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Women in Data
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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

  1. ٠٥‏/١٢‏/٢٠٢٤

    Innovation and Data Science Leadership

    (00:01:02) Role and responsibilities explained (00:01:39) AI impact on analytics maturity (00:02:17) Analytics maturity study findings (00:03:01) Reflections on industry progress (00:03:39) Leadership gaps and silos (00:04:27) Breaking down organizational silos (00:04:53) Accessibility in data tools (00:05:24) Data tools transforming organizations (00:05:55) Growing demand for data insights (00:06:47) Value of data science roles (00:07:04) Opportunities and challenges in analytics (00:07:56) Workflow automation in practice (00:08:15) Empowering subject matter experts (00:09:54) Automating insights delivery explained (00:11:04) Automation examples in finance (00:11:49) Workflow automation benefits highlighted (00:12:12) Leadership strategies across industries (00:13:03) Helping people realize potential (00:14:11) Overcoming self-limiting beliefs (00:15:19) Leadership advice for contributors (00:16:06) Creating internal user groups (00:17:11) Demonstrating leadership opportunities (00:18:24) Practical ways to show leadership (00:19:32) Recognizing strengths in others (00:20:27) Lessons on articulating value (00:23:02) Asking “why” to find impact

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  2. Advancing AI through Data Engineering in Pharmaceuticals

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    Advancing AI through Data Engineering in Pharmaceuticals

    (00:00) Introducing Catherine Shen’s Career(00:32) Transition from Luxury to Pharma(01:55) Role of Data in Pharma(02:52) Evolution of Data Engineering(04:06) Innovative Data Solutions Impact(07:23) AI’s Role in Pharma Industry(10:24) Future AI Investments and Strategy(13:09) Solving Unstructured Data Challenges(14:02) Partnering with Math Company(16:44) Measuring Success in Partnerships(20:05) Pivotal Leadership Moments(23:22) Believing in Innovation and Confidence(25:29) Balancing Personal and Professional Life(26:12) Building Confidence Over Time(30:55) Creating Innovative Healthcare Collaborations(33:02) Confidence Grows with Tenacity(34:38) Excitement for the Future of Data(36:39) Catherine’s Closing Remarks

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  3. The AI Insider: Data Curation and Privacy Mastery with Jigyasa Grover

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    The AI Insider: Data Curation and Privacy Mastery with Jigyasa Grover

    (00:00) Intro: Negative connotations in AI(00:21) Synthetic data fills gaps(00:35) Guest introduction(01:23) Importance of data quality(02:14) Data-centric machine learning focus(03:02) Bias mitigation strategies(03:41) Role of human in AI loop(04:34) Synthetic data in AI(05:29) Pre-trained models and data quality(06:02) Experiments with data quality(06:39) Leading AI and research projects(07:24) Explainability in AI models(08:57) Privacy concerns in AI analysis(10:34) Open source model benchmarking(11:33) Motivation for open source contributions(12:28) Long-term open source involvement(13:50) Mentoring in open source projects(15:19) Starting with open source(16:35) Contributing beyond code(17:50) Building community through collaboration(18:48) Power of open source accessibility(19:52) Open source challenges(20:38) Success factors for open source projects(22:58) Career-defining moments(24:49) First encounter with open source(26:28) Introduction to AI through NLP(28:02) Pivoting from PhD to industry(29:02) Career lessons and continuous learning(30:13) Advice for women in tech

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  4. GenAI effects on the job market and hiring

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    GenAI effects on the job market and hiring

    (01:22) Research on skills and technology(01:47) Changes in job search methods(02:29) Algorithmic hiring and firm adaptations(03:25) New roles from technology(04:54) Ripple effects of technological changes(06:06) Skating to where the puck is(07:07) Building future-proof skills(08:02) AI tools in daily work(09:00) AI's impact on jobs(10:08) Mega trends: technology, climate, demographics(11:17) Testing tools and adapting workflow(12:44) AI and future of hiring(13:45) Longer time to hire with tech(15:34) AI reshaping the labor market(17:03) Gaining skills for complex roles(18:20) Turing Trap: AI vs human augmentation(19:05) Challenges for early career seekers(20:26) Mentorship and human capital development(21:41) Updating skills before job transitions(23:21) Impact of job loss on earnings(24:52) Career conversations and landscape awareness(26:31) Advice for young researchers(27:24) Staying motivated through research

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  5. GenAI Use Cases and the Road Ahead

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    GenAI Use Cases and the Road Ahead

    (Intro 00:00:00) Generative AI discomfort. (00:00:36) Excited for data and MLOps. (00:01:10) First one-on-one chat. (00:02:29) Career transitions and "aha" moments. (00:03:05) Bored easily, switched roles. (00:05:22) Starting with startups. (00:07:27) Learning skills at startups. (00:09:26) Startups vs. big companies. (00:11:55) Best time to join startups. (00:13:41) Risky career, conservative money. (00:15:27) Startups in twenties ideal. (00:16:03) Label Box overview, responsibilities. (00:19:50) Importance of data quality. (00:24:05) Exciting Gen AI use cases. (00:27:56) Future of AI agents. (00:31:12) Justifying data quality investment. (00:36:54) AI concerns and excitement. (00:42:50) Building your community.

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  6. Navigating the AI Frontier: Leadership Lessons and Insights

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    Navigating the AI Frontier: Leadership Lessons and Insights

    Join Women in Data's Datathon for free here: (https://womenindata.mn.co/spaces/10708034/about) (00:00:21) Importance of soft skills for technical professionals (00:00:39) Introduction to the guest's extensive career and leadership in the military and data fields (00:01:16) Discussion on breaking barriers in a male-dominated field (00:01:45) Leadership journey and pivotal moments in career (00:02:12) Starting a non-traditional career and early involvement with data (00:03:04) Returning to federal service after 9/11 and subsequent roles in intelligence (00:03:30) Impact of being selected as a White House leadership fellow (00:04:25) Importance of breadth and depth in skill development (00:05:19) How to lead without authority or official title (00:06:02) Developing emotional intelligence (EQ) and soft skills (00:06:27) Importance of partnerships and collaboration in the data and AI community (00:07:03) Challenges of soft skills for technical professionals (00:07:45) Practical advice for developing soft skills and teamwork (00:08:44) Peer mentoring and the value of collaborative learning (00:09:54) Adaptability in a rapidly changing tech environment (00:10:38) The need to dream big and be prepared for future roles (00:11:09) Lifelong commitment to curiosity and upskilling (00:12:00) Encouragement to apply for challenging roles (00:13:10) Starting an office from scratch as a Chief Data Officer (00:14:15) Using an agile approach to deliver capability and value (00:15:16) Building partnerships and collaborating with military executives (00:16:27) Importance of strategic communication in leadership (00:17:34) Balancing technical skills with leadership responsibilities (00:18:22) Fostering innovation and creativity within data and AI teams (00:19:34) Hosting hackathons and datathons to solve hard problems (00:21:00) Providing a safe environment for team creativity and risk-taking (00:21:51) Balancing technical knowledge with leadership roles (00:22:48) Staying current through teaching and continuous learning (00:24:13) Teaching as a way to learn and stay relevant (00:25:01) Encouraging participation in datathons and hackathons (00:25:52) Advice for emerging leaders on staying relevant and dreaming big (00:27:30) The importance of lifelong learning and curiosity (00:27:55) Plans after retirement and ongoing impact in the data field (00:30:10) Building the next generation of leaders through volunteering and advising

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  7. Unveiling Data Odyssey

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    Unveiling Data Odyssey

    (00:00:00) Intro (00:00:22) Introduction to Snowflake and AI (00:00:34) Guest introduction and background (00:00:57) Excitement about the conversation (00:01:13) Impressions of Snowflake's office (00:01:21) Discussion on Snowflake Summit and AI/ML announcements (00:01:52) Overview of Snowflake as a unified platform (00:02:16) Evolution of Snowflake from data warehousing to AI (00:02:37) AI features and tools in Snowflake (00:02:55) Announcements at Snowflake Summit (00:03:05) Getting started with Snowflake (00:03:16) Starting with Snowflake based on specific roles (00:03:45) Specialization within Snowflake's platform (00:03:55) Deciding where to start with Snowflake (00:04:25) Importance of Python and SQL in Snowflake (00:05:35) Snowflake as a platform for various roles (00:05:57) Snowflake's learning platform and resources (00:06:05) Overview of Snowflake's developer resources (00:06:17) Introduction to Snowflake's North Star program (00:06:53) North Star courses for different workloads (00:07:13) North Star's foundation course (00:07:35) Learning paths within North Star (00:07:59) Availability of North Star courses on Coursera (00:08:34) Discussion on teaching generative AI courses (00:09:18) Differences between teaching online and live talks (00:09:37) Experiences in writing scripts for courses (00:10:30) Challenges in creating course content (00:11:29) Tips for writing course scripts (00:11:50) Experiences in teaching and content creation (00:12:12) Changes in NLP and language models over the years (00:12:24) Evolution of interest in NLP (00:13:21) Excitement about the resurgence of NLP (00:14:07) Shift in momentum for AI research (00:14:38) Concerns about the use of generative AI (00:14:59) Misuse of LLMs in outdated tasks (00:15:54) Pessimism about the overuse of LLMs (00:16:15) Exploring correct use cases for LLMs (00:16:29) Potential use cases for LLMs (00:17:04) Example of Snowflake's internal use of LLMs (00:17:25) Chatbots as a first line of defense in support (00:18:19) Content generation with LLMs (00:18:40) Example of a content engine using LLMs (00:19:23) Excitement about enterprise use of LLMs (00:19:59) Benefits of internal knowledge sharing using LLMs (00:20:03) Use cases for LLMs in organizations (00:21:04) Encouragement to stick with niche interests (00:21:50) Shift in focus from computer vision to NLP (00:22:01) Advice for PhD students on choosing specializations (00:22:35) Importance of following research trends (00:23:15) Recommendations for getting started in NLP (00:24:18) Importance of understanding fundamentals in NLP (00:24:28) Starting with core NLP papers (00:24:58) Keeping up with new research in AI (00:25:05) Strategies for staying updated on AI research (00:26:23) Following key figures in AI on social media (00:26:45) Trends in AI research and their impact (00:27:14) Challenges in staying current with AI papers (00:27:43) Use of social media for AI research (00:28:27) Academic communities on different platforms (00:29:36) Visual learning in AI education (00:29:55) Excitement about the future of AI (00:30:06) AI's impact across industries (00:30:15) Exploration of new use cases in AI (00:30:46) Examples of creative AI use cases (00:31:32) Curiosity about AI's future impact on industries (00:31:50) Potential changes in education through AI (00:33:05) Excitement about new AI-driven education tools (00:33:40) Personalized education with AI (00:33:47) The future of women in data and tech

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  8. Breaking Barriers in Data Science

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    Breaking Barriers in Data Science

    Data Bytes listeners get an exclusive discount to join Women in Data. ⁠⁠⁠⁠⁠View discount here. (Intro 00:00:00) Introduction by Maggie (00:00:19) Data science roles evolving (00:00:34) Guest Introduction - Maggie Ma (00:00:56) Maggie’s diverse data science background (00:01:12) What drew Maggie to data? (00:01:35) University majors and early internships (00:02:37) Discovering geospatial data science (00:03:08) Predicting COVID-19 spread (00:03:29) Logistics and transportation data science (00:03:34) Geospatial data complexity (00:04:13) Advice for geospatial data work (00:04:43) Maggie’s journey to freelancing (00:05:55) Impact and imposter syndrome (00:06:03) Research team experiences (00:07:13) Content creation feedback (00:08:09) Overcoming imposter syndrome (00:08:36) Challenges in tech industry (00:09:57) Handling imposter syndrome daily (00:10:20) Focus on self-improvement (00:11:32) Authenticity on social media (00:12:14) Behind the scenes content (00:13:03) Sharing authentic daily lives (00:13:41) Building a social media presence (00:14:39) Staying updated in data science (00:15:50) Managing information overload (00:16:59) Career moves within data science (00:17:27) Unplanned career progression (00:18:03) Switching roles within data (00:19:10) AI’s impact on data jobs (00:19:31) Specific roles in data science (00:20:10) Lower barrier of entry (00:21:30) Using AI to debug code (00:22:00) Advice for aspiring data scientists (00:22:42) Importance of reflection (00:23:49) Making peace with your path (00:24:13) Future business and personal growth (00:24:33) Building an AI startup (00:25:42) Customized data science projects app (00:26:27) Target release date for app (00:27:01) Incorporating AI in learning (00:28:07) Encouraging the community

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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

المعلومات

  • صناع العمل
    Women in Data
  • سنوات النشاط
    ٢٠٢١ - ٢٠٢٤
  • الحلقات
    ١٣٠
  • التقييم
    ملائم
  • حقوق النشر
    © Women in Data
  • موقع البرنامج على الويب
    Data Bytes