Introduction to Data Analytics (ZD-1201)

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

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

Data Pre-processing: Data Cleaning, Handling Missing Data, Graphical Methods for Identifying Outliers, Measures of Centre and Spread, Data Transformation
Exploratory Data Analysis: Exploring Categorical and Numeric Variables, Exploring Multivariate Relationships, Deriving New Variables: Flag and Numeric Variables, Using EDA to Investigate Correlated Predictor Variables
Univariate and Multivariate Statistical Analysis: Descriptive Statistics Measures, Statistical Approaches to Estimation and Prediction, Statistical Inference, Confidence Interval Estimation of the Mean and Proportion, Hypothesis Testing for the Mean and Proportion, Statistical tests (t-Test, Chi-Square, ANOVA), Simple and Multivariate Regression
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
Introduction to Programming environment for data analytics: Data Wrangling: Data Gathering, Data Cleaning, Data Assessing, Clustering, Data Visualization: Univariate, Bivariate and Multivariate Exploration
Case Study: Apply knowledge to real world dataset and create slide deck

Lectures

Lesson 1 (Jan 11, 2022)	Connecting to Data Visualization - Introduction
Lesson 2 (Jan 13, 2022)	Filtering and Sorting Aggregation
Lesson 3 (Jan 18, 2022):	Calculated Fields Symbol Map Trend Lines Forecasting Dashboard and Story Project Discussion

Lesson 4	Python setup Introduction to Python Introduction to Pandas
Lesson 5	Data Wrangling Data Gathering
Lesson 6	Data Assessing and Cleaning Univariate Visualisation
Lesson 7	Bivariate Visualization Multivariate Visualization Slide deck

Lesson 8	Descriptive Statistics
Lesson 9	Mean Median Mode Skewed Distribution Range, Quartiles and Interquartile Range Variance and Standard Deviation
Lesson 10	Outliers Normal Distribution
Lesson 11	Probability Distributions
Lesson 12	Sampling Distributions
Lesson 13	Sampling Distributions Example
Lesson 14	Estimation
Lesson 15	Hypothesis Testing
Lesson 16	t-Table t-Tests
Lesson 17	Chi-Square Statistic
Lesson 18	ANOVA
Lesson 19	Simple and Multiple Regression
Lesson 20	Clustering