DATA100A: Introduction to Data Analytics (Fall 2020)

Calendar Description

This course provides a broad overview of modern methods and tools for big data analytics. Different stages of data analytics lifecycle including diagnosing, cleaning, preparing, transforming, visualizing and modelling data are considered. Numerical and graphical methods of descriptive statistics are introduced. Data analytic methods are demonstrated using tools such as Excel, Google spreadsheets, Python and the R package.

Co-requisites

CP104.

Instructor

Professor Shengda Hu
Office: LH3036 (Lazaridis Hall)
Office hours: Tuesday  11:30am-12:20pm., or by appointment via email.
E: shu@wlu.ca

Lectures

Monday and Wednesday 11:30 a.m. - 12:50 p.m.

Lab Coordinator

Sukhjit Singh Sehra
E: ssehra@wlu.ca

Textbook

Wickham, Hadley and Grolemund, Garrett. R for Data Science.which is available online at
https://r4ds.had.co.nz. An electronic version will be available on MyLS.

Calculators

You will require a cordless, non-programmable scientific calculator. Calculators may be used during the quizzes, midterm and final examination.

MyLearningSpace

Materials related to this course and the full course outline will be posted on the DATA100 MyLearningSpace website. You are responsible for checking here on a regular basis for important announcements.

Evaluation

A final mark out of 100 will be calculated as follows:

• Labs: 25%
• Quizzes 10% (alt. 0%)
• Midterm test (Monday November 2nd, 2020 11:30-12:50pm): 20%
• Project: 15% (Out on Monday, November 2nd; due Thursday, December 10th, 2020)
• Final exam (exact date, time and location to be announced): 30% (alt. 40%)

Students must earn at least 40% on the final exam to be eligible to pass the course. The final mark will be reported as a letter grade in accordance with the conversion table of the current undergraduate calendar.

This document is a summary of the course outline for DATA100 and is provided for the convenience of students.