Learn how to define data science. This video covers requirements for math, coding, and subject matter expertise.
- Let's talk about the definition of data science. … Somehow it's already 2019 and people are still debating … the actual definition of data science … which honestly that astonishes me … because it was very well defined by Drew Conway … back in 2010. … He gave a great explanation of what actually data science is … and there isn't really much deliberation that's needed … about these points in my opinion anyway. … For the definition of data science, … I'm going to revert back to Drew Conway's definition … from 2010. … This is the classical definition. … It hasn't changed. … The classical definition of data science … is that it's comprised of three core elements. … One is programming, two is math and statistics knowledge … and three is subject matter expertise. … With respect to programming skills … that are required in data science, … those are Python, R, SQL and sometimes JavaScript, … more specifically D3.js. … You use Python for data preparation, analysis, … visualization and predictive modeling. …
Author
Released
10/25/2019- Why use Python for data science
- Machine learning 101
- Linear regression
- Logistic regression
- Clustering models: K-means and hierarchal models
- Dimension reduction methods
- Association rules
- Ensembles methods
- Introduction to neural networks
- Decision tree models
Skill Level Intermediate
Duration
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Introduction
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1. Introduction to Data Science
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Defining data science5m 9s
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Where does AI fit in?3m 29s
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2. Introduction to Machine Learning
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Machine learning 10110m 45s
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3. Regression Models
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Linear regression11m 18s
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Multiple linear regression8m 36s
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4. Clustering Models
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K-means method12m 31s
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Hierarchical methods13m 31s
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DBSCAN for outlier detection9m 43s
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5. Dimension Reduction Methods
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Explanatory factor analysis5m 11s
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6. Other Popular Machine Learning Methods
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Bayesian models with Naive Bayes12m 10s
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Conclusion
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Next steps1m 22s
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Video: Defining data science