The Complete Data Science Project Management Course
The Complete Data Science Project Management Course

The Complete Data Science Project Management Course

Learn step by step Data Science Project Management through CRISP-DM industry standard data mining methodology

The Complete Data Science Project Management Course

What you’ll learn

  • Plan end to end data science projects including activities involved, dependencies, external/internal resource needs and skills requirements
  • Manage stakeholder expectations on the delivery of data science projects
  • Manage data science team and ensure alignment to larger project/program objectives
  • Plan communications on status reporting of data science projects with details of all activities

Requirements

  • None
Description

This course is to enable learners to successfully manage a data science project. It is process oriented and explains CRISP-DM methodology. CRISP-DM, stands for Cross Industry Standard Process for Data Mining, and it is the most widely used, holistic framework for data science projects.

This course takes you through the data mining activities in the context of Project Management. The project explains inputs and outputs of all activities helping effective project management of a data science project. As per the Project Management best practices it guides you to engage the right stakeholders to help setting Data Mining Success criteria to achieve the business goals.

Machine Learning and Model building activities using Python or R are an important activities in any data science project. However, there are several other activities that are part of any Data Science project. The data needs to be prepared for application of machine learning techniques. There are lot of steps involved in preparing a data-set which would be suitable for achieving the  business goal of the data science project. In this course, we are going to take a broader look and identify how each activity of CRISP-DM fits together towards achieving business outcomes of a data science project.

The course lists the monitoring, reporting and user training needs during the execution of data science project. The data science project needs to conclude with deployment of data mining results and review of lessons learned. All the above activities are sequenced in this course along with their purpose and elaborate details for end to end execution of a data science project.

Who this course is for:
  • Project/Program Managers who want to manage data science, Artificial Intelligence and Machine Learning projects
  • Business Analysts/ Domain Specialists/ Business sponsors who need to drive business improvements through data science projects
  • Data Science team members (developers/technologists/data analysts) who want to get the big picture of data science projects
  • Aspiring Data science professionals, who want to learn complete methodology without having to learn coding or technical topics

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