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.
Contents
- 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
Tableau
Lesson 1 (Jan 11, 2022) | Connecting to Data Visualization - Introduction |
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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 |
Python Programming
Lesson 4 | Python setup Introduction to Python |
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Lesson 5 | Introduction to Python (contd…Tuple) Introduction to Pandas |
Lesson 6 | Introduction to Pandas cont indexing Data Wrangling |
Lesson 7 | Data Gathering Data Assessing and Cleaning |
Lesson 8 | Descriptive Statistics |
Lesson 9 | Descriptive Statistics cont EDA Mean Median Mode Skewed Distribution Range, Quartiles and Interquartile Range |
Lesson 10 | Variance and Standard Deviation Univariate Visualisation |
Lesson 11 | Bivariate Visualization Multivariate Visualization Slide deck |
Statistics
Lesson 12 | Outliers Normal Distribution |
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Lesson 13 | Probability Distributions |
Lesson 14 | Sampling Distributions |
Lesson 15 | Sampling Distributions contd CLT |
Lesson 16 | Sampling Distributions Example |
Lesson 17 | Estimation |
Lesson 18 | Review Estimation |
Lesson 19 | Review Normal Distribution |
Lesson 20 | Test and Revision |
Lesson 21 | Hypothesis Testing |
Lesson 22 | t-Table t-Tests |
Lesson 23 | t-Tests Examples |
Lesson 24 | Chi-Square Statistic |
Lesson 25 | ANOVA |
Lesson 26 | ANOVA contd |
Lesson 27 | Simple and Multiple Regression Clustering |
Datasets
Assessment
- Examination: 30%
- Coursework: 70%
- Two Lab Tests (20%)
- Six Class Tests (30%)
- Project (20%)
Projects by Students
- Internet mobile and broadband speeds, Tableau project
- Cost of Each Netflix Plan (per month) in Asian Countries Dec 2021, Tableau project
- Traffic_Violations, Tableau Project
Recommended Books/Resources
- Tableau
- Statistics
Academic Calendar
Jan 4 - Jan 9 | Fresher’s Week |
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Jan 10 - Feb 27 | Classes |
Feb 28 - Mar 6 | Mid Semester Break |
Mar 7 - Apr 24 | Classes |
Apr 25 - May 8 | Revision Week |
May 9 - May 22 | Examination |
- Tuesday 7:50-9:40 and Saturday 2:00-4:00