Data science and web development are both growing fields with strong job prospects. Data science involves analyzing data to solve problems and find insights, while web development focuses on building interactive websites and applications. Some key differences are that data science often requires more advanced technical skills and mathematics training, while web development places more emphasis on designing user experiences. Both fields offer opportunities for remote and flexible work. Thinkful provides guided learning programs to help students explore these fields and land jobs through project-based learning and mentorship.

1. bit.ly/tf-web-vs-ds

2. Introductions
➔ What's your name?
➔ What brought you here today?
➔ What is your programming experience?

3. About
Thinkful
We train web developers and
data scientists through 1x1
mentorship and project-based
learning.
Guaranteed.

4. ➔ What is Data Science?
➔ What is Web development?
➔ How's the job market for both?
➔ How do I know if I'm geared for either?
➔ Next steps
Goals

5. What
is
Data
Science?

6. 1. Form a Question
2. Collect the Raw Data
3. Explore the Data
4. Communicate Results
The
Data
Pipeline

7. The
Data
Pipeline

8. ➔ The Researcher
➔ The AI or Automation Guru
➔ The Statistician
➔ The Super Analyst
Four
Types
of
Data
Scientists

9. ➔ The first data scientists
➔ Often have PhD’s or other advanced degrees
➔ Research background (often in academia)
➔ Research at big companies
➔ Google, Microsoft, etc all have research
departments
➔ Become Teachers themselves
➔ Government agencies
The
Researcher

10. ➔ Work on cutting edge research - the HOW
◆ The first facial recognition software
◆ Self driving cars
➔ Start by getting a PhD or graduate degree
➔ Then learn to code
The
Researcher

11. ➔ They love to code
➔ Mostly from scratch
➔ Work at big companies and startups
◆ There are over 3,000 Artificial Intelligence
startups on AngelList
◆ (if you don't know what AngelList is...)
The
AI
Guru

12. ➔ Chatbots and automated assistants (Siri, Alexa,
Einstein, Will.i.Am, etc)
➔ Automated Support
➔ Really just automating anything
➔ Replacing humans, adding efficiency
➔ Write code for everything
➔ Try to automate your own life or routines
➔ Python/JavaScript
The
AI
Guru

13. ➔ Formal mathematics or statistics training
➔ Lots of Masters in Statistics (shocking)
➔ Not necessarily experienced programmers
➔ May use tools like STATA or R
➔ Statistical consultants
◆ Political polling as an example
➔ Experimentation experts
◆ A/B testing
◆ Future Predicting
The
Statistician

14. ➔ Answer statistical questions with data
◆ Are these things different?
◆ What is the most likely outcome?
➔ Usually don’t build consumer products
➔ Study the math/probability
➔ Elements of Statistical Learning is a
great place to start
But the AI gurus may be automating a lot of
these jobs away...
The
Statistician

15. ➔ This is the fastest growing section of data science
➔ Love numbers and products, and want to put the two
together
➔ Expert problem solvers through code
➔ Can communicate those solutions
➔ Different from a Data Analyst (machine learning)
The foot-soldiers of the data science revolution...
The
Super
Analyst

16. ➔ Every company that generates data
◆ Every app and website records enormous
amounts of data
◆ What can be learned from that data
➔ So basically everywhere...
The
Super
Analyst

17. ➔ They don’t necessarily build consumer
products, but find consumer insights
◆ Who’s going to be our next customer?
◆ What’s our growth going to be next month?
◆ Will this person click on our ad?
➔ Learn to code
➔ Immerse yourself in data
➔ Learn some basic Machine Learning
The
Super
Analyst

18. Growth
in
the
Job
Market

19. Growth
in
the
Job
Market

20. What
is
Web
Development?

21. Types
of
Developers
1. Frontend Engineer: using technologies such as HTML,
CSS, and JS to create interactive experiences
through websites
2. Backend Engineer: creating applications that deliver
data to websites, mobile apps, or databases.

22. Types
of
Developers
1. Full Stack Engineer: a rare breed of developers
that can do both frontend and backend engineering
2. QA Engineer: creating and running tests for code
that is written by other developers to help catch
bugs before the code is made live

23. Coding
Plus
Roles
➔ Product Manager (Coding + Product)
◆ someone who understands the business goals
of a customer and can create product
requirements to give to developers.
◆ Layman -> Technical
➔ Growth Hacker (Coding + Marketing)
◆ someone who can use data and analytics to
come up with experiments on how to
increase traffic to a website or social
media profile

24. Coding
Plus
Roles
➔ Sales Engineer (Coding + Sales)
◆ understanding coding can be extremely
helpful in a sales role. Come out of the
basement nerd.
➔ Data Scientist (Coding + Data)
◆ someone who can use statistics and
programming to find valuable insights
from extremely large datasets

25. Growth
in
the
Job
Market

26. Market
Growth:
Compared

28. Which
is
Right
For Me?

29. Interests &
Personality:
Data
Scientists

30. ➔ Have a graduate degree or a strong,
quantitative academic background
◆ Statistician or a Researcher
➔ Are an experienced engineer
◆ You could be an AI guru
➔ Love data, and analysis, and want to find the
‘signal in the noise’
◆ You could be a Super Analyst
Interests &
Personality:
Data
Scientists

31. Interests &
Personality:
Web
Developers

32. Interests &
Personality:
Web
Developers ➔ If you enjoy designing and creating user
experiences that others can enjoy
◆ Front-End Engineer or Full-Stack Engineer
➔ If you love organizing data in tables,
manipulating & sending data
◆ Back-End Engineer or Full-Stack engineer
➔ If you like catching bugs or creating tests to
make sure features pass or fail
◆ QA Engineer

33. Ways
To
Keep
Learning

34. ➔ Python & Statistics or HTML/CSS & JavaScript
➔ Personal Program Manager
➔ Unlimited Q&A Sessions
➔ Student Slack Community
➔ bit.ly/freetrial-ds
➔ bit.ly/freetrial-webdev
Thinkful
Two-Week
Free
Trial

35. The
Student
Experience
Marnie Boyer, Thinkful Graduate
Capstone
Wolfgang Hall, Thinkful Graduate
Capstone