Data for UniHack
- Academic Experts
- Business Experts
You might use these interesting datasets in your hacks. If you need more details, come to the workshop room at the 2gthr platform at 8pm on Friday. If you have problems using the deepnote notebooks, catch Jakub Zitny on the slack.
Raw datasets are available here: https://drive.google.com/drive/folders/1z67rYNAinUJM76H89Gs3ukwPr5Hoh-lI?usp=sharing
Please do not share data outside, we are authorised to use the datasets just within the scope of this ideathon!
Duplicate this notebook along with all the data:
- Get you invitation to UNIHACK-DATASETS Deepnote team (ask Jakub Zitny via Slack)
- Click on
Datasetdropdown in top left menu and select
UNIHACK-DATASETS (Private)-> this way only you'll see the project, but you'll be able to access team integrations.
Dataset provides information about student final theses, such as Bachelor or Master thesis.
FIX. Wrong csv format -> now it's pickle
The data that we provide are based on original data of FIT,CTU, with some anonymization. We change student name, suffle their results, change the marks and select approx. some amout of them.
SUBJECTS AT FIT, CTU
The subject of the curriculum is a basic unit of instruction through which the student acquires the comprehensive part of the body of knowledge and skills needed to master the field of study. Subject matter content is the responsibility of the object guarantor. The subject's time-consuming is roughly expressed by the subject's attribute the extent of contact instruction. For example, a range = 2+2 indicates that the subject will have two hours of lectures per week and two hours of exercise per week. At the end of the semester, the teacher must make an assessment of how much each student has acquired the knowledge and skills he or she should have acquired during the course. How this assessment is made by teachers determines the attribute's method of completion. For a subject, it can be defined that the subject is completed only by the credit (Z), classified by the credit (KZ), only by the test (ZK), or by the credit and exam (Z,ZK). The challenge of successfully completing the subject is expressed by ECTS credit points. The course is taught during the semester. The subject is taught repeatedly in the winter(Z) or summer(L) semester of each academic year. Exceptionally, the subject may be offered to students in both semesters (Z,L). The organisational provision of the teaching is the responsibility of the assigned department, which in particular creates the subject timetable and provides the teaching for the subject. Some lecture and rehearse, others conduct exercises and grant credits.
COOPERATION WITH INDUSTRY PORTAL (FIT)
- coop_with_industry_portal_assign_cs - Datasets of the assignments, that assign by experts (mostly industry experts) in SSP (Cooperation with industry portal), unfortunately the data is mostly in CZ language
- external_fit_experts - list of the external experts, that participate with FIT
The datasets "Skill-XXXX" contains mainly IT skills from severall sources. The dataset "all_linked_skills_50K.txt" contains all linkedin skills at 2019
- skill - name of the skill
EXPERTS.AI (powered by Unico.ai)
Unico.ai provide the part of the internal experts database, that they use at Experts.ai platform. You can choose between dataset of 20K enteries or 2M enteris
Dataset of the academia experts from https://arxiv.org/ in 2019
Number of the experts in http://www.mendeley.com/ database, the folder containt name of the experts with json profile