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Problem Identification and Solution Design for Data Scientists

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Keith McCormick

1:25:10

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  • 01 - Welcome.mp4
    00:51
  • 02 - Intended Audience.mp4
    01:20
  • 01 - Looking at the project from the sponsors point of view.mp4
    03:45
  • 02 - Reading the project description critically.mp4
    03:48
  • 03 - Preparing for the first meeting as an internal resource.mp4
    02:59
  • 04 - Preparing for the first meeting as an external resource.mp4
    02:36
  • 01 - What to expect in the initial meeting.mp4
    03:18
  • 02 - Inference vs. prediction.mp4
    06:11
  • 03 - Prediction vs. forecasting.mp4
    04:31
  • 04 - Avoiding confusion with other analytic project types.mp4
    03:13
  • 05 - Diving deeper into predictive analytics.mp4
    01:38
  • 06 - Identifying ROI.mp4
    02:38
  • 07 - Some questions that always apply.mp4
    01:10
  • 01 - Business understanding phase overview.mp4
    02:28
  • 02 - The four tasks.mp4
    02:52
  • 03 - Advice on how much detail to share.mp4
    01:48
  • 01 - Pre-meeting requests and preparation.mp4
    03:30
  • 02 - Ensuring that you leave with the critical info.mp4
    05:17
  • 03 - The provenance of the data.mp4
    02:34
  • 04 - Leveraging IT experience and expertise.mp4
    02:53
  • 01 - Leave these interviews for last.mp4
    01:52
  • 02 - Assessing culture.mp4
    02:54
  • 03 - Focusing on inclusion, not exclusion.mp4
    02:11
  • 01 - Metadata vs. data.mp4
    02:04
  • 02 - Estimates of accuracy.mp4
    02:54
  • 03 - Beware too much prototyping.mp4
    03:39
  • 01 - Documentation advice.mp4
    04:03
  • 02 - A simple visuatlization for setting priorities.mp4
    01:38
  • 03 - Striking the optimal amount of detail.mp4
    03:11
  • 01 - Whats next in problem identification and solution design for data scientists.mp4
    01:24
  • Description


    Whether you’re working as a consultant or an employee, you need to be able to speak to nontechnical business leaders if you want to be successful as a data scientist. Becoming bilingual isn’t easy, though—so what’s the secret to mastering this coveted skill? In this course for aspiring data professionals, join instructor Keith McCormick as he outlines the fundamentals of problem identification and solution design for data scientists. Learn how to translate business needs into technical terms, follow the CRoss Industry Standard Process for Data Mining (CRISP-DM), conduct structured interviews with project leaders, and think about projects from a business leader’s point of view. Keith offers quick insights and easy-to-use tips for conveying technical concepts clearly with ease. Along the way, you’ll learn how to leverage business communication and documentation skills throughout every stage of a project.

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    Keith McCormick
    Keith McCormick
    Instructor's Courses
    I'm an independent consultant, trainer, speaker, and author of seven books. My consulting specializes in helping analytics leaders build and manage their data science teams. My training, including 20 LinkedIn Learning courses and frequent conference workshops, has reached 1000s of individuals trying to learn statistics, machine learning, and data science. I love that I am able to train and consult. Training allows me to interact with (and learn from) 100s of clients in dozens of industries every year. It prevents me from obtaining too narrow a focus, and it keeps me current. Consulting allows me to work with a smaller number of clients in detail and in-depth, working with them on real problems of immediate concern to them. It keeps me sharp. If you've encountered me through my LinkedIn Learning courses, please consider following me here on LinkedIn. I'm not able to connect with everyone, so I connect only with clients and colleagues that I know directly. But please do follow me here because I'm quite active on LinkedIn and frequently post excerpts from the courses and other content. Follow #freefirstfridays to see when I post a link to watch a course for free. My favorite kind of consulting work involves: - working with analytics management to create effective data science teams - listening carefully to my client explain their business in detail - turning their description into a research question that can be answered with their data - coaching my client on presenting possible solutions to decision-makers - working behind the scenes to get the solution deployed Specialties: For the last several years, my emphasis has been working with analytics management to more efficiently run their teams and to nurture new hires as they expand their teams. I am skilled at explaining complex methods to new users or decision-makers and can do so at any level of technical detail. I specialize in predictive models and segmentation analysis, including classification trees, neural nets, general linear model, cluster analysis, and association rules. Books and Courses The best way to find out more about me is to check out my courses on LinkedIn Learning. They have received over 500,000 views, and each one has some free content. My books can be found on Amazon, and typically that allows you to view some free content as well. I'm very proud of all of this content (listed below in my profile), but I am still primarily an active consultant. If you need consulting help, private training, or a keynote speaker, contact me, and we can discuss.
    LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.
    • language english
    • Training sessions 30
    • duration 1:25:10
    • English subtitles has
    • Release Date 2025/01/15

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