课程信息
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第 2 门课程(共 6 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

完成时间大约为10 小时

建议:17 hours/week...

英语(English)

字幕:英语(English)

您将获得的技能

Data ScienceArtificial Intelligence (AI)Machine LearningBig DataSpark

第 2 门课程(共 6 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

完成时间大约为10 小时

建议:17 hours/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 2 小时

Week 1: Introduction

6 个视频 (总计 44 分钟), 6 个阅读材料, 2 个测验
6 个视频
What is Big Data?11分钟
Data storage solutions5分钟
Parallel data processing strategies of Apache Spark7分钟
Functional programming basics6分钟
Resilient Distributed Dataset and DataFrames - ApacheSparkSQL6分钟
6 个阅读材料
Course Syllabus10分钟
Setup of the grading and exercise environment10分钟
Exercise 1 - working with RDD10分钟
Exercise 2 - functional programming basics with RDDs10分钟
Exercise 3 - working with DataFrames10分钟
Programming Lanuage Options for Apache Spark (optional)10分钟
2 个练习
Practice Quiz (Ungraded) - Apache Spark concepts8分钟
Apache Spark and parallel data processing
2
完成时间为 1 小时

Week 2: Scaling Math for Statistics on Apache Spark

5 个视频 (总计 29 分钟), 1 个阅读材料, 2 个测验
5 个视频
Averages5分钟
Standard deviation3分钟
Skewness3分钟
Kurtosis2分钟
Covariance, Covariance matrices, correlation13分钟
1 个阅读材料
Exercise 1 - statistics and transfomrations using DataFrames10分钟
2 个练习
Practice Quiz (Ungraded) - Statistics and API usage on Spark4分钟
Parallelism in Apache Spark 
3
完成时间为 1 小时

Week 3: Introduction to Apache SparkML

5 个视频 (总计 34 分钟), 2 个阅读材料, 3 个测验
5 个视频
Introduction to SparkML20分钟
Extract - Transform - Load3分钟
Introduction to Clustering: k-Means3分钟
Using K-Means in Apache SparkML2分钟
2 个阅读材料
Exercise 1: Modifying a Apache SparkML Feature Engineering Pipeline10分钟
Exercise 2 - Working with Clustering and Apache SparkML10分钟
3 个练习
Practice Quiz (Ungraded) - ML Pipelines4分钟
SparkML concepts 
Practice Quiz (Ungraded) - SparkML Algorithms
4
完成时间为 1 小时

Week 4: Supervised and Unsupervised learning with SparkML

4 个视频 (总计 18 分钟), 2 个阅读材料, 2 个测验
4 个视频
LinearRegression with Apache SparkML6分钟
Logistic Regression1分钟
LogisticRegression with Apache SparkML4分钟
2 个阅读材料
Exercise 1 - Improving Classification performance10分钟
Course Project10分钟
2 个练习
Practice Quiz (Ungraded) - SparkML Algorithms (2)4分钟
Course Project Quiz
4.0
19 条评论Chevron Right

来自Scalable Machine Learning on Big Data using Apache Spark的热门评论

创建者 ATSep 24th 2019

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

创建者 WOSep 30th 2019

Great tutor, he loves to keep things simple and to the point. Loved the course.

讲师

Avatar

Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT

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 AI Engineering 专业证书

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

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