Introduction to Data Analysis and Visualization (ZD-2401)

Bachelor of Digital Science, Universiti Brunei Darussalam, Digital Science, 2022

Students will learn the latest technologies including Tableau in the field of data analytics.

Data pre-processing: data cleaning, handling missing data, graphical methods for identifying outliers, measures of centre and spread
Exploratory data analysis: exploring categorical and numeric variables, exploring multivariate relationships
Data analytics tool: basic commands, graphics, indexing data, loading data, graphical and numerical summaries
Statistical learning: regression versus classification problems, bias-variance trade-off; simple linear regression, multiple linear regression, logistic regression, leave-one-out cross-validation, k-fold cross-validation
Data Visualization: Connecting to data, Dimension and Measure, Filtering and Sorting, Aggregation, Calculated Fields, Symbol Map, Trend Lines, Forecasting, Dashboard and Story
Case study using visualization tool: apply knowledge on real dataset and create a dashboard to present a story

Lectures

Lesson 1	Connecting to Data Visualization - Introduction
Lesson 2	Filtering and Sorting Aggregation
Lesson 3	Calculated Fields Symbol Map Trend Lines Forecasting Dashboard and Story Project Discussion

Lesson 4	Descriptive Statistics Mean Median Mode Skewed Distribution Range, Quartiles and Interquartile Range Variance and Standard Deviation
Lesson 5	Introduction to R
Lesson 6	Introduction to R cont.. loading data Statistical Learning
Lesson 7	Statistical Learning cont supervised learning
Lesson 8	Simple Linear Regression Multiple Linear Regression
Lesson 9	Multiple Linear Regression cont Deciding on Important Variables
Lesson 10	Linear Regression Lab
Lesson 11	Other Considerations in Regression Model
Lesson 12	Linear Regression Lab Contd Interaction Terms ggplot2
Lesson 13	R Commands Classification
Lesson 14	Logistic Regression Logistic Regression Lab
Lesson 15	Logistic Regression Lab contd Resampling
Lesson 16	Resampling lab dplyr
Lesson 17	dplyr contd additional aesthetics
Lesson 18	dplyr contd line graph
Lesson 19	Plotly
Lesson 20	Plotly cont customizing graphics
Lesson 21	Plotly cont background
Lesson 22	Shiny
Lesson 23	Visualization Best Practices
Lesson 24	Visualization Best Practices Contd Geospatial

Coursework: 100%
- Two Lab Tests (30%)
- Two Class Tests (30%)
- Two Class Quizzes (20%)
- One Project (20%)