Introduction to Data Science

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Introduction to Data Science

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In partnership with Pandata.

The ability to consistently derive value from data is becoming critical to organizations at all levels. Data Science skills are in high demand and limited supply. From assessing feasibility to implementing machine learning algorithms to drive business value, this class provides a foundation in the technical skills and processes to develop data-driven solutions. This course will be hands-on with a combination of case studies and workshops to equip attendees with practical experience that translates directly to the workplace.

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Audience

This course is designed for IT professionals looking to develop foundational data science skills.

Learning Objectives

By the end of the course, participants will be able to:

  • Understand basic Data Science workflows and best practices

  • Collaborate in teams to develop end-to-end data science solutions

  • Develop trust and credibility in solutions using a proven Data Science process

  • Interpret results and communicate expectations around data solutions

Course Topics

  • The data science process

  • Workflows, version control, and collaboration

  • Statistical modeling and machine learning assumptions

  • Overview of regression and machine learning concepts

  • Data quality and statistical validation

  • Communicating data science results

Prerequisites

  • Proficiency in one or more programming language.

  • Technical instruction will be based in R, however all
    focus will be on concepts as opposed to coding so skills are transferrable to other scientific computing
    languages. No background in R necessary.