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LinkedIn Learning

DJ Patil: Ask Me Anything

via LinkedIn Learning

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Overview

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Join former U.S. chief data scientist DJ Patil, as he tackles questions posed by LinkedIn members. Topics range from data security to the future of data science.

Syllabus

Introduction
  • Data science: Ask me anything
Previous Installments
  • What were you like as a kid?
  • How did your parents influence you?
  • How did you navigate college?
  • What are some fond memories from grad school?
  • How can we foster learning for everyone?
  • What's the importance of learning liberal arts?
  • What advice do you have for job seekers?
  • How did data science come about?
  • What does it take to be a data scientist?
  • Why is apprenticeship important?
  • How can a data scientist influence policy?
  • How can I prepare for data science in college?
  • How can hackathons benefit me?
  • How did you use data in grad school?
  • How is data used in the US?
  • How is data used worldwide?
  • How do you expose holes in cybersecurity?
  • How can we educate people about hacking?
  • What are the real threats to personal data?
  • Should we focus on media headlines?
  • How can we educate people about data use?
  • How can people fight for data privacy?
  • What's the role of the data scientist in 15 years?
  • What are you working on currently?
  • How can we make data secure?
  • How to serve the people with data science?
  • What's the difference between wisdom and experience?
  • How do you advocate for science?
  • What is the role of AI in today's world?
  • What's an example of ethical hacking?
  • How do you bring data science into the workplace?
  • What is the role of AI in human resources and recruiting?
  • What are tools every data scientist should own?
  • Is there a data science code of ethics?
  • What are AI threats in the cybersecurity world?
  • How can data scientists better inform the general public?
  • How can people participate in data science?
  • Why do people fear a machine revolution?
  • How can data inform healthcare?
  • Why should we democratize data?
  • How are you advocating for science?
  • Why is the march for science important?
  • What is AI?
  • What is an example of robust machine learning?
  • What is AI's place in healthcare?
  • How can AI impact clinical trials?
  • How can a data scientist be best leveraged for business?
  • What does a data science team need to thrive?
  • What are the pros and cons with AI in HR roles?
  • What should be in a data scientist's toolbox?
  • What makes up a good data science team?
  • What new projects are you working on?
  • What data science projects are you working on?
  • How can AI and machine learning (ML) help cybersecurity?
  • How can governments fight back against AI attacks?
  • What can the public do to protect against AI attacks?
  • What are neural networks (NN)?
  • What's the difference between ML and NN?
  • Do you have a favorite machine learning technique?
  • How does the Internet of Things work?
  • What is a connected city?
  • What is the fear associated with data?
  • How can we address the fear of machines taking jobs?
  • What about job loss due to AI?
  • What's the reality of bringing back jobs?
  • What is a scientific process for data science?
  • What is your tip for not getting overwhelmed by big data?
  • How do you accept that you're not going to know stuff?
  • What is a dynamic range?
  • When does data leave holes?
  • How important is diversity on a data science team?
  • How does data influence people's emotions?
  • How do you train yourself to be intellectually curious?
  • How do we empower people to foster dialogue?
  • What is your philosophy on leadership?
  • How can a company retain employees?
  • How do you cultivate employee development?
  • How do you identify algorithmic biases?
  • Can you describe the process of ethical testing?
  • How do you feel about machine learning for business decisions?
  • Can you talk about your book?
  • What are possible solutions for displacement?
  • What impact does technology have on the US economy?
  • Can you discuss the future of intelligent things?
  • What are the current issues with data collection?
  • How is technology changing human expectations?
  • Wrapping up

Taught by

DJ Patil

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4.6 rating at LinkedIn Learning based on 56 ratings

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