Introduction to Machine Learning For Data Science Course
What will I learn?
Manola maatla a data ka thuto ya rona ya "Ketapele ya Go Ithuta ka Botlalo ka Machine Learning mo Data Science," e e diretsweng ba ditsompelo ba Business Intelligence. Ithute ka botlalo dintlha tse di botlhokwa jaaka go baakanya data, go tlhama dipopego, le go thapisa model. Ithute ka botlalo ditsela tse di kwa godimo jaaka Random Forests le Gradient Boosting go bona gore thekiso e tla nna jang. Ithute go tokafatsa di-model ka go fetofetola di-hyperparameter le go di sekaseka o dirisa ditsela tse di tshwanang le MAE le RMSE. Tsholetsa bokgoni jwa gago jwa BI ka dintlha tse di mosola, tsa boleng jo bo kwa godimo tse di thusang kgwebo go atlega.
Apoia's Unique Advantages
Develop skills
Enhance the development of the practical skills listed below
Ithute go phepafatsa data: Netefatsa gore ga go na diphoso le ditlhaelo.
Tlhama dipopego tse di mosola: Dira dipopego tse di nang le mosola gore model e dire botoka.
Tokafatsa di-model: Oketsa boleng ka go fetofetola di-hyperparameter le go bapisa ditsela tse di farologaneng.
Bontsha dintlha ka mokgwa o o bonalang: Dirisa didirisiwa tsa go bontsha go senola dintlha tse di ka dirisiwang.
Sekaseka di-model: Lekanya katlego ka ditsela tse di tshwanang le MAE le RMSE.
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.