HDP Analyst: Data Science - Hortonworks Official Curriculum
Event Information
Description
COURSE OVERVIEW
This course Provides instruction on the processes and practice of data science, including machine learning and natural language processing. Included are: tools and programming languages (Python, IPython, Mahout, Pig, NumPy, pandas, SciPy, Scikit-learn), the Natural Language Toolkit (NLTK), and Spark MLlib.
COURSE CONTENT
DAY 1: AN INTRODUCTION TO HADOOP AND DATASCIENCE
OBJECTIVES
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Using Hadoop for Data Science
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The Hadoop Distributed File System
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The MapReduce Framework
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Hadoop 2 and YARN
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Machine Learning from Data
LABS
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Setting up the Lab Environment
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Using HDFS Commands
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Demonstration: Understanding MapReduce
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Using Apache Mahout for Machine Learning
DAY 2: AN INTRODUCTION TO APACHE PIG AND PYTHON
OBJECTIVES
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Introduction to Apache Pig
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Python Programming
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Analyzing Data with Python
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Running Python on Hadoop
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Machine Learning Algorithms
LABS
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Getting Started with Apache Pig
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Using the IPython Notebook
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Demonstration: Understanding the NumPy Package
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Demonstration: The Pandas Library
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Performing Data Analysis with Python
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Interpolating Data Points
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Defining User Defined Functions in Python
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Streaming Python with Apache Pig
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Exploring Data with Apache Pig
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Demonstration: Classification with Scikit-Learn
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Computing K-Nearest Neighbor
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Generating a K-Means Clustering
DAY 3: MACHINE LEARNING ALGORITHMS
OBJECTIVES
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Machine Learning Algorithms Continued
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Natural Language Processing
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Apache SparkMLib
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Talking Data Science to Production
LABS
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Demonstration: POS Tagging Using a Decision Tree
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Using the Python Natural Language Toolkit
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Classifying Text Using Naïve Bayes
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Using Spark Transformations andActions
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Using Spark MLib
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Creating a Spam Classifier Using Spark MLib
