dsc101 | undergraduate

Introduction To Data Science

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This course surveys potential industries for data scientists. Students gain an overview of how to mine, analyze, and present large sets of data. This course also sets proper expectations for the mathematics, statistics, and computer science requirements needed to be successful in the Bachelor of Science in Data Science.

This undergraduate-level course is 5 weeks To enroll, speak with an Enrollment Representative.

Course details:

Credits: 3
Continuing education units: XX
Professional development units: XX
Duration: 5 weeks

topic title goes here

    Math in Data Science

    • Describe regression and classification methods used in predictive analysis.
    • Describe the process of using predictive analytics in a real world scenario.
    • Explain the purpose of data modeling.

    Computer Science

    • Compare NoSQL and relational databases and their uses.
    • Explain different machine learning techniques (supervised and unsupervised).

    Structured vs. Unstructured

    • Describe data structures required for data analysis.
    • Describe market basket analysis and its uses.
    • Apply a market basket analysis to a real data set.

    Big Data

    • Explain the benefits of regression modeling.
    • Define big data and identify associated challenges.
    • Describe the process of data analysis against a big data set.

    Data Mining

    • Explain the uses for text based analytics.
    • Compare data mining and data analysis.
    • Describe the process of data mining against a large data set.
    • Describe reports that can be generated for presentation from a data mining exercise.
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    Transferability of credit is at the discretion of the receiving institution. It is the student’s responsibility to confirm whether or not credits earned at University of Phoenix will be accepted by another institution of the student’s choice.