Advanced Methods in Data Science and Big Data Analytics

Cílová skupina

Tato část není lokalizována

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.

Struktura kurzu

Tato část není lokalizována

The content of this course is designed to support the course objectives.

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 In addition t
• Lecture and demonstrations, the classroom options include handson lab exercises designed to allow practical experience for the participant. The
  on-demand course provides recordings of the lab exercises.