Computer Science Data Science Course
What will I learn?
Tsholetsa tiro ya gago ya Botsipa jwa Kgwebo ka Khomputara Saense ya Data Saense Khoso ya rona. Ithute botsipa jwa go supa data ka difisuale, go akaretsa go tlhama dichate tse di mosola le go dirisa dikerafo ka botlale. Nna le bokgoni mo didirisweng tsa go sekaseka data jaaka Excel, Python, le R. Ithute go kwala dipego le dipresenteshene tse di gogelang bakeng sa ba ba sa itseng tsa thekenoloji. Ithute ka botlalo go sekaseka data go bona dipaterone le go leka go rarabolola mathata. Oketsa bokgoni jwa gago mo thekisong le tshekatsheko ya lotseno, mme o tlhabolole temogo ya togamaano ya papatso ka go kgaoganya bareki le go rotloetsa dilo tse di rileng.
Develop skills
Enhance the development of the practical skills listed below
Ithute botsipa jwa go supa data ka difisuale: Tlhama dichate le dikerafo tse di nang le mosola go bona tlhaloganyo.
Nna le bokgoni mo go sekasekeng data ka Excel: Dirisa Excel, Python, le R go sekaseka ka botlalo.
Kwala dipego tse di gogelang: Kopanya difisuale mme o kwalele bareetsi ba ba farologaneng.
Dira tshekatsheko ya patlisiso: Lemoga dipaterone, dilo tse di kwa ntle, le popego ya data.
Tlhabolola maano a papatso: Kgaoganya bareki le go tokafatsa ditogamaano tsa papatso.
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can modify the chapters and the workload.
- Choose which chapter to start with
- Add or remove chapters
- Increase or decrease the course workload
Examples of chapters you can add
You’ll be able to generate more chapters like the examples below
This is a free course, focused on personal and professional development. It is not equivalent to a technical, undergraduate, or postgraduate course, but offers practical and relevant knowledge for your professional journey.