Dr Kasım Zor

EEE356 - Data Analytics [R] (2020-2021 Spring)

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Office Hours by Reservation via e-mail

• Venue: Room 210, West Wing, Prefab Building

• Date&Time: Will be announced in response to e-mail reservation

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Main Course

• Venue: Distance Learning

• Date&Time: 09:15-12:00 on Mondays

• 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.

• 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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Lecture Slides or Notes

1. Course Introduction and Scope

2. Introduction to Data Analytics

3. Introduction to R Programming Language and Data Structures - Lab Files - Video

4. Control Structures and Functions - Lab Slides - Lab Files - Video

5. Introduction to Data Visualisation - Lab Files

6. Data Transformation - Lab Files

7. Data Wrangling (Introduction, Tibbles, Data Import, and Tidy Data) - Lab Files

8. Data Wrangling (Relational Data, Strings, Factors, and Dates&Times) - Lab Files

9. Midterm Exam

10. Data Visualisation: ggplot2 and Layers - Lab Files

11. Data Visualisation: Scales - Lab Files

12. Data Visualisation: The Grammar - Lab Files - R Markdown for Presentations

13. Exploratory Data Analysis - Lab Files

14. Approaches to Missing Data - Lab Files

15. Paper Presentations

    • Presentations shall be sent to kzor@atu.edu.tr till 17:00 on 27 May 2021.

    • Presentation duration is determined as at least 10 minutes and at most 20 minutes per student.

    • Presentations shall be prepared as beamer presentations via using R Markdown.

16. Final Exam

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Laboratory

• Venue: Distance Learning

• Date&Time: 13:15-15:00 on Mondays

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Exams

• Week 9 - Midterm Examination: 2021

• Week 16 - Final Examination

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Assignment (2020-2021 Spring) [Weight: 50% of Final Exam]

• Students are responsible for preparing a paper in a scientific manner in order to present a reputable data set related to electric load, electricity demand, or electrical energy consumption. Students should send an e-mail containing title, source, and abstract of their data set to kzor@atu.edu.tr till 17:00 on 10 May 2021 on a first-come first-serve basis.

  • 3 May 2021, 15:51, 170103031, Residential Electricity Usage

  • 3 May 2021, 16:03, 180103012, Household Energy Data

  • 3 May 2021, 16:56, 180103025, Hourly Energy Consumption

  • 4 May 2021, 01:34, 160103022, NREL RSF Building Demand

  • 4 May 2021, 09:02, 170103007, Hourly Electricity Consumption of Turkey​

  • 4 May 2021, 12:20, 170103043, Household Power Consumption

  • 4 May 2021, 17:54, 170103010, Hourly Electricity Generation of Turkey

  • 4 May 2021, 20:55, 160103018, Hourly Energy Demand, Generation, and Weather

  • 4 May 2021, 21:57, 170103035, Hourly Commercial Energy Consumption

  • 6 May 2021, 15:45, 180103045, Hourly Household Load

  • 6 May 2021, 22:38, 170103006, Hourly Electricity Consumption of 15 EU Countries

  • 10 May 2021, 02:02, 170103028, Hourly Electricity Consumption of US

  • 10 May 2021, 13:13, 170103023, Household Electricity Consumption in Romania

• Rule 1. IEEE Conference Paper Template for LaTeX will be used within any LaTeX editor.

• Rule 2. Maximum page limit is 4. Figures of the paper must be prepared by using ggplot2 package. A general introduction regarding sections of the paper are discussed in Document 1 and Document 2.

• Rule 3. After finishing the paper, a compressed folder containing LaTeX files and named as student number will be sent to dngencoglan@atu.edu.tr. In addition, a portable document file (PDF) of the paper will be uploaded to Academic Plagiarism Detector by creating a student account (Class ID: 29114215 and Enrollment Key: Assignment; Please note that during upload, students must choose single-file upload as submit option). Turnitin system will generate similarity reports for each student's submission on due date. Hence, students are recommended to prepare the paper by avoiding plagiarism. If a similarity report of a paper shows a percentage which equals to or greater than 30% (after the exclusion of bibliography), that paper will not be admitted for the evaluation.

• Deadline: 21 May 2021, Friday, 17:00.

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Announcements

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