$30 off During Our Annual Pro Sale. View Details »

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

Shanelle Recheta

March 22, 2021
Tweet

More Decks by Shanelle Recheta

Other Decks in Technology

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/