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.
Overview
Syllabus
Introduction
- Data science: Ask me anything
- 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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