このコースについて
50,288 最近の表示

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

初級レベル

約13時間で修了

推奨:14 hours/week...

英語

字幕:英語, ベトナム語

習得するスキル

StatisticsData ScienceInternet Of Things (IOT)Apache Spark

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

初級レベル

約13時間で修了

推奨:14 hours/week...

英語

字幕:英語, ベトナム語

シラバス - 本コースの学習内容

1
4時間で修了

Introduction to exploratory analysis

Analysis of data starts with a hypothesis and through exploration, those hypothesis are tested. Exploratory analysis in IoT considers large amounts of data, past or current, from multiple sources and summarizes its main characteristics. Data is strategically inspected, cleaned, and models are created with the purpose of gaining insight, predicting future data, and supporting decision making. This learning module introduces methods for turning raw IoT data into insight ...
2件のビデオ (合計3分), 1 reading, 3 quizzes
2件のビデオ
Overview of technology used within the course1 分
1件の学習用教材
Latest Video summary on environment setup10 分
1の練習問題
Challenges, terminology, methods and technology2 分
2
5時間で修了

Tools that support BigData solutions

Data analysis for IoT indicates that you have to build a solution for performing scalable analytics, on a large amount of data that arrives in great volumes and velocity. Such a solution needs to be supported by a number of tools. This module introduces common and popular tools, and highlights how they help data analyst produce viable end-to-end solutions. ...
8件のビデオ (合計52分), 1 reading, 4 quizzes
8件のビデオ
ApacheSpark and how it supports the data scientist7 分
Programming language options on ApacheSpark10 分
Functional programming basics6 分
Introduction of Cloudant2 分
ApacheSparkSQL6 分
Overview of how the test data has been generated (optional)8 分
IBM Watson Studio (formerly Data Science Experience)3 分
1件の学習用教材
Create the data on your own (optional)10 分
3の練習問題
Data storage solutions, and ApacheSpark12 分
Programming language options and functional programming12 分
ApacheSparkSQL, Cloudant, and the End to End Scenario12 分
3
4時間で修了

Scaling Math for Statistics on Apache Spark

This learning module explores mathematical foundations supporting Exploratory Data Analysis (EDA) techniques. ...
7件のビデオ (合計35分), 1 reading, 4 quizzes
7件のビデオ
Averages5 分
Standard deviation3 分
Skewness3 分
Kurtosis2 分
Covariance, Covariance matrices, correlation13 分
Multidimensional vector spaces5 分
1件の学習用教材
Exercise 210 分
3の練習問題
Averages and standard deviation10 分
Skewness and kurtosis10 分
Covariance, correlation and multidimensional Vector Spaces16 分
4
4時間で修了

Data Visualization of Big Data

This learning module details a variety of methods for plotting IoT time series sensor data using different methods in order to gain insights of hidden patterns in your data...
4件のビデオ (合計24分), 2 readings, 2 quizzes
4件のビデオ
Plotting with ApacheSpark and python's matplotlib12 分
Dimensionality reduction4 分
PCA5 分
2件の学習用教材
Exercise 3.110 分
Exercise 3.210 分
1の練習問題
Visualization and dimension reduction10 分
4.3
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人気のレビュー

by HSSep 10th 2017

A perfect course to pace off with exploration towards sensor-data analytics using Apache Spark and python libraries.\n\nKudos man.

by MTFeb 8th 2019

Good course content, however, some of the material especially the IBM cloud environment setup sometimes confusing

講師

Avatar

Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT

IBMについて

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....

Advanced Data Science with IBMの専門講座について

As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You'll understand the mathematical foundations behind all machine learning & deep learning algorithms. You can apply knowledge in practical use cases, justify architectural decisions, understand the characteristics of different algorithms, frameworks & technologies & how they impact model performance & scalability. If you choose to take this specialization and earn the Coursera specialization certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging....
Advanced Data Science with IBM

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