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FOUNDATIONS OF DATA SCIENCE - Coggle Diagram
FOUNDATIONS OF DATA SCIENCE
UNIT I – INTRODUCTION
Data Science:
Benefits and uses
Facets of data (types, sources, etc.)
Data Science Process:
Overview of steps
Defining research goals
Retrieving data
Data preparation
Exploratory data analysis (EDA)
Model building
Presenting findings & building applications
Data Mining: Finding patterns from large datasets
Data Warehousing: Central repositories of integrated data
Basic Statistical Descriptions: Mean, median, mode, range, etc.
UNIT II – DESCRIBING DATA
Types of data (qualitative, quantitative)
Types of variables (nominal, ordinal, interval, ratio)
Descriptive statistics:
Tables and graphs
Measures of central tendency (averages)
Measures of variability (range, IQR, standard deviation)
Normal Distributions
Standard (z) Scores
UNIT III – DESCRIBING RELATIONSHIPS
Correlation
Scatter plots
Correlation coefficient (r) for quantitative data
Computational formula for r
Regression:
Simple linear regression and regression line
Least squares method
Standard error of estimate
Interpretation of R
Multiple regression equations
Regression toward the mean
UNIT IV – PYTHON LIBRARIES FOR DATA WRANGLING
NumPy:
Array basics, aggregation, computation
Comparisons, masks, boolean logic
Fancy indexing, structured arrays
Pandas:
Data indexing and selection
Operating on data
Handling missing data
Hierarchical indexing
Combining datasets
Aggregation, grouping, pivot tables
UNIT V DATA VISUALIZATION
Line Plots
Plot 2D data
Scatter Plots
Visualization with Seaborn
Geographic Data with Basemap
Three Dimensional Plotting
Histograms
Subplots
Text and Annotation
Legends, Colors