Introduction to information system
Introduction to Data Science
Semester B
Bowei Chen
School of Computer Science
University of Lincoln
CMP3036M/CMP9063M Data Science
Module Information
Title Data Science
Code CMP3036M/CMP9063M
Semester 2016-2017 Semesters A & B
Assessment CMP3036M:
Assignment (50%) + Assignment (50%)
CMP9063M:
Assignment (40%) + Assignment (40%) + Report (20%)
Delivery Team in Semester B
Gerhard Neumann
Instructor
gneumann@lincoln.ac.uk
http://staff.lincoln.ac.uk/gneumann
Office Hour: Monday 10:00 – 12:00
Office: INB2216
Bowei Chen
Module Coordinator and Instructor
bchen@lincoln.ac.uk
http://staff.lincoln.ac.uk/bchen
Office Hour: Monday 14:00 – 16:00
Office: MC3220B, MHT
Deema Abdal Hafeth
Demonstrator
dabdalhafeth@lincoln.ac.uk
Jingmin Huang
Demonstrator
jhua8590@gmail.com
mailto:gneumann@lincoln.ac.uk
http://staff.lincoln.ac.uk/gneumann
mailto:bchen@lincoln.ac.uk
http://staff.lincoln.ac.uk/bchen
mailto:dabdalhafeth@lincoln.ac.uk
mailto:jhua8590@gmail.com
Topics in Semester A (1/3)
• Week 01
– Lecture: Introduction
• Week 02
– Lecture: Probability Review
– Workshop: Introduction to R and RStudio
• Week 03
– Lecture: Popular Distributions (1/2)
– Workshop: Data Structure in R
• Week 04
– Lecture: Popular Distributions (2/2)
– Workshop: Data I/O in R
Topics in Semester A (2/3)
• Week 05
– Lecture: Inference
– Workshop: R Graphics (1/2): Exploratory Graphs and Base Plotting System
• Week 06
– Lecture: Hypothesis Testing
– Workshop: R Graphics (2/2): lattice & ggplot2
• Week 07 (Direct Study)
• Week 08
– Lecture: Linear Regression
– Workshop: Handling and Processing Strings/Texts in R
• Week 09
– Lecture: Logistic Regression
– Workshop: Linear Regression in R
Topics in Semester A (3/3)
• Week 10
– Lecture: Model Selection
– Workshop: Logistic Regression in R
• Week 11
– Lecture: Evaluation
– Workshop: Model Selection in R
• Week 12
– Lecture: Naive Bayes & Decision Tree
– Workshop: Evaluating Models in R
• Week 13
– Lecture & Workshop: Q&A
Topics in Semester B (1/3)
• Week 01 (Bowei)
– Lecture: Introduction to Semester B
– Workshop: NA
• Week 02 (Bowei)
– Lecture: Data Preprocessing
– Workshop: Microsoft Azure Pass Redeem
• Week 03 (Gerhard)
– Lecture: Matrix and Linear Regression (1/2)
– Workshop: TBC
• Week 04 (Gerhard)
– Lecture: Matrix and Linear Regression (2/2)
– Workshop: TBC
Topics in Semester B (2/3)
• Week 05 (Bowei)
– Lecture: KNN & K-Means(1/2)
– Workshop: TBC
• Week 06 (Bowei)
– Lecture: KNN & K-Means(2/2)
– Workshop: TBC
• Week 07 (Gerhard)
– Lecture: Decision Tree and Random Forest (1/2)
– Workshop: TBC
• Week 08 (Gerhard)
– Lecture: Decision Tree and Random Forest (2/2)
– Workshop: TBC
• Week 09 Directed Study Week
Topics in Semester B (3/3)
• Week 10 (Bowei)
– Lecture: Simulation
– Workshop: TBC
• Week 11 (Gerhard)
– Lecture: Topic Models (1/2)
– Workshop: TBC
• Week 12 (Gerhard)
– Lecture: Topic Models (2/2)
– Workshop: TBC
• Week 13 (Bowei)
– Lecture & Workshop: Q&A
Timetable in Semester B
Lecture
Thursday 15:00 – 16:00 @ JUN0005
Workshop
Group A:
Thursday 9:00 – 11:00 @ MC3203
Group C:
Thursday 16:00 – 18:00 @ MC3203
Group B:
Friday 13:00 – 15:00 @ MC3204
Timetable in Semester B is slightly different to Semester A!
Module Github page
https://github.com/boweichen/UoLDataScience
• Detailed Course Topics (by Week)
• Reading List
Note: please check your slides, example codes, and
assessment documents on Blackboard. The
reading list on the Github page is a general guide for
your direct study. I suggest you to select the
materials according to your background and interest.
https://github.com/boweichen/UoLDataScience
Data Programming Tools in Semester B
Python 2.7 or 3.5
(I suggest you use 2.7 for this module)
Microsoft Azure Machine Learning Studio
Python Installation through Anaconda
Anaconda, a free product of Continuum
Analytics (www.continuum.io), is a virtually
complete scientific stack for Python.
http://www.continuum.io/
Python IDE
• Pydev with Eclipse • PyCharm
http://www.pydev.org/ https://www.jetbrains.com/pycharm-edu/
http://www.pydev.org/
https://www.jetbrains.com/pycharm-edu/
Microsoft Azure PASS Redeem in the Next Week’s Workshops
Thank You
bchen@lincoln.ac.uk
mailto:bchen@lincoln.ac.uk