Training is provided by authorized distributor DNS a.s.
The main focus areas cover Hadoop (including Pig, Hive, and HBase), Natural Language Processing, Social Network Analysis, Simulation, Random Forests, Multinomial Logistic Regression, and Data Visualization.
Taking an “Open” or technology-neutral approach, this course utilizes several open-source tools to address big data challenges.
Required knowledge
Completion of the Data Science and Big Data Analytics course
Proficiency in at least one programming language such as Java or Python
Target audience
This course is intended for aspiring Data Scientists, data analysts that have completed the associate level Data Science and Big Data Analytics course, and computer scientists wanting to learn MapReduce and methods for analyzing unstructured data such as text.
Course content
Module 1: MapReduce and Hadoop
Lesson 1: The MapReduce Framework
Lesson 2: Apache Hadoop
Lesson 3: Hadoop Distributed File System
Lesson 4: YARN
Module 2: Hadoop Ecosystem and NoSQL
Lesson 1: Hadoop Ecosystem
Lesson 2: Pig
Lesson 3: Hive
Lesson 4: NoSQL - Not Only SQL
Lesson 5: HBase
Lesson 6: Spark
Module 3: Natural Language Processing
Lesson 1: Introduction to NLP
Lesson 2: Text Preprocessing
Lesson 3: TFIDF
Lesson 4: Beyond Bag of Words
Lesson 5: Language Modeling
Lesson 6: POS Tagging and HMM
Lesson 7: Sentiment Analysis and Topic Modeling
Module 4: Social Network Analysis
Lesson 1: Introduction to SNA and Graph Theory
Lesson 2: Most Important Nodes
Lesson 3: Communities and Small World
Lesson 4: Network Problems and SNA Tools
Module 5: Data Science Theory and Methods
Lesson 1: Simulation
Lesson 2: Random Forests
Lesson 3: Multinomial Logistic Regression
Module 6: Data Visualization
Lesson 1: Perception and Visualization
Lesson 2: Visualization of Multivariate Data Module
Certification
This training prepares the learner for Dell Technologies Proven Professional advanced analytics specialist-level certification exam (E20-065).
Materials
Materials are in electronic form from Dell Technologies.
Objectives
Upon successful completion of this course, participants should be able to:
Develop and execute MapReduce functionality
Gain familiarity with NoSQL databases and Hadoop Ecosystem tools for analyzing large-scale, unstructured data sets
Develop a working knowledge of Natural Language Processing, Social Network Analysis, and Data Visualization concepts
Use advanced quantitative methods and apply one of them in a Hadoop environment
Apply advanced techniques to real-world datasets in a final lab
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