## 课程信息

75,048 次近期查看

100% 在线

You will need mathematical and statistical knowledge and skills at least at high-school level.

### 您将学到的内容有

• Define and explain the key concepts of data clustering

• Demonstrate understanding of the key constructs and features of the Python language.

• Implement in Python the principle steps of the K-means algorithm.

• Design and execute a whole data clustering workflow and interpret the outputs.

### 您将获得的技能

K-Means ClusteringMachine LearningProgramming in Python

100% 在线

You will need mathematical and statistical knowledge and skills at least at high-school level.

1

## Week 1: Foundations of Data Science: K-Means Clustering in Python

9 个视频 （总计 22 分钟）
9 个视频
Introduction to Data Science2分钟
What is Data?1分钟
Types of Data1分钟
Machine Learning3分钟
Supervised vs Unsupervised Learning2分钟
K-Means Clustering4分钟
A Real World Dataset53
4 个练习
Types of Data – Review Information15分钟
Supervised vs Unsupervised – Review Information15分钟
K-Means Clustering – Review Information30分钟
Week 1 Summative Assessment40分钟
2

## Week 2: Means and Deviations in Mathematics and Python

11 个视频 （总计 37 分钟）, 4 个阅读材料, 11 个测验
11 个视频
2.1 – Introduction to Mathematical Concepts of Data Clustering1分钟
2.2 – Mean of One Dimensional Lists2分钟
2.3 – Variance and Standard Deviation3分钟
2.4 Jupyter Notebooks6分钟
2.5 Variables4分钟
2.6 Lists4分钟
2.7 Computing the Mean3分钟
2.8 Better Lists: NumPy3分钟
2.9 Computing the Standard Deviation6分钟
Week 2 Conclusion31
4 个阅读材料
Population vs Sample, Bias10分钟
Variability, Standard Deviation and Bias10分钟
Python Style Guide10分钟
Numpy and Array Creation20分钟
10 个练习
Population vs Sample – Review Information5分钟
Mean of One Dimensional Lists – Review Information3分钟
Variance and Standard Deviation – Review Information4分钟
Jupyter Notebooks – Review Information20分钟
Variables – Review Information10分钟
Lists – Review Information10分钟
Computing the Mean – Review Information10分钟
Better Lists – Review Information10分钟
Computing the Standard Deviation – Review Information10分钟
Week 2 Summative Assessment40分钟
3

## Week 3: Moving from One to Two Dimensional Data

16 个视频 （总计 53 分钟）, 10 个阅读材料, 15 个测验
16 个视频
3.1 Multidimensional Data Points and Features2分钟
3.2 Multidimensional Mean2分钟
3.3 Dispersion: Multidimensional Variables3分钟
3.4 Distance Metrics5分钟
3.5 Normalisation1分钟
3.6 Outliers1分钟
3.7 Basic Plotting2分钟
3.7a Storing 2D Coordinates in a Single Data Structure6分钟
3.8 Multidimensional Mean4分钟
3.10 Calculating the Distance to the Mean3分钟
3.11 List Comprehension3分钟
3.12 Normalisation in Python5分钟
3.13 Outliers and Plotting Normalised Data2分钟
Week 3 Conclusion30
10 个阅读材料
Multidimensional Data Points and Features Recap10分钟
Multidimensional Mean Recap10分钟
Multidimensional Variables Recap10分钟
Distance Metrics Recap10分钟
Normalisation Recap10分钟
Note on Matplotlib10分钟
Matplotlib Scatter Plot Documentation20分钟
Matplotlib Patches Documentation10分钟
List Comprehension Documentation20分钟
3.12 Errata10分钟
15 个练习
Multidimensional Data Points and Features – Review Information3分钟
Multidimensional Mean – Review Information3分钟
Dispersion: Multidimensional Variables – Review Information5分钟
Distance Metrics – Review Information6分钟
Normalisation – Review Information3分钟
Outliers – Review Information30分钟
Basic Plotting – Review Information5分钟
Storing 2D Coordinates – Review Information30分钟
Multidimensional Mean – Review Information30分钟
Adding Graphical Overlays – Review Information30分钟
Calculating Distance – Review Information30分钟
List Comprehension – Review Information30分钟
Normalisation in Python – Review Information30分钟
Outliers – Review Information30分钟
Week 3 Summative Assessment25分钟
4

## Week 4: Introducing Pandas and Using K-Means to Analyse Data

8 个视频 （总计 37 分钟）, 6 个阅读材料, 8 个测验
8 个视频
4.1: Using the Pandas Library to Read csv Files5分钟
4.1a: Sorting and Filtering Data Using Pandas8分钟
4.1b: Labelling Points on a Graph4分钟
4.1c: Labelling all the Points on a Graph3分钟
4.2: Eyeballing the Data5分钟
4.3: Using K-Means to Interpret the Data8分钟
Week 4: Conclusion35
6 个阅读材料
Week 4 Code Resources5分钟
More Pandas Library Documentation10分钟
The Pyplot Text Function10分钟
For Loops in Python10分钟
Documentation for sklearn.cluster.KMeans10分钟
7 个练习
Using the Pandas Library to Read csv Files – Review Information5分钟
Sorting and Filtering Data Using Pandas – Review Information10分钟
Labelling Points on a Graph – Review Information5分钟
Labelling all the Points on a Graph – Review Information5分钟
Eyeballing the Data – Review Information5分钟
Using K-Means to Interpret the Data – Review Information5分钟
Week 4 Summative Assessment40分钟