Chapter 2 List of Curated Python & Statistical Education Resources

2.0.0.1 Python Courses

  • Python Tutorial for Beginners (Link)

  • Forbes Best Free online data science courses in 2019 (Link)

  • Data Camp (Link) (Python plus more)

  • Python Beginner Course - Breathe Code (Link)

  • Coursera - Python Genomic Data Science Specialization (Link)

  • Data Science Plus (Link)

    • Impressive review of Stats Methods (Linear regression)

  • “Data Professor” - Python search playlist (Link)

  • Google Cloud Platform (Link)

  • Coursera

    • Machine Learning with Python (Link)

    • Data Analysis with Python (Link)

    • Specializations

      • Python for Everybody Specialization - (Link)
      • Applied Data Science with Python Specialization - (Link)

  • Kaggle

    • NR - good for introductory learners

2.0.0.3 LinkedIn Learning:

  • Resources pending, currently contained mostly in ResourceSpreadsheet.MD

2.0.0.4 Others locations of information

  • OHSU - Wiki that reviews other resources - Main page, Article list

  • ICS Lab Tutors - Link

    • Python Exercises

  • “The Ultimate Data Science Prerequisite Learning List” - Link

    • List of List

2.0.0.5 Statistics Materials:

  • UTHealth - Biostatistics for the Clinician - Link

  • Youtube - Brandon Fultz - Link

  • Youtube “Stats Quest” - Josh Starmer - Link

  • BMJ Statistics - Link * Kenyon - Biology (Link)

  • Health Knowledge UK, Public Health Textbook, statistical methods section (Link)

  • StatR Analysis - Which test to choose - (Link)

  • Medium, Towards Data Science - “Everything You Need To Know about Hypothesis Testing — Part II” (Link)

  • Concordia University - “OER Statistics” (Link)

  • Open UMich Introduction to Statistics - Link)

  • OER Hopkins “Introduction to Biostatistics” - (Link)

2.0.0.6 Books

  • Clinical Data as the Basic Staple of Health Learning: Creating and Protecting a Public Good: Workshop Summary (HSLS)

  • Neural Data Science : A Primer with MATLAB® and Python (HSLS)

  • Python for Bioinformatics (HSLS)

  • Python for Everybody - trinket Open book - (Link)

    • Very easy to read

2.0.0.7 Assessments/Homework

  • NHLBI Big Data Analysis Challenge - (Link)
  • Introduction to VA Pharmacy Data Sources - (Link)

2.0.0.8 Data sets

2.0.0.9 Fun Reads/Videos

  • Bringing AI to the Underserved Billions - (Link), Ted Talk 12 minutes

  • How to keep human bias out of AI - (Link), Ted Talk 12 minutes

  • Rayid Ghani -

  • ONC Overview of HealthCare Data Analytics - (Link) 20 minutes

  • Data Science in Healthcare, PyData NYC 2018 - (Link)

  • BD2K - Exploratory Data Analysis - (Link) 60 minutes

  • University of Virginia, Exploratory Data Analysis" - (Link) 20 minutes

  • HBR

    • Articles tagged with “Data” - (Link)
    • "Use This Framework to Predict the Success of Your Big Data Project - (Link)
    • Building a data science team - (Link)

  • Python for Industry Pharmaceuticals and Healthcare - (Link) (4 minutes)

  • Python vs R vs SAS, Simplilearn - (Link) (20 minutes)

2.0.0.10 Articles

  • A Machine Learning Approach for the Detection and Characterization of Illicit Drug Dealers on Instagram: Model Evaluation Study - (Link)

    • Python for language analysis

  • A validation of machine learning-based risk scores in the prehospital setting - (Link)

  • CHIME: COVID-19 Hospital Impact Model for Epidemics - (Link)

  • Simulate Covid-19 in your area with Python — beyond SIR models (towardsdatascience.com) - (Link)

  • HBR “The Kinds of Data Scientist” - (Link)

  • “Acquiring and Using Electronic Health Record Data” (https://rethinkingclinicaltrials.org/) - (Link)

  • A machine learning approach predicts future risk to suicidal ideation from social media data - (Link)

  • “A dataset quantifying polypharmacy in the United States” - (Link)