Review of Python Courses (Part 18)
Posted by Mark on January 15, 2021 at 07:15 | Last modified: February 5, 2021 10:08In Part 17, I summarized my Datacamp courses 50-52. Today I will continue with the next three.
As a reminder, I introduced you to my recent work learning Python here.
My course #53 was Introduction to Python for Finance. This course covers:
- Why Python for finance?
- Comments and variables
- Variable data types
- Lists in Python
- Lists in lists
- Methods and functions
- Arrays (probably best for financial analysis)
- Two dimensional arrays
- Using arrays for analyses (indexing arrays—might work in place of .loc or .iloc?)
- Visualization in Python
- Histograms (normed arg)
- Introducing the dataset
- Closer look at the sectors
- Visualizing trends
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My course #54 was Experimental Design in Python. This course covers:
- Intro to experimental design (import plotnine as p9)
- Our first hypothesis test—Student’s t-test (from scipy import stats)
- Testing proportion and correlation [stats.chisquare(), stats.fisher_exact(), stats.pearsonr()]
- Confounding variables
- Blocking and randomization (random sampling)
- ANOVA [import statsmodels as sm, stats.f_oneway()]
- Interactive effects (two- and three-way ANOVAs)
- Type I error (Bonferroni and Šidák correction for multiple comparisons)
- Sample size (from statsmodels.stats import power as pwr)
- Power
- Assumptions and normal distributions (Q-Q plot)
- Testing for normality [from scipy import stats, stats.shapiro()]
- Non-parametric tests: Wilcoxon rank-sum and signed-rank (paired) test
- More non-parametric tests: Spearman correlation
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My course #55 was Introduction to Data Engineering. For some reason, these data engineering courses are not my cup of tea. This course covers:
- What is data engineering?
- Tools of the data engineer (data engineers are expert users of database systems)
- Cloud providers
- Databases
- Parallel computing (from multiprocessing import Pool) and computation frameworks
- Workflow scheduling frameworks
- Extract
- Transform
- Loading
- Putting it all together
- Case study: course ratings
- From ratings to recommendations
- Scheduling daily jobs
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I will review more classes next time.
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