Absolute Beginner Ballet with Liezl Austria


Aug 03 2020


Eastern Time
12:30 pm - 1:45 pm




Pay-what-you-can: $10, $15, $25

Classical ballet is the mainstay and technical foundation of Alonzo King LINES Ballet Company, Training Program, BFA at Dominican University and LINES Dance Center. You will learn the very basics of ballet in a highly personalized and non-intimidating atmosphere. The basic body stance, body placement, musicality, and basic terminology will be emphasized in the course. In addition, you will learn arm movements (port de bras) and strengthening exercises, specific to ballet. No prior experience necessary. Click here to sign up through Alonzo King LINES Dance Center.

Liezl Austria born in Manila, Philippines, studied ballet with her mentor, Augusta Moore, Yehuda Maor and Alba Calzada. She performed in the United States and internationally for more than 19 years. Locally, Liezl danced with Anne Bluethenthal and Dancers, American Repertory Theater Ballet, Pacific Dance Theater, BalletMindDance, Avenue Dance Project, Mark Foeringer Dance Project and Robert Henry Johnson Dance Company, In 2006, she began her study of the Vaganova Syllabus with John White in Bryn Mawr, Pennyslvania. Since 2010, Liezl has attended annual demonstrations of the Preservation of the Vaganova Method at the Vaganova Ballet Academy in St. Petersburg, Russia. Liezl subsequently began the Teacher Re-Training program at the Vaganova Ballet Academy in 2016 studying under her mentor Pedagogue Irina Badaeva, as well as Pedagogue Galina Bashlovkina and Pedagogue Ludmila Komolova. She completed the Junior and Middle level method courses at the Vaganova Ballet Academy in St. Petersburg in June 2019, studying under the Head of Education Pedagogue Maria Gribanova.

Local Time

  • Timezone: America/New_York
  • Date: Aug 03 2020
  • Time: 12:30 pm - 1:45 pm

“Local Time” is the time zone approximated based on your physical location.

Class information is gathered through community submissions. Dancing Alone Together takes no responsibility for class quality or errors in event data.