EEE356 - Data Analytics [R] (2025-2026 Spring)
Main Course
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Venue: D203, M2 Building
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Date&Time: 09:30-12:00 on Thursdays
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Objectives: This course aims to gain students insight and required skills related to data analytics containing R Programming, data wrangling, data visualisation, exploratory data analysis, and approaches to missing data.
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Textbook:
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Contents: Introduction to Data Analytics, Introduction to R Programming Language, Data Structures, Control Structures, Functions, Introduction to Data Visualisation, Data Transformation, Data Wrangling, Data Visualisation (ggplot2, Layers, Scales, and The Grammar), Exploratory Data Analysis, and Approaches to Missing Data.
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Course Documents
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Introduction to Data Analytics & Quarto Markdown & The Joy of Stats
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Hands-on Exercise: Case Study for Students (Deadline: 09:45 on March 18, 2025)
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Hands-on Exercise: Q2 (a, b, c, and d) (Deadline: 09:45 on March 25, 2025)
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Hands-on Exercise: Q2 (e, f, g, and h) (Deadline: 09:45 on April 8, 2025)
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Hands-on Exercise: Q3 (Deadline: 09:45 on May 13, 2025)
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Hands-on Exercise: Q2 (a, b, c, d, and e) (Deadline: 09:45 on May 20, 2025)
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Hands-on Exercise: Q3 and Q4 (Deadline: 09:45 on May 27, 2025)
Laboratory
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Venue: Computer and Networks Lab, M3 Building
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Date&Time: 15:15-17:00 on Wednesdays
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Lab Documents
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Introduction to RStudio (Reference: Prof. Trevor Hastie, Statistical Learning)
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DataCamp Classrooms: Introduction to R
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DataCamp Classrooms: Introduction to the Tidyverse
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DataCamp Classrooms: Introduction to Data Visualisation with ggplot2
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DataCamp Classrooms: Exploratory Data Analysis with R
Exams
Announcements