Data Science Foundations: Data Mining Course
What will I learn?
Notlolla maatla a data ka Motheo wa Data Science: Khoso ya Go Ribolola Data, e e diretsweng bomankge ba Business Intelligence. Ithute bokgoni jo bo botlhokwa jaaka go phepafatsa data, go lemoga dipaterone, le go dira feature engineering. Inaakanye le go tlhotlhomisa data, go lemoga diphoso, le mekgwa e e mosola ya go supa data ka pono. Ithute go tlhagisa tlhaloganyo e e botlhale ka go kgaoganya bareki ka ditlhopha le tshekatsheko ya kgolagano ya dikumo. Tsholetsa tiro ya gago ka dithuto tse dikhutshwane, tsa maemo a a kwa godimo, le tse di mosola tse di diretsweng go dirisiwa ka bonako. Ikakanye jaanong go fetola bokgoni jwa gago jwa data.
Apoia's Unique Advantages
Develop skills
Enhance the development of the practical skills listed below
Itseng go phepafatsa data: Baakanya dipharologanyo le go samagana le data e e tlhokafalang ka botswerere.
Senola dipaterone: Dirisa mekgwa ya go ribolola data go lemoga dipaterone tse di nang le tlhaloganyo.
Fetola data: Dirisa feature engineering le normalization go dirisa data ka botlalo.
Supa tlhaloganyo ka pono: Tlhama dipono tse di nang le seriti le dipego tse dikhutshwane.
Tlhagisa tlhaloganyo: Tsamaisa go kgaoganya bareki ka ditlhopha le tshekatsheko e e botlhale ka botswerere.
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.