TensorFlow 2 시작하기

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  • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

  • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

• What will I get if I purchase the Certificate?

  When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

• Is financial aid available?

  Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

• Solve problems with Jupyter Notebooks

  Jupyter Notebooks are a third-party tool that some Coursera courses use for programming assignments.

  You can revert your code or get a fresh copy of your Jupyter Notebook mid-assignment. By default, Coursera persistently stores your work within each notebook.

  To keep your old work and also get a fresh copy of the initial Jupyter Notebook, click File, then Make a copy.

  We recommend keeping a naming convention such as “Assignment 1 - Initial” or “Copy” to keep your notebook environment organized. You can also download this file locally.

  Refresh your notebook

  Find missing work

  If your Jupyter Notebook files have disappeared, it means the course staff published a new version of a given notebook to fix problems or make improvements. Your work is still saved under the original name of the previous version of the notebook.

  To recover your work:

  Unsaved work

  "Kernels" are the execution engines behind the Jupyter Notebook UI. As kernels time out after 90 minutes of notebook activity, be sure to save your notebooks frequently to prevent losing any work. If the kernel times out before the save, you may lose the work in your current session.

  How to tell if your kernel has timed out:

  To restart your kernel:

More questions? Visit the Learner Help Center.