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University of Toronto

Gender Analytics: Gender Equity through Inclusive Design

University of Toronto via Coursera Specialization

Overview

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Current conversations about diversity & inclusion often forget that these are not just HR issues but affect how products, services, processes & policies create outcomes that differ by gender, race, differences in ability, Indigeneity & other intersecting identities. Gender Analytics is a methodology that allows you to create opportunities for business or policy impact by using gender-based insights to design transformational solutions. More here... In 5 courses offered by the Institute for Gender and the Economy, you will: >Examine how policies, products, services & processes have gendered impacts that miss opportunities or create needless risks >Break norms that perpetuate exclusion in serving customers/beneficiaries >Get comfortable with concepts such as sex, gender identity & intersectionality >Learn qualitative & quantitative analytical techniques to uncover intersectional gender-based insights >Use human-centred design to create innovative solutions >Become a transformational leader Who is this designed for? >Business leaders who want to use gender insights to innovate >Government & NGO professionals who want to do gender-based analysis (GBA+) >Women’s studies experts seeking job-related applications >Business analytics experts extending their skills to questions of equity >Human resources professionals looking to be partners for business innovation *Academic Director: Sarah Kaplan; Project Lead: Lechin Lu; Teaching Consultant: Kim de Laat

Syllabus

  • Course 1: Gender Analytics for Innovation
  • Course 2: Inclusive Analytic Techniques
  • Course 3: Human-Centered Design for Inclusive Innovation
  • Course 4: Transformational Leadership for Inclusive Innovation
  • Course 5: Gender Analytics Capstone Project

Courses

Taught by

Brian Silverman, Chanel Grenaway, Jia-Lin Xie, Karen Sihra, PhD, Mark Leung, Nika Stelman, Nouman Ashraf and Sarah Kaplan

Reviews

4.8 rating at Coursera based on 625 ratings

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