Databases & SQL:

Why SQL is Important

• Introduction to Databases
• Understanding Query
• Table Preview
• The LIMIT Clause
• Selecting Specific Columns
• Filtering Rows Using WHERE
• Expressing Multiple Filter Criteria Using ‘AND’
• Returning One of Several Conditions With OR
• Grouping Operators
• Ordering Results

Statistics in SQL:

• Aggregate Functions
• Missing Values
• Combining Multiple Aggregation Functions
• Customizing the Results
• Counting Unique Values
• Data Types
• String Functions and Operations
• Arithmetic in SQL

Group Statistics in SQL:

• If/Then in SQL
• Dissecting CASE
• Calculating Group-Level Summary Statistics GROUP BY Visual Breakdown
• Multiple Summary Statistics by Group
• Multiple Group Columns
• Querying Virtual Columns
• Order of Execution
• Nesting functions
• Casting

Subqueries in SQL:

• Subqueries
• Subquery in SELECT
• The IN Operator
• Multiple Results in Subqueries
• Building Complex Subqueries
• Integrating A Subquery with The Outer Query

Joining Data in SQL:

• Introducing Joins
• Inner Joins
• Left Joins
• Right Joins and Outer Joins
• Combining Joins with Subqueries

Intermediate Joins in SQL:

• Combining Multiple Joins with Subqueries
• Self-joins
• Pattern Matching Using Like

Building and Organizing Complex Queries in SQL:

• The With Clause
• Creating Views
• Combining Rows with Union
• Combining Rows Using Intersect and Except
• Multiple Named Subqueries

Sampling:

• Introduction
• Populations and Samples
• Sampling Error
• Simple Random Sampling
• Importance of Sample Size
• Stratified Sampling
• Proportional Stratified Sampling
• Choosing the Right Strata
• Cluster Sampling
• Sampling in Data Science Practice
• Descriptive and Inferential Statistics

Variables in Statistics:

• Quantitative and Qualitative Variables
• Scales of Measurement
• The Nominal Scale
• The Ordinal Scale
• The Interval and Ratio Scales
• Difference Between Ratio and Interval Scales
• Common Examples of Interval Scales
• Discrete and Continuous Variables
• Real Limits

Frequency Distributions:

• Frequency Distribution Tables
• Proportions and Percentages
• Percentiles and Percentile Ranks
• Grouped Frequency Distribution Tables
• Information Loss
• Frequency Tables and Continuous Variables
• Visualizing Distributions
• Statistical Bar & Pie Charts and its customization
• Histogram and the statistics behind it
• Histograms as Modified Bar Plots
• Binning for Histograms
• Skewed Distributions
• Symmetrical Distributions
• Comparing Frequency Distributions
• Grouped Bar Plots
• Comparing Histograms
• Kernel Density Estimate Plots
• Drawbacks of Kernel Density Plots
• Strip Plots
• Box plots
• Outliers

Averages:

• The Mean as a Balance Point
• Mean Algebraically
• Estimating the Population Mean
• Estimates from Low-Sized Samples
• Variability Around the Population Mean
• The Sample Mean as an Unbiased Estimator
• The Weighted Mean
• The Median for Open-ended Distributions
• Distributions with Even Number of Values
• The Median as a Resistant Statistic
• The Median for Ordinal Scales
• Sensitivity to Changes
• The Mode for Ordinal Variables
• The Mode for Nominal Variables
• The Mode for Discrete Variables

Measures of Variability & Z-Scores:

• The Range
• Mean Absolute Deviation
• Variance
• Standard Deviation
• Average Variability Around the Mean
• Measure of Spread
• The Sample Standard Deviation
• Bessel’s Correction
• Standard Notation
• Sample Variance — Unbiased Estimator
• Z-scores
• Locating Values in Different Distributions
• Transforming Distributions
• The Standard Distribution
• Standardizing Samples
• Standardization for Comparisons
• Converting Back from Z-scores

Probabilities:

• Probability Introduction
• The Empirical Probability
• Probability as Relative Frequency
• Repeating an Experiment
• The True Probability Value
• The Theoretical Probability
• Events vs. Outcomes

Probability Rules:

• Sample Space
• Probability of Events
• Certain and Impossible Events
• The Addition Rule
• Venn Diagrams
• Exceptions to the Addition Rule
• Mutually Exclusive Events
• Set Notation

Complex Probability:

• Complex Probability Problems
• Opposite Events
• Set Complements
• Multiplication Rule
• Independent Events
• Combining Formulas
• Sampling With(out) Replacement

Permutations and Combinations:

• The Rule of Product
• Extended Rule of Product
• Permutations
• Unique Arrangements
• Combinations

Conditional Probability:

• Updating Probabilities
• Conditional Probability Formula
• Complements
• Order of Conditioning
• The Multiplication Rule
• Statistical Independence
• Statistical Dependence

Bayes Theorem:

• Independence vs. Exclusivity
• The Law of Total Probability
• Bayes’ Theorem
• Prior and Posterior Probability
• The Naive Bayes Algorithm
• Conditional Independence
• Edge Cases
• Additive Smoothing
• Multinomial Naive Bayes

Significance Testing:

• Hypothesis Testing
• Research Design
• Statistical Significance
• Test Statistic
• Permutation Test
• P Value

 Chi-Squared Tests:

• Observed and Expected Frequencies
• Statistical Significance
• Sampling Distribution Equality
• Degrees of Freedom
• Chi-squared
• Cross Tables

APIs:

• What’s an API?
• API Requests
• Types of Requests
• Status Codes
• Endpoints
• Query Parameters
• JSON Format
• Content Type
• API Authentication
• Endpoints and Objects
• Pagination
• User-Level Endpoints
• POST Requests
• PUT/PATCH Requests
• DELETE Requests

Web Scraping:

• Web Page Structure
• Retrieving Elements from a Page
• Find All
• Element IDs
• Element Classes
• CSS Selectors
• Nesting
• Selenium
• Beautiful Soup
• Requests libraries
• Playwright
• Microsoft browser automation tool
• Automate clicking