Data Science

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The program includes training in Statistics, Computer Programming, Data Visualization, Data Modeling, Big Data and Machine Learning. Learn how to create big impact as a Data Scientist by analyzing data that impacts key business decisions.

Class Concepts + Areas of Study:

Basic Statistics (Probability, Data Types, Common Distributions, Common Descriptive Statistics and Statistical Inference)
Databases (Foundational knowledge of database concepts, theory, and overview of various implementations and architectures)
Programming Foundations (Programming Foundations in a language heavily used in data science)
Statistical Programming (Basic scripting & data manipulation commands, intro to a vast library of functions to perform various statistical analyses)
Data Visualization (Data wrangling and manipulation to meet the rigid requirements for analysis, graphical representation of data)
Metrics and Data Processing (Creation of new metrics to directly answer business questions, theory and practice of statistical process control)
Intermediate Statistics (Hypothesis testing under multiple scenarios, identification and verification of data requirements for hypothesis testing)
Introduction to Big Data (Foundational concepts of Big Data and how to move from Big Data basis to more business-specific needs and requirements)
Machine Learning and Modeling (Determine the best methods for a given set of data, use of common software tools to utilize these methods)
Group Project (Work as a team in a scrum environment to cover tasks and progress collectively and individually to meet project goals)