When I was first starting out in my professional career, I scoured the internet for hours looking for resources that could help me on my journey - professional organizations, places to volunteer, slacks to join, blogs to follow, podcasts, and various others.
I’ve compiled this list of what I’ve found with the hope of it helping others along the way.
Organizations
Women in Tech
- Women in Analytics: Global, annual conference, membership program.
- Women in Machine Learning and Data Science (WiMLDS): Global, chapter-based.
- Pyladies: Global, chapter-based.
- R-Ladies: Global, chapter-based.
- Women in Big Data: Global, chapter-based.
- Women in Voice: Global, chapter-based.
- Women Who Code: Global, chapter-based.
- Women in Technology International (WITI): Global, chapter-based.
Diversity in Tech
- Data Umbrella: For under-represented persons in the fields of ML/DS/AI.
- DiversifyTech: Scholarships, events, career resources, and opportunities.
Professional Associations
- Caucus for Women in Statistics
- Association for Women in Mathematics
- American Statistical Association
Data Science & Analytics Resources
Podcasts
- Linear Digressions: Explores interesting and often unusual applications of machine learning and data science.
- Not So Standard Deviations: The latest in data science and data analysis in academia and industry.
- This Week in Machine Learning & AI: Brings together the top minds and ideas from the world of ML and AI.
- Analytics Power Hour: Digital analytics.
- Partially Derivative: Data science in the world around us.
- Casual Inference: Topics include epidemiology, statistics, data science, causal inference, and public health.
- The R-Podcast: Practical advice on how to use R for powerful and innovative data analyses.
- Data Skeptic: Topics include data science, machine learning, and artificial intelligence.
- Talk Python To Me: Python and related technologies.
- Data Stories: Data visualization.
- Ladybug Podcast: Three women in tech debugging the industry.
Resource Collections
- Data Science Learning Resources (MBAStack): Resources about data science, statistics, and careers. (Thank you Lyndhurst STEM Club for sharing!)