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第 2 門課程(共 6 門)
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完成時間大約為5 小時
英語(English)
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Data ScienceArtificial Intelligence (AI)Machine LearningBig DataSpark
可分享的證書
完成後獲得證書
100% 在線
立即開始,按照自己的計劃學習。
第 2 門課程(共 6 門)
可靈活調整截止日期
根據您的日程表重置截止日期。
中級
完成時間大約為5 小時
英語(English)
字幕:英語(English)

提供方

IBM 徽標

IBM

教學大綱 - 您將從這門課程中學到什麼

1

1

完成時間為 2 小時

Week 1: Introduction

完成時間為 2 小時
6 個視頻 (總計 44 分鐘), 6 個閱讀材料, 2 個測驗
6 個視頻
What is Big Data?11分鐘
Data storage solutions5分鐘
Parallel data processing strategies of Apache Spark7分鐘
Functional programming basics6分鐘
Resilient Distributed Dataset and DataFrames - ApacheSparkSQL6分鐘
6 個閱讀材料
Course Syllabus10分鐘
Setup of the grading and exercise environment10分鐘
Exercise 1 - working with RDD10分鐘
Exercise 2 - functional programming basics with RDDs10分鐘
Exercise 3 - working with DataFrames10分鐘
Programming Lanuage Options for Apache Spark (optional)10分鐘
2 個練習
Practice Quiz (Ungraded) - Apache Spark concepts8分鐘
Apache Spark and parallel data processing
2

2

完成時間為 1 小時

Week 2: Scaling Math for Statistics on Apache Spark

完成時間為 1 小時
8 個視頻 (總計 52 分鐘), 3 個閱讀材料, 4 個測驗
8 個視頻
Averages5分鐘
Standard deviation3分鐘
Skewness3分鐘
Kurtosis2分鐘
Covariance, Covariance matrices, correlation13分鐘
Plotting with ApacheSpark and python's matplotlib12分鐘
Dimensionality reduction4分鐘
PCA5分鐘
3 個閱讀材料
Exercise 1 - statistics and transfomrations using DataFrames10分鐘
Exercise on Plotting10分鐘
Exercise on PCA10分鐘
4 個練習
Practice Quiz (Ungraded) - Statistics and API usage on Spark4分鐘
Parallelism in Apache Spark 
Questions on Plotting
Questions on PCA
3

3

完成時間為 1 小時

Week 3: Introduction to Apache SparkML

完成時間為 1 小時
5 個視頻 (總計 34 分鐘), 2 個閱讀材料, 3 個測驗
5 個視頻
Introduction to SparkML20分鐘
Extract - Transform - Load3分鐘
Introduction to Clustering: k-Means3分鐘
Using K-Means in Apache SparkML2分鐘
2 個閱讀材料
Exercise 1: Modifying a Apache SparkML Feature Engineering Pipeline10分鐘
Exercise 2 - Working with Clustering and Apache SparkML10分鐘
3 個練習
Practice Quiz (Ungraded) - ML Pipelines4分鐘
SparkML concepts 
Practice Quiz (Ungraded) - SparkML Algorithms
4

4

完成時間為 1 小時

Week 4: Supervised and Unsupervised learning with SparkML

完成時間為 1 小時
4 個視頻 (總計 18 分鐘), 2 個閱讀材料, 2 個測驗
4 個視頻
LinearRegression with Apache SparkML6分鐘
Logistic Regression1分鐘
LogisticRegression with Apache SparkML4分鐘
2 個閱讀材料
Exercise 1 - Improving Classification performance10分鐘
Course Project10分鐘
2 個練習
Practice Quiz (Ungraded) - SparkML Algorithms (2)4分鐘
Course Project Quiz

審閱

來自SCALABLE MACHINE LEARNING ON BIG DATA USING APACHE SPARK的熱門評論

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關於 IBM AI Engineering 專業證書

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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