About this Course
최근 조회 440,215

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

Data Analysis with Python

완료하는 데 약 14시간 필요

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

영어

자막: 영어

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

Data Analysis with Python

완료하는 데 약 14시간 필요

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

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 1시간 필요

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.

...
4 videos (Total 24 min), 1 quiz
4개의 동영상
Introduction to Machine Learning8m
Python for Machine Learning6m
Supervised vs Unsupervised5m
1개 연습문제
Intro to Machine Learning10m
2
완료하는 데 5시간 필요

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.

...
6 videos (Total 50 min), 5 quizzes
6개의 동영상
Simple Linear Regression12m
Model Evaluation in Regression Models8m
Evaluation Metrics in Regression Models3m
Multiple Linear Regression13m
Non-Linear Regression7m
1개 연습문제
Regression10m
3
완료하는 데 5시간 필요

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 videos (Total 81 min), 5 quizzes
9개의 동영상
K-Nearest Neighbours9m
Evaluation Metrics in Classification7m
Introduction to Decision Trees4m
Building Decision Trees10m
Intro to Logistic Regression7m
Logistic regression vs Linear regression15m
Logistic Regression Training13m
Support Vector Machine8m
1개 연습문제
Classification10m
4
완료하는 데 4시간 필요

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 videos (Total 41 min), 1 reading, 4 quizzes
6개의 동영상
Intro to k-Means9m
More on k-Means3m
Intro to Hierarchical Clustering6m
More on Hierarchical Clustering5m
DBSCAN6m
1개의 읽기 자료
IBM Digital Badge2m
1개 연습문제
Clustering10m
4.7
290개의 리뷰Chevron Right

41%

이 강좌를 수료한 후 새로운 경력 시작하기

46%

이 강좌를 통해 확실한 경력상 이점 얻기

22%

급여 인상 또는 승진하기

Machine Learning with Python의 최상위 리뷰

대학: 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.

대학: AJJul 9th 2019

This was a very informative course. The videos provided a good background on the concepts and I found the labs especially helpful for learning to implement Python code for each technique covered.

강사

Avatar

SAEED AGHABOZORGI

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

IBM 정보

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....

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 수료 과정의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며, 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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