Blog

Topics

• Data science
  • How to enter data science
  • Careers
  • Statistics
  • Theory
  • External
  • Projects
• Data engineering
  • AWS essentials
• Computer science
• Python
  • Random Python
• R
  • Introduction to R
  • Random R
• Academic advice
  • Grad school life
  • Applications and writing
  • Tips for undergrads
  • Behind the scenes in research

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Data science

How to enter data science

1. The target
2. The statistics
   • Featured in Toward Data Science’s 5/13/21 editors’ picks
3. The analytics
   • Featured in Toward Data Science’s 5/27/21 editors’ picks
4. The engineering
   • Featured in Toward Data Science’s 6/3/21 editors’ picks
5. The people
   • Featured in Toward Data Science’s 3/25/21 editors’ picks

Careers

1. Transitioning to data science from academia
2. Lessons from the first two data scientists at a startup

Statistics

1. Visualizing the danger of multiple t-test comparisons
2. Linear regression via gradient descent
3. A deep dive on ARIMA models
   • Featured in Toward Data Science’s 8/19/21 editors’ picks

Theory

1. Fish schools as ensemble learning algorithms
   • Featured in Toward Data Science’s 6/17/21 editors’ picks

External

1. Data quality at Aquicore
2. How we created the morning overshoot detector

Projects

Building a full-stack spam catching app

1. Context
2. Backend
3. Frontend & Deployment

Data engineering

1. SQL vs. NoSQL databases in Python
   • Featured in Toward Data Science’s 4/15/21 editors’ picks
2. Intermediate SQL
   • Featured in Toward Data Science’s 2/3/22 editors’ picks
3. 3 levels of technical abstraction when sharing your code
4. A hands-on demo of big data with Spark

AWS essentials

1. Why cloud computing?

Computer science

1. Intro to data structures
   • Featured in Toward Data Science’s 10/28/21 editors’ picks
2. Exploring stacks and queues
   • Featured in Toward Data Science’s 12/09/21 editors’ picks

Python

Random Python

1. Perspectives on Python after R
2. Efficient type validation for Python functions

R

Introduction to R

1. Intro to R
2. Random data and plotting
3. For loops and random walks
4. Functions and if statements
5. The apply functions

Random R

1. For loops vs. apply - a race in efficiency
2. How to be fancy with comparisons
3. Visualizing my daily commute

Academic advice

Grad school life

1. 1st-year reflections
2. 2nd-year reflections
3. 3rd-year reflections
4. 4th-year reflections
5. Advice for generals/quals/prelims

Applications and writing

1. How to get into a biology Ph.D. program
2. How to get a National Science Foundation Graduate Research Fellowship (NSF-GRFP)
3. How to get a Gates Cambridge scholarship p.1 (written by Dr. Paul Bergen)
4. How to get a Gates Cambridge scholarship p.2 (written by Dr. Corina Logan)
5. How to write the self-contained universe

Tips for undergrads

1. Retrospective advice for undergrads to make the most of their four years
2. Why start grad/med/law school right away? There’s a whole world out there

Behind the scenes in research

1. Behind the scenes for Couzin et al. 2011, Science