Course Search Results

  • DANC 325: Ballet II

    3.00 Credits
    Commonwealth University of Pennsylvania

    Explores ballet dance from an artistic, intellectual and physical approach. Through exposure to floor-barre, standing barre, traveling and center-based exercises, students will gain a greater sense of alignment, anatomical principles, musicality, terminology, and self-awareness. Additionally, through studying the repertoire of professional ballet companies, students will be able to recognize the elements that define classical versus contemporary ballet dance, and the importance of both to the dance landscape. *Prior exposure to ballet dance is required. Instructor approval will be given during the first week of classes to determine appropriate placement. Students may have completed DANC 115 or have previous non-Commonwealth University studio experience in ballet technique.
    ShareDANC 325 - Ballet II

  • DANC 350: Ensemble

    0.00 - 3.00 Credits
    Commonwealth University of Pennsylvania

    Provides a mentored forum for the development of student choreography, research, design work, and/or practical dance production experiences. Choreographers submit project proposals for approval and are paired with cast members and designers as appropriate. Most projects appear in the annual dance minor concert, which offers multiple hands-on production stage crew experiences and jobs. The course focuses on developing artistry, technique, leadership skills, collaborative voices, and/or the skills/knowledge required for successful public performances of dance works.
    ShareDANC 350 - Ensemble

  • DANC 400: Repertory

    3.00 Credits
    Commonwealth University of Pennsylvania

    Experience the exciting innovative process of creating, learning and performing new faculty dance works, faculty repertoire and/or masterworks of selected guest artists and/or master artists. This course places emphasis on developing artistry, technique, and the skills required for live performance. A final public performance is held at the end of the term showcasing the works studied and/or rehearsed as appropriate. Previous exposure to dance technique training is required. This course may be repeated for credit without limit.
    ShareDANC 400 - Repertory

  • DANC 425: Special Topics

    3.00 Credits
    Commonwealth University of Pennsylvania

    Examines various special topics in dance from an artistic, intellectual, and physical approach. On a rotating basis, these topics may include Teaching Methods, Advanced Level Technique offerings, Hip Hop, Tap, Improvisation, Social Dance Forms, or other, and serve to add depth and diversity to the Dance program. Students will explore these topics through various exercises, discussions, class films, choreographic studies, guest artists, and/or texts as appropriate. Course may be repeated for credit without limit.
    ShareDANC 425 - Special Topics

  • DATS 110: Intro Data Science

    3.00 Credits
    Commonwealth University of Pennsylvania

    Introduces the concepts and techniques used in data science. Students learn to use software tools and write computer programs to explore, visualize and analyze data. The course is intended for students studying data science, business, physical science, or social science.
    ShareDATS 110 - Intro Data Science

  • DATS 210: Intro to Data Visualization

    3.00 Credits
    Commonwealth University of Pennsylvania

    Covers basic concepts of data visualization. Explores the issues and problems in designing and creating graphical representation of data. Topics include fundamentals of visualization and the practice of communicating with data. Focus is on visual encoding and presenting to communicate the data features. The course is intended for students studying data science, physical science or social science.
    ShareDATS 210 - Intro to Data Visualization

  • DATS 310: Databases for Big Data

    3.00 Credits
    Commonwealth University of Pennsylvania

    Continues the material of CS150, Principles of Database Design. Students learn advanced topics in SQL programming. The course also covers basic concepts, practices, and challenges of big data and distributed analytics computing. Topics include SQL stored procedures and functions, creating triggers and handling exceptions in SQL, Hadoop, MapReduce, related software, and enhanced approaches such as Spark and big data machine learning. The course is intended for students studying data science, computer science, applied computer science, mathematics or statistics.
    ShareDATS 310 - Databases for Big Data

  • DATS 320: Data Mining

    3.00 Credits
    Commonwealth University of Pennsylvania

    Presents the concepts and issues involved in data mining and students learn how to apply current data mining software for tree-structured data analysis to real-world problems.
    ShareDATS 320 - Data Mining

  • DATS 410: Machine Learning

    3.00 Credits
    Commonwealth University of Pennsylvania

    Introduces modern machine learning. Machine learning is an active and growing field that is the basis of modern data mining and big data techniques. The course aims at the balance of the theoretical versus practical spectrum. The course covers the concepts behind several machine learning algorithms without going deeply into the mathematics. Students will gain practical experience applying machine learning using Python and related modules. Applications include pattern recognition and artificial intelligence, making the course valuable to students interested in data science, engineering, and intelligent agent applications.
    ShareDATS 410 - Machine Learning

  • DATS 420: Advanced Data Science

    3.00 Credits
    Commonwealth University of Pennsylvania

    Presents Data Science techniques that allow data scientists to successfully complete projects to draw conclusions from big datasets. Students complete a project that starts with "data wrangling" (collecting, cleaning and organizing data). They use techniques learned in the prerequisite classes (Data Visualization, Machine Learning and Databases for Big Data or Advanced Python) to complete the project. The project culminates in a final report and presentation.
    ShareDATS 420 - Advanced Data Science