University Requirements are 34 credits

College requirements: 27 Credits

Specialization requirements: 72 Credits

Track 1 Courses – Artificial Intelligence

Track 2 Courses – Big Data Analytics

Second Year ( Third Semester )

Second Year ( Fourth Semester )

Third Year ( Fifth Semester )

Third Year ( Sixth Semester )

Fourth Year ( Seventh Semester )

Fourth Year ( Eighth Semester )

Practical Training

Refers to a course in Bachelor Data Science programs in the college. Practical training as a course makes students from the college of Computing and Informatics responsible for having to spend a 280 hours of training (equivalent to minimum eight working weeks) in their fields of specialization either in private or public organization. At the completion of training, student will have to show his grasp of most relevant and state of the art technologies in their relevant specialization

Terms of Cooperative Training

• The training organization should fill in the form and stamp it.
• The training start date must be consistent with what was specified in the announcement.
• The total training hours must not be less than 280 hours.
• The training tasks written in the form must be related to Computer Science , and not less than five different tasks.
• That the training be attended at the training headquarters, not remotely, and the party is approved through the registration form
• Any training initiated by the student directly without obtaining final approval to start training from the Training Committee in the college will not be considered.
• Failure to submit any of these reports on the specified dates leads to Fail in the course.

Registration Terms:

• The student must have 86 credit hours by the end of the current semester.
• No other course can be registered during the second semester, in the case of registration of practical training.

Registration Steps

1. First, each student issues a letter addressed to the training organization in which the student will train from the icon in Student Services.
2. The student prints the letter directly from Student Services. (You must make sure that the written semester in the letter is “the Second Semester” - the letter will be updated starting from the start of registration date)
3. The student should take the letter and registration form to the training organization.
4. The training organization should fill in the form and stamp it.
5. The total training hours must not be less than 280 hours.
6. The training tasks written in the form must be related to Data Science , and not less than five different tasks.
7. The student will be contacted if the data in the form is rejected or needs to be changed.
8. The training committee reviews the files, and if acceptance is granted, the student receives an email with the initial approval. If a student didn’t receive the initial approval, this means that the approval has not been granted and the student has not been registered for practical training for this semester.
9. Approval of the registration is preliminary one, and the final approval is obtained only if the student exceeds 86 credit hours earned by the end of the current semester. If students didn’t earn 86 credit hours by the end of this semester, the registration of the training is canceled automatically.
10. The final approval will be sent to the student on his email after publishing this semesters’ results.
11. If the student registers for any other course during the semester in which he/she will enroll in the practical training course, the registration for the training is considered cancelled, and the student is not considered registered for practical training for that semester.
12. Any training initiated by the student directly without obtaining final approval to start training from the Training Committee in the college will not be considered.

Course Requirements (Summary for important points from the practical training guide)

• Attendance at the training organization that was approved by the college.
• Complete all tasks assigned by the training organization.
• Attending weekly lectures with the training supervisor from the college on the blackboard.
• Required Reports:
  • A report from the supervisor at the training organization on the student’s performance in the middle of the training period.
  • A report from the supervisor in the training organization on the student’s performance at the end of the training period.
  • A report from the student about what has been achieved, learned and the challenges he/she faced during the training period.
  • A research report from the student on the latest trends in the field of Data Science (this topic will be discussed and explained in detail in weekly lectures with the supervisor from the college).
  • Failure to submit any of these reports on the specified dates leads to Fail in the course.

Cooperative Training Documents and Forms

• Practical Training Guide Click here
• Registration form Click here
• Student training forms Click here
• Cooperative training letter (from student services - other - request for field and practical training).

Contact us

For any inquiries about cooperative training program please, contact Cooperative Training Unit cci.ds.spt@seu.edu.sa

For study plan files

Study Plan for Bachelor of Data Science Program 2023 Click here