Data Bytes Women in Data
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- Technology
Your bite-sized dose of data stories, professional interviews, and latest trends in the world of data. Join the Women in Data Community here: https://womenindata.mn.co/sign_up Support this podcast: https://podcasters.spotify.com/pod/show/women-in-data/support
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Retrieval Augmented Generation and the Evolution of Data Science Roles
[00:00:00] Intro and discussion on information retrieval
[00:00:36] Sadie welcomes Harpreet, discussing his achievements and connections
[00:01:46] Early interactions and courses between Harpreet and Sadie
[00:02:27] Updates on Sadie's SQL course and new roles
[00:03:42] Harpreet discusses following curiosity in his career and AI's growth
[00:06:55] Future of data science roles and specialization within the field
[00:09:40] Unique skills of data scientists and transition to deep learning
[00:15:23] Discussion on benchmarks, datasets, and introduction to retrieval augmented generation (RAG)
[00:20:16] Explanation and potential applications of RAG models
[00:24:09] AI applications in various industries and predictions for future AI integration
[00:29:02] Harpreet's personal productivity gains from AI and new tools enhancing workflows
[00:34:58] Harpreet's podcast impact on his career and future plans
[00:40:44] Recommendations for staying updated in deep learning
[00:45:36] Harpreet invites listeners to join his new research initiative
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Effective Strategies for Data and AI Literacy
Intro [00:00:00]
Priscila discusses the importance of an accessible data infrastructure and data literacy.
[00:00:41] Sadie:
Introduction of Priscila Papazisis, her achievements and roles.
[00:01:06] Sadie:
Discussion on AI and data literacy strategies for organizations.
[00:01:27] Priscila:
Priscila responds about strategies for fostering data literacy in organizations.
[00:02:03] Priscila:
Importance of executive support in building a data-driven culture.
[00:02:36] Priscila:
Training programs for data literacy across various companies.
[00:03:05] Priscila:
Reiteration of the need for accessible data infrastructure.
[00:03:42] Priscila:
Emphasizes employee engagement with data for decision-making.
[00:04:12] Priscila:
Continuous improvement and promoting an environment for feedback.
[00:04:36] Sadie:
Challenges in providing and encouraging training in organizations.
[00:05:07] Priscila:
Finding time and interest for employee training in a busy schedule.
[00:06:25] Priscila:
Importance of understanding statistical concepts, data visualization, and AI in business.
[00:07:39] Priscila:
Critical thinking and application of AI and machine learning in business.
[00:08:20] Priscila:
Understanding industry trends and market dynamics.
[00:08:50] Sadie:
Priscila shares examples of business value from data literacy programs.
[00:09:10] Priscila:
Story about enhancing logistics in a health insurance company.
[00:10:23] Priscila:
The impact of data literacy programs she initiated.
[00:11:16] Priscila:
Operational improvements from data-driven decisions.
[00:12:42] Priscila:
Importance of practical results from data products.
[00:13:19] Priscila:
Engaging in continuous learning and leveraging data literacy.
[00:14:10] Sadie:
Discussing common pitfalls in implementing data and AI programs.
[00:14:28] Priscila:
Key challenges and advice for data and AI program implementation.
[00:16:45] Sadie:
Advice for individuals improving their data and AI literacy.
[00:17:09] Priscila:
Recommended resources and personal approaches to data literacy.
[00:18:37] Priscila:
Emphasis on data storytelling and problem-solving with data.
[00:20:42] Sadie:
The role of storytelling in data and AI.
[00:21:11] Sadie:
Priscila's journey into the data field.
[00:22:10] Priscila:
Career path and evolution in data roles.
[00:23:16] Priscila:
Contributions to the data community and networking.
[00:25:36] Sadie:
The value of community in data and AI.
[00:26:27] Sadie:
Final advice for women in data and AI careers.
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How to cultivate a growth mindset
[00:00:00] - Ania discusses her approach to energy use and following curiosity without questioning its practicality.
[00:00:34] - Introduction of Ania Cwojdzinska as a vibrant member of the Women in Data community, mentioning her background and achievements.
[00:01:24] - Sadie asks Ania about the intersection of data science and psychology and how Ania incorporates both in her work.
[00:03:02] - Ania shares her journey into data science during her PhD, highlighting the benefits of interdisciplinary approaches.
[00:04:52] - Discussion on the rigors of academic research and its relevance to data careers.
[00:05:47] - Ania talks about her surprise at the continued use of Excel in industry and the transition from academia to industry.
[00:08:05] - Sadie inquires if Ania has started using Excel in her industry work.
[00:08:27] - Exploring Ania's growth mindset and whether it was innate or developed over time.
[00:10:46] - Ania discusses leading the growth group for Women in Data and the various activities and workshops they conduct.
[00:13:35] - The unique aspects of the Women in Data growth group and its contribution to the community.
[00:14:42] - The inclusivity and openness of the Women in Data community.
[00:15:33] - Ania reflects on her advice for women in data careers, emphasizing self-awareness and the blend of personal interests with professional skills.
[00:20:16] - Sadie thanks Ania for her mentorship and contributions to the community.
[00:20:45] - Ania shares her most proud accomplishments: fostering lifelong friendships and achieving self-contentment.
[00:24:31] - Sadie and Ania discuss redefining success and the importance of being comfortable and happy with oneself.
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Measuring the Value of AI Solutions
Discussion on AI in Business
[00:01:00] Sadie introduces the main conversation topics.
[00:01:20] Cal shares his anticipation for future meetups.
[00:01:26] Discussion on the rapid developments in AI.
[00:02:03] Key indicators companies overlook when identifying AI opportunities.
[00:02:28] Cal elaborates on challenges and solutions in AI opportunity realization and measurement.
[00:03:41] Approaches to mapping out the value of AI projects.
[00:04:53] Sadie questions the average time to see benefits from AI implementation.
[00:05:52] Cal discusses AI implementation timelines and the importance of build vs. buy decisions.
[00:08:20] Discussion on successful integration of AI into workflows and overcoming adoption barriers.
[00:09:23] The role of AI literacy in preventing unintended consequences.
[00:13:08] Conversation shifts to responsible AI and baseline principles for ethical considerations.
[00:14:16] Cal emphasizes the comprehensive nature of responsible AI beyond ethics.
[00:20:33] Cal shares his journey to founding Panda Data and its acquisition.
[00:24:52] Discussion on navigating the challenges in highly regulated industries.
[00:27:41] Cal's personal motivations and overcoming obstacles.
[00:32:09] What's next for Cal at Further and the vision for AI auditing practice.
[00:36:14] Cal shares his personal goal of visiting 100 countries and its relevance to understanding AI and data science.
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Women in AI
Intro & Discussion on AI Career and Passion00:00:00 - Introduction and advice on pursuing AI as a career.00:00:17 - The importance of passion and intellectual rigor in AI.
Erica's Background & Journey into AI00:00:32 - Introduction to Erica Luna Lee: her background in tech and founding Women of AI.00:01:16 - Erica's entry into the AI space and her journey from research to tech leadership.
Moving to Silicon Valley & Building a Community00:02:10 - Erica's move to Silicon Valley and the importance of community in career development.00:03:09 - The unique ecosystem of Silicon Valley for technology and innovation.
Career Advancement & Challenges00:04:12 - Insights on career advancement and the significance of choosing the right manager.00:09:06 - Discussing the challenges for women in leadership roles and how to navigate them.
The Importance of Support Systems00:12:47 - The critical role of support systems for female executives and founders.00:16:51 - Erica shares advice for female founders and the importance of having a supportive network.
Personal Growth & Finding Balance00:22:49 - Erica talks about personal growth, balancing work with personal life, and the importance of hobbies and social connections.
Outlook on AI and Future Technologies00:34:14 - Erica's take on the current state of AI and speculation on future waves of technology innovation.
Closing Remarks00:39:52 - Final thoughts and encouraging words from Erica.00:40:03 - Outro and information on joining Women in Data.
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Machine Learning Ops
Dive into the world of Machine Learning Operations (MLOps) with the remarkably insightful Maria Vechtomova. She is an MLOps Tech Lead at Ahold Delhaize and Co-Founder of Marvelous MLOps.
TimeStamps:
00:00:00 - Introduction to the episode with Maria Vechtomova.
00:00:32 - Sadie introduces Maria Vechtomova and her career.
00:01:06 - Maria expresses her appreciation for the DataBytes podcast.
00:02:06 - Conversation about past experiences with piano lessons.
00:03:12 - Maria's transition from economics to data and MLOps.
00:04:31 - The impact of having inspiring colleagues.
00:06:07 - Discussion on the value of freedom and management styles in Maria's career.
00:07:14 - Maria talks about the founding of Marvelous MLOps.
00:09:09 - The impact of publishing articles and LinkedIn engagement.
00:10:39 - How the field of MLOps has evolved over the years.
00:14:10 - The state of MLOps practices in the industry.
00:16:27 - Advice for data scientists on best practices for MLOps collaboration.
00:18:19 - Ideal handoff models between data engineering, data science, and MLOps teams.
00:20:58 - Describing a typical week for an MLOps engineer.
00:24:21 - How to balance leadership and technical knowledge.
00:26:26 - Discussing the representation of women in MLOps and tech.
00:29:51 - Conclusion and thanks to Maria and listeners.
00:30:05 - Outro with an advertisement for Women in Data community memberships.
Join Women in Data as a Member: https://womenindata.mn.co/plans/389742?bundle_token=786e315f336334cfdfd416404db1fbf5&utm_source=manual
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Support this podcast: https://podcasters.spotify.com/pod/show/women-in-data/support