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MMBazel / Springboard-DataScienceTrack-Student Public template

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Blog Posts on Data Bootcamp

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Mikiko Bazeley edited this page Jan 11, 2019 · 1 revision

https://towardsdatascience.com/data-science-project-flow-for-startups-282a93d4508d

Toggle table of contents Pages 47

Home
01 Chapter: Course Outline
02 Chapter: What is Data Science?
04 Chapter: The Python Data Science Stack
05 Chapter: Data Wrangling
06 Chapter: Effective Networking
07 Chapter: Data Storytelling & Visualization
08 Chapter: Inferential Statistics
10 Chapter: Machine Learning
12 Chapter : Deep Learning Track
12 Chapter: NLP Track
13 Chapter: Software Engineering for Data Scientists
14 Chapter: Planning For And Getting Interviews
16 Chapter: Data Science at Scale
Appendix: Additional Career Resources
Appendix: Additional Resources to be reviewed and read
Appendix: Advanced Analytics
Appendix: Beautiful Inspiration
Appendix: Customer Propensity Scoring
Appendix: DSDJ Links
Appendix: Improving Data Science projects
Appendix: Interesting Data Sources
Appendix: Interesting Technical (Non DS Resources)
Appendix: Interview: DS General Interview
Appendix: Model Algorithm Deep Dive
Appendix: Post Vacation
Appendix: Post Springboard
Appendix: Productionalizing Models
Appendix: Resources: By Function Domain Industry
Appendix: Resources: DS Career
Appendix: Resources: Terminology & Definitions
Appendix: Scaling DS Initiatives & Teams
Blog Posts on Data Bootcamp
Bootcamp: Worth it or not?
Capstone Project 1
Capstone Project 2
Career Resources: Chapter 3, 6, 9, 11, 14, 17
Mini Project: API
Mini Project: Clustering
Mini Project: Data Wrangling API
Mini Project: EDA
Mini Project: JSON
Mini Project: Linear Regression Using the Boston Housing Prices Data
Mini Project: Logistic Regression
Mini Project: Naive Bayes
Mini Project: PySpark
Mini Project: Reduce Hospital Admissions

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