Communicating Expectations to the Business

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Benjamin Culbertson

43:26

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1. Course Overview

1. Course Overview.mp4

01:20

2. Reviewing Available Data with Stakeholders

1. Overview.mp4

00:55

2. The Use Case - Media Insights Solution.mp4

01:53

3. Available Data Sources.mp4

01:47

4. Bring in the SME.mp4

01:35

5. Exploratory Data Analysis Tools.mp4

01:37

6. The Format of the Data.mp4

02:05

7. Summary.mp4

01:09

3. Communicating Barriers to Data Access to Stakeholders

1. Overview.mp4

00:54

2. The Problem with the Internal Data.mp4

01:44

3. Your New Data Broker.mp4

02:12

4. The Budget Barrier and Solution.mp4

02:32

5. Personally Identifiable Information (PII).mp4

02:52

6. Ethical and Legal Barriers to Data Use.mp4

02:01

7. Summary.mp4

01:01

4. Recommending Next Steps Based on Available Data

1. Overview.mp4

01:09

2. A New Problem to Be Solved.mp4

02:33

3. Synthetic Training Data.mp4

03:53

4. The Complete Media Insights Solution.mp4

02:20

5. Testing for Validity.mp4

02:16

6. Correlation vs. Causation.mp4

02:36

7. The Big Ask.mp4

01:50

8. Summary.mp4

01:12

Description

Learn how to manage your stakeholders' expectations for a solution as well as the ins and outs of procuring data for training a model. You'll also explore the idea of synthetic generation--it could save your project and your budget!

What You'll Learn?

Discover critical skills in communicating barriers and solutions to data acquisition for model training. In this course, Communicating Expectations to the Business, you will learn foundational knowledge that will aid you in managing stakeholders' expectations of data science, machine learning, and augmented intelligence solutions. First, you will learn what is needed for a data science solution. Next, you will discover the four main sources of historical data that can be used to train models for a solution that will generate insights that will be used by a team, and what barriers you may encounter in acquiring that data. Then, you will examine an innovative solution, synthetic data generation, that will aid in transforming existing data while maintaining the data's character, personality, and richness. Finally, you will explore how to communicate solutions and expectations to stakeholders on data availability and formatting, and ask for a go/no-go decision. When you're finished with this course, you will have the skills and knowledge of communicating challenges around availability of data, and strategies needed to overcome barriers to bring needed historical data to your data science and machine learning solution.

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Benjamin Culbertson

Instructor's Courses

Coach helps leaders recharge their batteries and gain new skills through energizing and interactive presentations that have immediate real-world impact. He's taught tens of thousands of corporate, military, and government IT people around the world, and he's been trained as a clown by a Ringling Bros. veteran--not a combination you can find just anywhere. He combines his vast experience in pragmatic training with his over-the-top energy to create the "infotainment" style his fans know and love.

Pluralsight

View courses Pluralsight

Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.