课程信息
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第 2 门课程(共 2 门)

100% 在线

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中级

Data Analysis with Python

完成时间大约为13 小时

建议:5-6 weeks of study, 3-6 hours per week...

英语(English)

字幕:英语(English)

第 2 门课程(共 2 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

Data Analysis with Python

完成时间大约为13 小时

建议:5-6 weeks of study, 3-6 hours per week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 1 小时

Introduction to Machine Learning

In this week, you will learn about applications of Machine Learning in different fields such as health care, banking, telecommunication, and so on. You’ll get a general overview of Machine Learning topics such as supervised vs unsupervised learning, and the usage of each algorithm. Also, you understand the advantage of using Python libraries for implementing Machine Learning models.

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4 个视频 (总计 24 分钟), 1 个测验
4 个视频
Welcome3分钟
Introduction to Machine Learning8分钟
Python for Machine Learning6分钟
Supervised vs Unsupervised5分钟
1 个练习
Intro to Machine Learning10分钟
2
完成时间为 5 小时

Regression

In this week, you will get a brief intro to regression. You learn about Linear, Non-linear, Simple and Multiple regression, and their applications. You apply all these methods on two different datasets, in the lab part. Also, you learn how to evaluate your regression model, and calculate its accuracy.

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6 个视频 (总计 50 分钟), 5 个测验
6 个视频
Simple Linear Regression12分钟
Model Evaluation in Regression Models8分钟
Evaluation Metrics in Regression Models3分钟
Multiple Linear Regression13分钟
Non-Linear Regression7分钟
1 个练习
Regression10分钟
3
完成时间为 5 小时

Classification

In this week, you will learn about classification technique. You practice with different classification algorithms, such as KNN, Decision Trees, Logistic Regression and SVM. Also, you learn about pros and cons of each method, and different classification accuracy metrics.

...
9 个视频 (总计 81 分钟), 5 个测验
9 个视频
K-Nearest Neighbours9分钟
Evaluation Metrics in Classification7分钟
Introduction to Decision Trees4分钟
Building Decision Trees10分钟
Intro to Logistic Regression7分钟
Logistic regression vs Linear regression15分钟
Logistic Regression Training13分钟
Support Vector Machine8分钟
1 个练习
Classification10分钟
4
完成时间为 4 小时

Clustering

In this section, you will learn about different clustering approaches. You learn how to use clustering for customer segmentation, grouping same vehicles, and also clustering of weather stations. You understand 3 main types of clustering, including Partitioned-based Clustering, Hierarchical Clustering, and Density-based Clustering.

...
6 个视频 (总计 41 分钟), 1 个阅读材料, 4 个测验
6 个视频
Intro to k-Means9分钟
More on k-Means3分钟
Intro to Hierarchical Clustering6分钟
More on Hierarchical Clustering5分钟
DBSCAN6分钟
1 个阅读材料
IBM Digital Badge2分钟
1 个练习
Clustering10分钟
4.7
221 个审阅Chevron Right

50%

完成这些课程后已开始新的职业生涯

50%

通过此课程获得实实在在的工作福利

17%

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来自Machine Learning with Python的热门评论

创建者 RCFeb 7th 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.

创建者 JJDec 6th 2018

I am happy to have this online education, I drop out my nuclear engineering degree, I am happy to learn practical things with future... I work for IBM also...but I want to become a data scientis

讲师

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SAEED AGHABOZORGI

Ph.D., Sr. Data Scientist
IBM Developer Skills Network

关于 IBM

IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame....

关于 IBM 数据科学专业证书 专项课程

Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning. This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets. It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics. Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....
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