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다음 전문 분야의 6개 강좌 중 2번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 10시간 필요

권장: 18 hours/week...

영어

자막: 영어

귀하가 습득할 기술

Data ScienceArtificial Intelligence (AI)Machine LearningBig DataSpark

다음 전문 분야의 6개 강좌 중 2번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 10시간 필요

권장: 18 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 2시간 필요

Week 1: Introduction

6개 동영상 (총 44분), 6 readings, 2 quizzes
6개의 동영상
What is Big Data?11m
Data storage solutions5m
Parallel data processing strategies of Apache Spark7m
Functional programming basics6m
Resilient Distributed Dataset and DataFrames - ApacheSparkSQL6m
6개의 읽기 자료
Course Syllabus10m
Setup of the grading and exercise environment10m
Exercise 1 - working with RDD10m
Exercise 2 - functional programming basics with RDDs10m
Exercise 3 - working with DataFrames10m
Programming Lanuage Options for Apache Spark (optional)10m
2개 연습문제
Practice Quiz (Ungraded) - Apache Spark concepts8m
Apache Spark and parallel data processing
2
완료하는 데 1시간 필요

Week 2: Scaling Math for Statistics on Apache Spark

5개 동영상 (총 29분), 1 reading, 2 quizzes
5개의 동영상
Standard deviation3m
Skewness3m
Kurtosis2m
Covariance, Covariance matrices, correlation13m
1개의 읽기 자료
Exercise 1 - statistics and transfomrations using DataFrames10m
2개 연습문제
Practice Quiz (Ungraded) - Statistics and API usage on Spark4m
Parallelism in Apache Spark 
3
완료하는 데 1시간 필요

Week 3: Introduction to Apache SparkML

5개 동영상 (총 34분), 2 readings, 3 quizzes
5개의 동영상
Introduction to SparkML20m
Extract - Transform - Load3m
Introduction to Clustering: k-Means3m
Using K-Means in Apache SparkML2m
2개의 읽기 자료
Exercise 1: Modifying a Apache SparkML Feature Engineering Pipeline10m
Exercise 2 - Working with Clustering and Apache SparkML10m
3개 연습문제
Practice Quiz (Ungraded) - ML Pipelines4m
SparkML concepts 
Practice Quiz (Ungraded) - SparkML Algorithms
4
완료하는 데 1시간 필요

Week 4: Supervised and Unsupervised learning with SparkML

4개 동영상 (총 18분), 2 readings, 2 quizzes
4개의 동영상
LinearRegression with Apache SparkML6m
Logistic Regression1m
LogisticRegression with Apache SparkML4m
2개의 읽기 자료
Exercise 1 - Improving Classification performance10m
Course Project10m
2개 연습문제
Practice Quiz (Ungraded) - SparkML Algorithms (2)4m
Course Project Quiz
4.0
14개의 리뷰Chevron Right

Scalable Machine Learning on Big Data using Apache Spark의 최상위 리뷰

대학: ATSep 24th 2019

In very simple and crisp way a lot of details are covered about Apache Spark. Very good way to start.

대학: UGNov 11th 2019

For a intorductory course it is very good. Do not expect anything too advanced.

강사

Avatar

Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT

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....

IBM AI Engineering 전문 자격증 정보

The rapid pace of innovation in Artificial Intelligence (AI) is creating enormous opportunity for transforming entire industries and our very existence. After competing this comprehensive 6 course Professional Certificate, you will get a practical understanding of Machine Learning and Deep Learning. You will master fundamental concepts of Machine Learning and Deep Learning, including supervised and unsupervised learning. You will utilize popular Machine Learning and Deep Learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow applied to industry problems involving object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers. You will be able to scale Machine Learning on Big Data using Apache Spark. You will build, train, and deploy different types of Deep Architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders. By the end of this Professional Certificate, you will have completed several projects showcasing your proficiency in Machine Learning and Deep Learning, and become armed with skills for a career as an AI Engineer....
IBM AI Engineering

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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