This program focuses on the design and development of data software that is able to access, process, and organize data in a meaningful way.
The program covers various concepts and tools/technologies that are essential to data development. Those concepts include Extract Transform Load (ETL) processes, Structured and unstructured data, Scripting languages, Relational and Non-Relational databases, Python, MySQL, MongoDB, Linux and Object-Oriented Design.
The course will outline how to leverage these concepts and tools to design and develop software that is able to organize data in a fast, simple, and effective way.
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Prerequisite Skills and Knowledge
This course requires that learners have development experience in at least one of the following areas:
- Application development using an object-oriented language, such as Java or C#
- Intermediate experience using SQL to create and manage databases
DATA ANALYTICS TOPICS
Track 1: Data Engineering and Data Science Overview
- Introduction to Data Engineering and Data Science
- Introduction to Python
- Python and MySQL
- Introduction to NoSQL databases and MongoDB
- Combine Data from different sources
Track 2: Using Distributed Systems to Manage Big Data
- Distributed Systems Overview
- Automating Jobs in Hadoop
- Big Data using Amazon Web Services
- Machine Learning, Amazon Spark, and ETL Processes
- Implementing an On-Demand ETL Process
- Final Project