engage their attention, ask businesspeople questions that will align your model's behavior with business needs, and anticipate and prepare for their questions.
Course Content
- 8 section(s)
- 37 lecture(s)
- Section 1 Introduction
- Section 2 Stakeholder Analysis: Understanding Your Audience
- Section 3 Communication - Solving the Right Problem
- Section 4 Model Explanation - Which Data is Most Important?
- Section 5 Model Explanation - What Did the Model Learn?
- Section 6 Model Explanation - Detailed Examples
- Section 7 Model Explanation - Accuracy and Business Value
- Section 8 Objection Handling
What You’ll Learn
- How to explain complex models without confusing your businessperson audience
- How tailor your explanations to your audience
- How to address common concerns and blocker raised by businesspeople
- How to create an engaging narrative from technical diagnostics
- How to collaborate with businesspeople to achieve better models that are accepted and used by across the business
Skills covered in this course
Reviews
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FFilip Dratwiński
Overall the course was great, it was concise and clear. However, one thing that I didn't like was the questions in the quizzes. Sometimes I feel the explanation why I choose incorrect answer wasn't clear. The questions were sometimes ambigious
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JJK Tan
Tailoring what we present to the needs of the audience is very important. This course nails it and gives quite a number of good examples. However, we get immersed in the technicalities of the work, one of the greatest temptations is to give and tell everything. So listening to the advice given in this course has been very useful. The details in the video are too small though to be viewed on a mobile phone though. Nevertheless I trust that the instructor will improve on that over time.
