DJ Patil on Data Science: The Ask Me Anything Conversations

Course details

DJ Patil—the former United States Chief Data Scientist—boasts a unique perspective on the future, risks, and all-around power of data. In addition to shaping policies at the White House, he's authored influential academic papers and served as head of data products at LinkedIn, where he helped to coin the term "data scientist." In this single-course compilation of the popular weekly series, DJ tackles questions posed by LinkedIn members, diving into topics ranging from data security to the future of data science.

Learning objectives
Learn about DJ Patil’s personal journey—from what he was like as a kid and how he navigated college to how he advocates for science and educates people on data use.
Find out what DJ thinks about preparing for data science in college, job seeking, apprenticeships, and hackathons.
Get insights on the role of the data scientist in 15 years and how to serve people with data science.
Listen to DJ’s expert insights into cybersecurity, hacking, data privacy, and AI in today’s world.
Explore the difference between wisdom and experience, fear of a machine revolution, the role of data and healthcare, and more.

Concepts

0. Introduction

01 - Data science - Ask me anything

1. The Questions You Asked DJ Patil

02 - What were you like as a kid
03 - How did your parents influence you
04 - How did you navigate college
05 - What are some fond memories from grad school
06 - How can you foster learning for everyone
07 - What's the importance of learning liberal arts
08 - What advice do you have for job seekers
09 - How did data science come about
10 - What does it take to be a data scientist
11 - Why is apprenticeship important
12 - How can a data scientist influence policy
13 - How can you prepare for data science in college
14 - How can hackathons benefit me
15 - How did you use data in grad school
16 - How is data used in the U.S.
17 - How is data used worldwide
18 - How do you expose holes in cybersecurity
19 - How can you educate people about hacking
20 - What are the real threats to personal data
21 - Should you focus on media headlines
22 - How can you educate people about data use
23 - How can people fight for data privacy
24 - What's the role of the data scientist in 15 years
25 - What are you working on currently
26 - How can you make data secure
27 - How to serve the people with data science
28 - What's the difference between wisdom and experience
29 - How do you advocate for science
30 - What is the role of AI in today's world
31 - What's an example of ethical hacking
32 - How do you bring data science into the workplace
33 - What is the role of AI in human resources and recruiting
34 - What are tools every data scientist should own
35 - Is there a data science code of ethics
36 - What are AI threats in the cybersecurity world
37 - How can data scientists better inform the general public
38 - How can people participate in data science
39 - Why do people fear a machine revolution
40 - How can data inform healthcare
41 - Why should you democratize data
42 - How are you advocating for science
43 - Why is the March for Science important
44 - What is AI
45 - What is an example of robust machine learning
46 - What is AI's place in healthcare
47 - How can AI impact clinical trials
48 - How can a data scientist be best leveraged for business
49 - What does a data science team need to thrive
50 - What are the pros and cons of AI in HR roles
51 - What should be in a data scientist's toolbox
52 - What makes up a good data science team
53 - What new projects are you working on
54 - What data science projects are you working on
55 - How can AI and machine learning (ML) help cybersecurity
56 - How can governments fight back against AI attacks
57 - What can the public do to protect against AI attacks
58 - What are neural networks (NN)
59 - What's the difference between ML and NN
60 - Do you have a favorite machine learning technique
61 - How does the Internet of Things work
62 - What is a connected city
63 - What is the fear associated with data
64 - How can you address the fear of machines taking jobs
65 - What about job loss due to AI
66 - What's the reality of bringing back jobs
67 - What is a scientific process for data science
68 - What is your tip for not getting overwhelmed by big data
69 - How do you accept that you're not going to know stuff
70 - What is a dynamic range
71 - When does data leave holes
72 - How important is diversity on a data science team
73 - How does data influence people's emotions
74 - How do you train yourself to be intellectually curious
75 - How do you empower people to foster dialogue
76 - What is your philosophy on leadership
77 - How can a company retain employees
78 - How do you cultivate employee development
79 - How do you identify algorithmic biases
80 - Can you describe the process of ethical testing
81 - How do you feel about machine learning for business decisions
82 - Can you talk about your book
83 - What are possible solutions for displacement
84 - What impact does technology have on the U.S. economy
85 - Can you discuss the future of intelligent things
86 - What are the current issues with data collection
87 - How is technology changing human expectations

2. Parting Thoughts for Now from DJ Patil

88 - Wrapping up

DJ Patil on Data Science: The Ask Me Anything Conversations

Authors

DJ Patil

Course details

Skills covered

Concepts

0. Introduction

1. The Questions You Asked DJ Patil

2. Parting Thoughts for Now from DJ Patil