Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Getting into Data Science @ HisarCS 2021

Getting into Data Science @ HisarCS 2021

Slides for my introduction to Data Science given at the Hisar Coding Summit 2021: http://event.hisarcs.com/en.html

Talk description:
This is a brief introduction to Data Science with an overview on some interesting problems that it can tackle. The talk is mainly aimed at students who are interested in knowing more about Data Science, and it will try to answer the question "what do data scientists do all day?", in order to offer some insights on whether you should consider a career in Data Science and how to start building your Data Science skill set.

Marco Bonzanini

April 16, 2021
Tweet

More Decks by Marco Bonzanini

Other Decks in Education

Transcript

  1. Getting into
    Data Science
    @MarcoBonzanini
    Hisar Coding Summit 2021

    View Slide

  2. Nice to meet you
    • Data Science consultant:
    Natural Language Processing,
    Machine Learning,
    Data Engineering
    • Corporate training:
    Python + Data Science
    • PyData London chairperson
    2

    View Slide

  3. My Goals for Today
    • Answer some questions:
    What is Data Science?
    What do Data Scientists do?
    (and more)
    • Inspire some of you to learn
    more about Data Science
    3

    View Slide

  4. WHAT IS
    DATA SCIENCE

    View Slide

  5. 5

    View Slide

  6. 6

    View Slide

  7. Data
    Value
    🦄
    7

    View Slide

  8. Data
    Value
    🦄
    ???
    8

    View Slide

  9. Value
    Insights
    Decision making
    Data products
    {
    9

    View Slide

  10. 10

    View Slide

  11. 11

    View Slide

  12. 12

    View Slide

  13. Data
    Value
    🦄 ???
    13

    View Slide

  14. Coding
    Math Modelling
    Visualisation
    Reporting
    {
    🦄
    14

    View Slide

  15. Source: Doing Data Science (Cathy O’Neil & Rachel Schutt, 2013)
    Raw

    Data
    Processing

    Data
    Clean

    Data
    Exploratory

    Analysis
    Models &

    Algorithms
    Communicate

    Visualise

    Report
    Data

    Product
    Decision

    Making
    15

    View Slide

  16. Source: https://medium.com/hackernoon/the-ai-hierarchy-of-needs-18f111fcc007
    16

    View Slide

  17. Source: http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram
    17

    View Slide

  18. Computer
    Science?
    18

    View Slide

  19. Software
    Engineering?
    19

    View Slide

  20. Business
    Intelligence?
    20

    View Slide

  21. Do you need
    3 PhD?
    21

    View Slide

  22. 🤝
    Computer

    Science
    Statistics
    Domain
    Expertise
    22

    View Slide

  23. ARE WE ALL
    DATA SCIENTISTS?

    View Slide

  24. Source: https://medium.com/hackernoon/the-ai-hierarchy-of-needs-18f111fcc007
    24

    View Slide

  25. 25
    Software Engineers
    Data Engineers

    View Slide

  26. 26
    ML Engineers

    View Slide

  27. 27
    Data Analysts

    Business Analysts

    View Slide

  28. 28
    Data Scientists

    View Slide

  29. 29
    Research Scientists

    View Slide

  30. 30
    Data Scientists

    at small corp

    View Slide

  31. DATA SCIENCE
    APPLICATIONS

    View Slide

  32. Weather
    32

    View Slide

  33. 33
    https://www.youtube.com/watch?v=_3sVA-_zIrc

    View Slide

  34. Healthcare
    34

    View Slide

  35. 35
    https://www.youtube.com/watch?v=B5n8Uavhl00

    View Slide

  36. Biology
    36

    View Slide

  37. 37
    https://www.youtube.com/watch?v=_9x4cmQWZ6g

    View Slide

  38. Journalism
    38

    View Slide

  39. 39
    https://www.youtube.com/watch?v=yPJhj855tvQ

    View Slide

  40. Product
    Recommendations
    40

    View Slide

  41. 41
    https://www.youtube.com/watch?v=qpbELUmbDIk

    View Slide

  42. Other
    Cool Stuff
    42

    View Slide

  43. 43
    https://www.youtube.com/watch?v=3k96HLqvhc0

    View Slide

  44. 44
    https://www.youtube.com/watch?v=S9PcPbtTcPc

    View Slide

  45. 45
    https://www.youtube.com/watch?v=UzGZtgu3PBM

    View Slide

  46. DATA SCIENCE
    SKILLS

    View Slide

  47. Getting into Data Science
    47

    View Slide

  48. Getting into Data Science
    48
    You
    🦄
    Data
    Scientist

    View Slide

  49. Getting into Data Science
    49
    You
    🦄
    Data
    Scientist
    What they tell you

    View Slide

  50. Getting into Data Science
    50
    You
    🦄
    Data
    Scientist
    How it feels like

    View Slide

  51. Getting into Data Science
    51
    “It depends”

    View Slide

  52. Getting into Data Science
    52
    Where are you?
    Where do you want to go?

    View Slide

  53. 🤝
    Computer

    Science
    Statistics
    Domain
    Expertise
    53

    View Slide

  54. Computer Science
    54

    View Slide

  55. Computer Science
    55
    • Basic coding in 1 language (e.g. Python)
    • Data Manipulation
    • Optional: out-of-the-box Machine Learning
    • Database technologies (e.g. SQL, NoSQL, etc)
    • “Behind the scenes” of Machine Learning
    • More programming languages (R, Scala, …),
    data processing tools (Spark, Elasticsearch,
    …), and other shiny toys
    Start
    Next

    View Slide

  56. Math / Stats
    56

    View Slide

  57. Math / Stats
    57
    • Basic descriptive statistics
    • Data visualisation techniques
    • Linear algebra (vector/matrix computation)
    • Calculus
    • Mathematical optimisation
    • More advanced probability / stats
    Start
    Next

    View Slide

  58. Domain Expertise
    58

    View Slide

  59. Domain Expertise
    59
    • Speak the language
    • Basic data analysis
    • Deeper domain understanding
    • Communicate with business stakeholders
    (non-technical roles)
    Start
    Next

    View Slide

  60. Soft Skills
    60

    View Slide

  61. Soft Skills
    • They should be called “Core Skills” really
    • Communication
    • Story telling
    • Problem solving
    • Learning to learn
    61

    View Slide

  62. What’s Next
    62

    View Slide

  63. What’s Next
    1. Find a topic you like
    2. Find a dataset about the topic *
    3.
    63
    🦄
    * links at the end

    View Slide

  64. SUMMARY

    View Slide

  65. Summary
    • Data Science lets you work in any domain
    • What kind of data scientist do you want to be?
    • You don’t need to be an expert in everything
    65

    View Slide

  66. Resources
    • Datasets: kaggle.com
    • Datasets: archive.ics.uci.edu
    • Datasets: “awesome data” on GitHub.com
    • Book: Doing Data Science (O’Neil and Schute)
    • Videos: youtube.com/user/PyDataTV
    66

    View Slide

  67. Thank You
    • Twitter: @MarcoBonzanini
    • Blog: marcobonzanini.com
    • Newsletter: marcobonzanini.com/newsletter
    • Questions?
    67

    View Slide