Study methods

This course is a massive open online course (MOOC) that involves distance learning in an online learning environment.
There are no attendance requirements.
You can complete the course at your own pace.
The learning environment contains all the materials and instructions needed for completing the course.

Learning objectives

After completing this course, you will

understand how computers store and process text
know how to load text into Python for processing
know basic tasks in natural language processing and the kinds of annotations they produce
know how to evaluate the performance of natural language processing models
know how to store texts and prepare them for further analysis

Exercises and final examination

The course has seven exercises and a final examination, which must be completed in the online learning environment.

- The exercises and the final examination are assessed automatically.

- You need to get 80% of the points available for each exercise to proceed to the next exercise.

- You can take the final examination after you have completed all the exercises. To pass the examination, you must get 50% of the available points.

- The final grade for the course is determined by taking the harmonic mean of the score for exercises and the final examination.

- The point ranges and grades for the exercises: 75-90 (1), 91-105 (2), 106-120 (3), 121-135 (4), 136-150 (5)

- The point ranges and grades for the examination: 67-80 (1), 81-94 (2), 95-108 (3), 109-122 (4), 123-135 (5)

- To exemplify, if you get a grade 5 for the exercises and 4 for the examination, the final grade will be calculated as follows: 2 / (1/5 + 1/4) ≈ 4.4444 = grade 4.

Communication

You can communicate with other students taking the course on Gitter.

Englannin syventävien valinnaiskurssi III

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