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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

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  1. Nice to meet you • Data Science consultant: Natural Language

    Processing, Machine Learning, Data Engineering • Corporate training: Python + Data Science • PyData London chairperson 2
  2. 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
  3. 5

  4. 6

  5. 10

  6. 11

  7. 12

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

 Data Processing
 Data Clean
 Data Exploratory
 Analysis Models &
 Algorithms Communicate
 Report Data
 Product Decision
 Making 15
  9. 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
  10. Math / Stats 57 • Basic descriptive statistics • Data

    visualisation techniques • Linear algebra (vector/matrix computation) • Calculus • Mathematical optimisation • More advanced probability / stats Start Next
  11. Domain Expertise 59 • Speak the language • Basic data

    analysis • Deeper domain understanding • Communicate with business stakeholders (non-technical roles) Start Next
  12. Soft Skills • They should be called “Core Skills” really

    • Communication • Story telling • Problem solving • Learning to learn 61
  13. What’s Next 1. Find a topic you like 2. Find

    a dataset about the topic * 3. 63 🦄 * links at the end
  14. 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
  15. 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