2019
Machine Learning #5: Model Evaluation
Diagnostics, ROC Curves, & Validation
Machine Learning #4: Model Optimization
Feature Engineering, Regularization, & Bagging
Machine Learning #3: Classification Models
Support Vectors, K-Nearest Neighbours, Trees, & Forests
Machine Learning #2: Regression Models
Linear, Logistic, Polynomial, Lasso, & Ridge
Machine Learning #1: Basics
ML Workflow & Gradient Descent
Stats #4: Functions
Loss, Risk, & Bayes
Stats #3: Laws & Theorems
Expectation, Variance, CLT, & LOTUS
Stats #2: Distributions
Probability & Random Distribution Functions
Stats #1: Probability
Definitions & Random Variables
Tableau
Basics of the Tableau engine
Python #5: Matplotlib
Basic plots & Pandas plots
Python #4: Pandas
Series, DataFrames, Methods, & Functions
Python #3: Web Scraping
JSON, BeautifulSoup, & Selenium
Python #2: Advanced Functions
Decorators, generators, I/O, RegEx, Modules
Python #1: Basics
Types, Dictionaries, Sets, OOP
SQL #11: Operation & Optimization
System commands, Error Handling, SCD’s & Other
SQL #10: Indexing
Clustered & Non-Clustered Indexes
SQL #9: Programmable objects
Functions, Views & Stored Procedures
SQL #8: Temporary tables
CTE’s & Temp tables
SQL #7: Joining
JOIN & UNION
SQL #6: Sorting
GROUP BY, Window Functions, PIVOT
SQL #5: DML
INSERT, UPDATE, DELETE, MERGE
SQL #4: DDL
CREATE, DROP, ALTER
SQL #3: DQL
SELECT
SQL #2: SQL Design
Constructs, tables, & set up
SQL #1: Database Design
Modelling & database types