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How to land an entry level DS job

How to land an entry level DS job

Here's a talk from Amber Teng on her journey to landing an entry level DS job

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Shanelle Recheta

March 22, 2021
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Transcript

  1. 5 Tips for breaking into data science Amber Teng

  2. About Me

  3. Part 1: Learning the basics Part 2: Showcasing your skills

    Part 3: Landing a Job Part 4:Collaboration and Beyond
  4. Part 1: Learning the basics

  5. Tip #1: Learn how to Code Languages: - Python -

    SQL - *R - *HTML/CSS - *Excel
  6. Tip #1: Learn how to Code Packages: - SciKit-Learn -

    NumPy - SciPy - Pandas - Matplotlib - Seaborn - NLTK, Gensim
  7. Tip #2: Brush up on your math Probability & Statistics:

    - Random Variables - Expectation - Parametric Models - Bayes’ Theorem - Probability Distributions - Regression Models
  8. Tip #2: Brush up on your math Linear Algebra: -

    Representing problems in linear algebra - Cosine similarity - Matrix Operations - PCA and SVD
  9. Part 2: Showcasing Your Skills

  10. Tip #3: Build, Build, and Build Creating Project Portfolios &

    Sharing Your Ideas - Github - Personal Website (getforge, bootstrap) - Medium (towards data science) - Deployment (Heroku, Flask)
  11. Part 3: Landing a Job

  12. Tip #4: Be Prepared - Have an elevator pitch -

    Practice interviewing regularly - Know your resume by heart - Diligence is key - Progress is a process: Be prepared for ups and downs
  13. Part 4: Collaboration and Beyond

  14. Tip #5: Connect and Collaborate Connecting with the Data Science

    Community: - Twitter - LinkedIn - Conferences - Slack Groups - Hackathons Pass it forward: - Contribute to FTWFoundation! - Mentorship + TA Roles - Data science for social good (ethics) - Data Science para sa bayan
  15. 1. Learn to Code 2. Learn Math 3. Keep Building

    4. Be prepared 5. Pass it forward
  16. Q & A

  17. Thank you! angelamarieteng@gmail.com @ambervteng in/angelavteng

  18. Appendix: Resources and Links - Udemy Courses: - https://www.udemy.com/course/python-for-dat a-science-and-machine-learning-bootcamp/lea

    rn/lecture/5733180?start=0#overview - MIT OCW: - https://ocw.mit.edu/courses/electrical-engineeri ng-and-computer-science/6-041sc-probabilistic -systems-analysis-and-applied-probability-fall- 2013/index.htm - YouTube Channels: - https://www.youtube.com/channel/UCxX9wt5F WQUAAz4UrysqK9A - Online Forums + Websites: - https://stackexchange.com/ - https://www.kaggle.com/ - https://sqlzoo.net/ - MOOCS/Course Resources: - https://cims.nyu.edu/~cfgranda/pages/DSGA1 002_fall15/index.html - https://github.com/jakevdp/PythonDataScience Handbook/blob/master/notebooks/01.00-IPyth on-Beyond-Normal-Python.ipynb - Medium Articles: - https://towardsdatascience.com/dealing-with-m ulticlass-data-78a1a27c5dcc - https://towardsdatascience.com/15-data-scien ce-slack-communities-to-join-8fac301bd6ce - Career + Interview Prep Resources: - https://www.brown.edu/campus-life/support/car eerlab/undergraduate-0/resumes-cover-letters- and-online-profiles - https://leetcode.com/problemset/all/