이 강좌에 대하여

최근 조회 125,513

학습자 경력 결과

42%

가 이 강좌를 수료한 후 새로운 커리어를 시작함

41%

가 이 강좌를 통해 확실한 경력상 이점을 얻음

14%

가 급여 인상 또는 승진 성취
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 6개 강좌 중 4번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 20시간 필요
영어
자막: 영어, 한국어, 중국어 (간체자)

귀하가 습득할 기술

Machine Learning ConceptsKnimeMachine LearningApache Spark

학습자 경력 결과

42%

가 이 강좌를 수료한 후 새로운 커리어를 시작함

41%

가 이 강좌를 통해 확실한 경력상 이점을 얻음

14%

가 급여 인상 또는 승진 성취
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 6개 강좌 중 4번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 20시간 필요
영어
자막: 영어, 한국어, 중국어 (간체자)

제공자:

캘리포니아 샌디에고 대학교 로고

캘리포니아 샌디에고 대학교

강의 계획 - 이 강좌에서 배울 내용

콘텐츠 평가Thumbs Up96%(5,207개의 평가)Info
1

1

완료하는 데 24분 필요

Welcome

완료하는 데 24분 필요
2개 동영상 (총 14분)
2개의 동영상
Summary of Big Data Integration and Processing10m
완료하는 데 3시간 필요

Introduction to Machine Learning with Big Data

완료하는 데 3시간 필요
7개 동영상 (총 45분), 7 개의 읽기 자료, 1 개의 테스트
7개의 동영상
Categories Of Machine Learning Techniques7m
Machine Learning Process3m
Goals and Activities in the Machine Learning Process10m
CRISP-DM5m
Scaling Up Machine Learning Algorithms5m
Tools Used in this Course5m
7개의 읽기 자료
Slides: Machine Learning Overview and Applications25m
Downloading, Installing and Using KNIME1시간
Downloading and Installing the Cloudera VM Instructions (Windows)10m
Downloading and Installing the Cloudera VM Instructions (Mac)10m
Instructions for Downloading Hands On Datasets10m
Instructions for Starting Jupyter10m
PDFs of Readings for Week 1 Hands-On10m
1개 연습문제
Machine Learning Overview20m
2

2

완료하는 데 3시간 필요

Data Exploration

완료하는 데 3시간 필요
6개 동영상 (총 39분), 5 개의 읽기 자료, 2 개의 테스트
6개의 동영상
Data Exploration4m
Data Exploration through Summary Statistics7m
Data Exploration through Plots8m
Exploring Data with KNIME Plots9m
Data Exploration in Spark5m
5개의 읽기 자료
Slides: Data Exploration Overview and Terminology10m
Description of Daily Weather Dataset10m
Exploring Data with KNIME Plots40m
Data Exploration in Spark10m
PDFs of Activities for Data Exploration Hands-On Readings10m
2개 연습문제
Data Exploration20m
Data Exploration in KNIME and Spark Quiz20m
완료하는 데 3시간 필요

Data Preparation

완료하는 데 3시간 필요
8개 동영상 (총 42분), 4 개의 읽기 자료, 2 개의 테스트
8개의 동영상
Data Quality4m
Addressing Data Quality Issues4m
Feature Selection5m
Feature Transformation5m
Dimensionality Reduction7m
Handling Missing Values in KNIME5m
Handling Missing Values in Spark5m
4개의 읽기 자료
Slides: Data Preparation for Machine Learning30m
Handling Missing Values in KNIME20m
Handling Missing Values in Spark10m
PDFs for Data Preparation Hands-On Readings10m
2개 연습문제
Data Preparation25m
Handling Missing Values in KNIME and Spark Quiz20m
3

3

완료하는 데 4시간 필요

Classification

완료하는 데 4시간 필요
8개 동영상 (총 60분), 7 개의 읽기 자료, 2 개의 테스트
8개의 동영상
Building and Applying a Classification Model5m
Classification Algorithms2m
k-Nearest Neighbors4m
Decision Trees13m
Naïve Bayes14m
Classification using Decision Tree in KNIME8m
Classification in Spark6m
7개의 읽기 자료
Slides: What is Classification?10m
Slides: Classification Algorithms10m
Classification using Decision Tree in KNIME45m
Interpreting a Decision Tree in KNIME20m
Instructions for Changing the Number of Cloudera VM CPUs10m
Classification in Spark45m
PDFs for Classification Hands-On Readings10m
2개 연습문제
Classification20m
Classification in KNIME and Spark Quiz16m
4

4

완료하는 데 3시간 필요

Evaluation of Machine Learning Models

완료하는 데 3시간 필요
7개 동영상 (총 42분), 7 개의 읽기 자료, 2 개의 테스트
7개의 동영상
Overfitting in Decision Trees3m
Using a Validation Set9m
Metrics to Evaluate Model Performance10m
Confusion Matrix7m
Evaluation of Decision Tree in KNIME3m
Evaluation of Decision Tree in Spark2m
7개의 읽기 자료
Slides: Overfitting: What is it and how would you prevent it?10m
Slides: Model evaluation metrics and methods10m
Evaluation of Decision Tree in KNIME30m
Completed KNIME Workflows10m
Evaluation of Decision Tree in Spark20m
Comparing Classification Results for KNIME and Spark10m
PDFs for Evaluation of Machine Learning Models Hands-On Readings10m
2개 연습문제
Model Evaluation20m
Model Evaluation in KNIME and Spark Quiz16m

검토

MACHINE LEARNING WITH BIG DATA의 최상위 리뷰

모든 리뷰 보기

빅 데이터 특화 과정 정보

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions. ********* Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data....
빅 데이터

자주 묻는 질문

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.