HW HDP DS - Hortonworks HDP Analyst Data Science (SCI-221)

Day 1: An Introduction to Data Science, Python, Hadoop and Machine Learning

OBJECTIVES

• Define Data Science and Explain What a Data Scientist Does
• Differentiate Between Different Types of Data Roles
• List a Number of Data Science Use Cases
• Present an Overview of Python
• Describe the Components of the Big Data Scientific Stack

LABS

• Using I Python
• Data Analysis with Python
• Using HDFS Commands
• Introduction to Spark REPLs and Zeppelin
• Using Apache Mahout for Machine Learning

Day 2: Working with Spark RDDs, Data Frames and SparkSQL, Visualization in Zeppelin

OBJECTIVES

• Explain What an RDD Is
• Explain How RDDs are Partitioned
• Create Manipulate and Restore RDDs
• Use Spark SQL to Create Tables
• Create an Application and Submit to the Cluster

LABS

• Create and Manipulate RDDs
• Create and Save Data Frames
• Build and Submit Spark Applications

Day 3: Machine Learning Algorithms, Natural Language Processing, and Spark MLlib

OBJECTIVES

• Describe Common Machine Learning Applications
• List the Pros and Cons of Various Algorithms
• Explain what Natural Language Processing is
• Explain the Feature Engineering Capabilities of Spark MLlib

LABS

• Use the Python Natural Language Toolkit (NLTK)
• Classify text using Naïve Bayes
• Compute K-nearest neighbors
• Creating a Spam Classifier with MLlib
• Sentiment Analysis with Spark MLlib