程序代写代做代考 data structure python decision tree data science Introduction to information system

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