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Framing and Planning Analytics & Data Science Projects that Drive Business Impact
Framing and Planning Analytics & Data Science Projects - online training course
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3-hour Online Course by Deanne Larson
Single-user access license
Our Price: $305.00

Product Code: SC-02-A

Course Exam [Add $100.00]

Description Course Outline Exam Details

Data Science projects often fail due to unclear scope, lack of project planning, and lack of clear alignment to business objectives. This 3 hour online course addresses how to scope, plan, and choose a project approach for analytics project success and clearly identify the problem and opportunities to be analyzed. Framing and planning drives all of the other phases of data science projects. Based on the CRISP-DM analytics lifecycle, this course describes the purpose, activities, and deliverables for the first phase of that lifecycle.

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You will learn to:
  • Clearly define a problem statement or question of interest
  • Define an analytic project including scope and methodology approach
  • Create a project plan to manage the analytics project
  • Establish stakeholder management and expectations
This course is geared towards:
  • Data scientists, data analysts, and business analysts who need to frame analytics problems and choose the most effective ways to solve those problems
  • Aspiring data scientists and data analysts
  • Business and technical managers who need to understand the nature of analytics and data science work
  • Data engineers and analytics developers who work with data scientists

Average Customer Review: Average Customer Review: 4.5 of 5 4.5 of 5 Total Reviews: 2 Write a review.

  0 of 0 people found the following review helpful:
4 of 5 Course Review from 6/16/2022 January 6, 2024
Reviewer: Melissa Ng Siok Kheng  
No changes.

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  0 of 0 people found the following review helpful:
5 of 5 Course Review from 12/5/2021 January 5, 2024
Reviewer: Gregory Fant DSc PhD MSHS  
This course was better than the "first course" on Data Science Fundamentals. Interestingly, I found "answers" to questions from the Data Science Fundamentals course in this course. This course was set-up for learning.

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