Data Science for Business Leaders: ML Fundamentals
Learn the fundamentals of machine learning and its potential for business success. No coding or complex math required. Suitable for all backgrounds.
What you’ll learn
- Learn what models are, how they work, and how they fit in the overall picture of machine learning (ML) and data science.
- Lots of terminology (“AI”, “deep learning”, etc.); plain and simple explanations (without the hype).
- Fair warning: NO hands-on model development (NO code & NO complex formulas)
- Includes sections dedicated to *identifying* and *quantifying* machine learning opportunities.
- Focused on understanding ML as a capability that can benefit any business.
Machine learning is a capability that business leaders should grasp if they want to extract value from data. There’s a lot of hype; but there’s some truth: the use of modern data science techniques could translate to a leap forward in progress or a significant competitive advantage. Whether your are building or buying “AI-powered” solutions, you should consider how your organization could benefit from machine learning.
No coding or complex math. This is not a hands-on course. We set out to explain all of the fundamental concepts you’ll need in plain English.
This course is broken into 5 key parts:
Part 1: Models, Machine Learning, Deep Learning, & Artificial Intelligence Defined
This part has a simple mission: to give you a solid understanding of what Machine Learning is. Mastering the concepts and the terminology is your first step to leveraging them as a capability. We walk through basic examples to solidify understanding.
Part 2: Identifying Use Cases
Tired of hearing about the same 5 uses for machine learning over and over? Not sure if ML even applies to you? Take some expert advice on how you can discover ML opportunities in *your* organization.
Part 3: Qualifying Use Cases
Once you’ve identified a use for ML, you’ll need to measure and qualify that opportunity. How do you analyze and quantify the advantage of an ML-driven solution? You do not need to be a data scientist to benefit from this discussion on measurement. Essential knowledge for business leaders who are responsible for optimizing a business process.
Part 4: Building an ML Competency
Key considerations and tips on building / buying ML and AI solutions.
Part 5: Strategic Take-aways
A view on how ML changes the landscape over the long term; and discussion of things you can do *now* to ensure your organization is ready to take advantage of machine learning in the future.
Who this course is for:
- Business leaders, executives, product managers, process owners, service managers, or anyone who is responsible for how their organization operates.
- Suitable for people with both technical and non-technical backgrounds.
- Can be a helpful business-point-of-view for aspiring and experienced data scientists.
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