Data Science

The program includes training in Statistics, Computer Programming, Data Visualization,
Data Modeling, Big Data and Machine Learning.

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This is not a traditional data science program

Our Data Science curriculum focuses on the fundamentals of computer science, statistics, and applied mathematics, while incorporating real-world examples. Students will learn to balance the theory and practice of applied mathematics and computer science, allowing them to analyze and handle large-scale data sets.

You will also learn how to transform information to discover relationships and insights into complex data sets for today’s business world*.

Student Platform

With such an ambitious vision for Woz U, we developed a world-class online learning platform from the ground up with technology-based instruction in mind.

HD Video Instruction
Captivating Content
Browser-based Labs
1-on-1 Mentors

Career Services

Woz U prepares students for successful, rewarding careers in the field of software engineering.

Woz U Connect – Online Employer Network
1-on-1 Career Planning
Custom Resume and Cover Letter Reviews
Job Search and Interview Assistance

Coder For Life

Woz U graduates are encouraged to return, free of charge, to refresh their knowledge in their chosen career track, learn new technologies and find new opportunities.

Our Data Science program will position you to succeed in specialized jobs involving everything from the data pipeline and storage, to statistical analysis and eliciting the story the data tells.

Download our Data Science Informational Handout.

Name of Class

Main Areas of Study

ITT 100 | Basic Statistics Probability, Data Types, Common Distributions, Common Descriptive Statistics and Statistical Inference
ITT 105 | Databases Foundational knowledge of database concepts, theory, and overview of various implementations and architectures
ITT 110 | Programming Foundations Programming Foundations in a language heavily used in data science
ITT 115 | Statistical Programming Basic scripting and data manipulation commands, introduction to a vast library of functions to perform various statistical analyses
ITT 120 | Data Visualization Data wrangling and manipulation to meet the rigid requirements for analysis, graphical representation of data
ITT 125 | Metrics and Data Processing Creation of new metrics to directly answer business questions, theory and practice of statistical process control
ITT 130 | Intermediate Statistics Hypothesis testing under multiple scenarios, identification and verification of data requirements for hypothesis testing
ITT 135 | Introduction to Big Data Foundational concepts of Big Data and how to move from Big Data basis to more business-specific needs and requirements
ITT 140 | Machine Learning and Modeling Determine the best methods for a given set of data, use of common software tools to utilize these methods
ITT 200 | Group Project Work as a team in a scrum environment to cover tasks and progress collectively and individually to meet project goals