SAS
Machine Learning Rock Star – the End-to-End Practice Specialization
SAS

Machine Learning Rock Star – the 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.

Taught in English

Eric Siegel

Instructor: Eric Siegel

9,881 already enrolled

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Specialization - 3 course series

Get in-depth knowledge of a subject

4.8

(142 reviews)

Beginner level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Learn at your own pace

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

Details to know

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Specialization - 3 course series

Get in-depth knowledge of a subject

4.8

(142 reviews)

Beginner level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 3 course series

What you'll learn

  • Participate in the deployment of machine learning

  • Identify potential machine learning deployments that will generate value for your organization

  • Report on the predictive performance of machine learning and the profit it generates

  • Understand the potential of machine learning and avoid the false promises of “artificial intelligence”

Skills you'll gain

Category: Predictive Analytics
Category: Ethics Of Artificial Intelligence
Category: Artificial Intelligence (AI)
Category: Data Science
Category: Machine Learning

What you'll learn

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

  • Plan ML: Determine the way machine learning will be operationally integrated and deployed, and the staffing and data requirements to get there

  • Greenlight ML: Forecast the effectiveness of a machine learning project and then internally sell it, gaining buy-in from your colleagues

  • Lead ML: Manage a machine learning project, from the generation of predictive models to their launch

Skills you'll gain

Category: Predictive Analytics
Category: Artificial Intelligence (AI)
Category: Data Science
Category: Machine Learning
Category: Machine learning strategy and leadership

What you'll learn

  • Participate in the application of machine learning, helping select between and evaluate technical approaches

  • Interpret a predictive model for a manager or executive, explaining how it works and how well it predicts

  • Circumvent the most common technical pitfalls of machine learning

  • Screen a predictive model for bias against protected classes – aka AI ethics

Skills you'll gain

Category: Predictive Analytics
Category: Artificial Intelligence (AI)
Category: Data Science
Category: Machine Learning
Category: Machine Learning (ML) Algorithms

Instructor

Eric Siegel
SAS
5 Courses15,730 learners

Offered by

SAS

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