Assessment

Evaluation activities and instruments:

a) Process and scheduled evaluation activities

The course consists of the following assessment activities:

- MD0 (20%): Theoretical exams (in English), where for each exam the student will have to answer 5 questions individually and in writing (to develop in a maximum level) about concepts of computer learning seen in theory classes. It represents 20% of the final grade, it is individual and can be retaken (there will be two partials and their respective retakes). 

- MD1 (50%): Realisation of the online Coursera course on Machine Learning: the mark obtained at this course will constitute the 50% on the final grade, is mandatory, and can not be retaken.

- MD2 (30%): Preparation of a jupyter notebook with the description in python code of a specific case of computational learning (either regression, classification, clustering or memorization, for example chosen here: https://www.kaggle.com/search?q = machine + learning), and the notebook will code the data, the models used (with the parameters that work best for the data), and the results of the chosen problem. Examples of jupyter notebooks applied to specific cases can be found here https://datauab.github.io/.Represents 20% of the final grade, is individual and can be retaken (online delivery the day of the second retake of the theoretical exam).

The following describes how to pass the course with continuous evaluation:

- MD0: Individual theory exams

The final theory grade will be calculated from two partial exams:

Theory Note = (0.6 * Partial1) + (0.4 * Partial2)

Partial1 is done in the middle of the semester and serves to eliminate part of the subject if it is approved. Partial2 is done at the end of the school semester and serves to eliminate the part of the agenda that comes after Partial1.

These exams aim at an individualized evaluation of the student with their abilities to answer 5 long questions (develop to occupy a maximum page length) about the techniques explained in class, as well as to evaluate the level of conceptualization that the student has not made of the techniques. views.

To pass the theory part of the subject by taking face-to-face exams, two requirements must be met:

• it will be necessary that the marks of the partials 1 and 2 are equal to or greater than 4.0 (in both partials). In case that less than 4.0 is achieved in one of the two Partials, the corresponding partial must be done again during the recovery exam.
• the final theory grade must be greater than or equal to 4.0. In case the final theory grade is not equal to or greater than 4.0, students can take the recovery exam to be evaluated of all the contents seen in the subject.

Recovery exam (end of January or beginning of February). In this exam, the student can recover the partial (s) that have not exceeded 4.0, or recover the syllabus in the event that the final theory grade does not exceed 4.0.

- MD1: Coursera online course on Machine Learning

The evaluation of this part will be the mark obtained at the online course https://es.coursera.org/learn/machine-learning. 

This course can not be retaken: in case of not completing the course, the mark will not add up to the final mark of the subject

- MD2: Making a jupyter notebook in python describing a specific case of machine learning

The evaluation will be based on the python code and the explanation of the code that will be found in the jupyter notebook that will be delivered nolater than the day of the second part of the course. The note of the notebook will be calculated according to the formula:

Note Notebook = (0.1 * Introduction to the database) + (0.25 * Analysis of the attributes, correlations, ...) + (0.25 * Description of the method used, howto find the best parameters, method comparison ...) + (0.3 * Described the results, confusion matrices, graphs of the models and the data, examples of false positives / negatives, ROC curves, ...) + (0.1 * Presentation of the Jupyter Notebook)

Examples of jupyter notebooks applied to specific cases can be found here https://datauab.github.io/.

- Evaluation of transversal competences

Partial exams MD0 will allow you to evaluate your acquisition of thinking habits and personal work (T01 Thinking habits, Note Theory). With the completion of the online course MD1 and the implementation of a Kaggle project MD3, the acquisition of habits will be evaluated to solve a predetermined task and data values totally different from those seenin class (T06 Personal attitude).

The final grade for the course is obtained by combining the evaluation of these activities as follows:

Final Note = (0.2 * Theory) + (0.5 * Online course) + (0.3 * Kaggle Case) 

Conditions to approve:

To pass, it is necessary that the evaluation of each of the activities exceeds the minimum required and that the total evaluation exceeds 5 points. In case of not passing the subject, the numerical note of the file will be the weighted average of the marks that exceed the minimum thresholds:

• The final grade of theory MD0 must be greater than or equal to 4.0 to contribute to the final mark.
• The grade of the MD1 and MD2 must be greater than or equal to 5.0 in order to contribute to the final mark.
• The final grade for the course must be greater than or equal to 5.0 to pass the course.

If the student attends an exam or if s/he submits a deliverable of MD1 or MD2, s/he can no longer be evaluated as "Not Evaluable" in case s/he does not take any of the other evaluations, but the final grade will be calculated from those continuous evaluations to which it has been submitted.

b)Scheduling ofevaluation activities

The dates of continuous evaluation and delivery of papers will be published in Caronte (http://caronte.uab.cat/), in the space of this subject and may be subject to programming changes for reasons of adaptation to possible problems; caronte.uab.cat will always be informed of these changes as this platform will become the usual mechanism for the exchange of information between teacher and students.

The following schedule is foreseen (week 1 correspons to the week of September 12th, 2022):

• Individual theoretical exams: weeks 8 and 17-19 of the subject.
• Submission of the mark obtained in the online course: weeks 17-19 of the subject.
• Submission of the Python notebook: weeks 17-19 of the subject.

c) Retake procedure

The student can retake the theoretical exam (MD0). 

Keep in mind that the Online Course (MD1) and the Kaggle Notebook (MD2) can not be retaken.

d) Grade review procedure of MD0

For each individual theory exam, a place, date and time of review will be indicated in which the student can review the activity with the teacher. In this context, claims may bemade about the grade for the activity, which will be evaluated by the teachers responsible for the subject. If the student does not appear in this review, this activity will not be reviewed later.

e) Ratings

Enrollment of Honor: Enrollment of Honor will be granted at the decision of the teaching staff responsible for the subject, up to five percent or fraction of the students enrolled in all teaching groups of the subject. UAB regulations indicate that MH can only be awarded to students who have obtained a final grade equal to or greater than 9.00.

Not evaluable: A student will be considered non-evaluable (NA) if he has not taken any evaluation.

f) Student perpart irregularities, copying and plagiarism

Without prejudice to other disciplinary measures deemed appropriate, they will be graded with a zero lesirregularitats committed by the student that may lead to a change in the grade of an act of assessment. Therefore, copying, plagiarism, cheating, copying, etc. in any of the evaluation activities it will involve suspending with a zero. The evaluation activities classified in this way and by this procedure will not be recoverable. If it is necessary to pass any of these evaluation activities to pass the subject, this subject will be suspended directly, with no opportunity to recover it in the same course. These irregularities include, among others:

• the total or partial copy of a practice, report, or any other evaluation activity;
• let copy;
• present a group work not done entirely by group members (applied to all members, not just those who have not worked);
• present their own material and work by a third party, whether they are translations or adaptations, and in general works with non-original and exclusive elements of the student;
• have communication devices (such as mobile phones, smart watches,pens with a camera, etc.) accessible during the course of individual theory-practical assessment(exams);
• talk to colleagues during individual theory-practical assessment tests (exams);
• copy or try to copy from otherstudents during the theoretical-practical assessment tests (exams);
• use or try to use writing related to the subject during the theoretical-practical evaluation tests (exams), when these have not been explicitly allowed.

The numerical grade of the record will be the lesser value between 3.0 and the weighted average of the grades in the event that the student has committed irregularities in an act of evaluation (and therefore it will not be possible to pass the compensation). In future editions of this subject, the student who has committed irregularities in an act of evaluation will not be validated any of the evaluation activities carried out.

In summary: copying, copying or plagiarizing (or trying to) in any of the assessment activities is equivalent to a SUSPENSE, not compensable or recoverable and without validation of parts of the subject in subsequent courses.

g) Evaluation of repeating students

From the second enrollment, the evaluation of the subject will consist of the marks corresponding to the evaluations passed the first time the student enrolled in the course, provided that the marks of practice are higher or equal to 4.0 in case of the theory, or 5.0 in case of the online course and the kaggle notebook.

In order to be eligible for this differentiated assessment, the repeating student must ask the teacher at the latest until week 8.