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Data Science Machine Learning Course
Tsamaya le rona mo kose ya Data Science le Machine Learning, e e diretsweng go thusa ba ba dirang ka Business Intelligence. Ithute ka botlalo ka feature engineering, o itshwaraganye le mekgwa e e amanang le nako le lefelo. To kafatsa bokgoni jwa gago ka go baakanya data pele, go samagana le dilo tse di tlhaelang, le go fetola data e e seng ya dipalo. Ithute ka ditsela tsa go dira machine learning jaaka Decision Trees le Gradient Boosting. Ithute go thapisa model, go e sekaseka, le go e tsenya tirisong, o e kopanye le ditiro tsa kgwebo. Oketsa bokgoni jwa gago jwa BI ka dintlha tse di mosola, tse di nang le boleng jo bo kwa godimo.
- Nna le bokgoni mo feature engineering: Tlhamela dilo tse di mosola, tse di itebagantseng le lefelo le o leng mo go lone.
- Tsenya di-model tirisong ka bonako: Kopanya le ditiro tsa kgwebo ka thelelo.
- Sekaseka di-model ka nepo: Dirisa mekgwa ya RMSE, MAE, le cross-validation.
- Baakanya data pele ka botswerere: Tlhatswa, fetola, mme o samagane le dilo tse di tlhaelang.
- Tokafatasa ditsela tsa go dira dilo: Baakanya di-hyperparameter le go bapisa maduo a di-model.
from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Tsamaya le rona mo kose ya Data Science le Machine Learning, e e diretsweng go thusa ba ba dirang ka Business Intelligence. Ithute ka botlalo ka feature engineering, o itshwaraganye le mekgwa e e amanang le nako le lefelo. To kafatsa bokgoni jwa gago ka go baakanya data pele, go samagana le dilo tse di tlhaelang, le go fetola data e e seng ya dipalo. Ithute ka ditsela tsa go dira machine learning jaaka Decision Trees le Gradient Boosting. Ithute go thapisa model, go e sekaseka, le go e tsenya tirisong, o e kopanye le ditiro tsa kgwebo. Oketsa bokgoni jwa gago jwa BI ka dintlha tse di mosola, tse di nang le boleng jo bo kwa godimo.
Elevify advantages
Develop skills
- Nna le bokgoni mo feature engineering: Tlhamela dilo tse di mosola, tse di itebagantseng le lefelo le o leng mo go lone.
- Tsenya di-model tirisong ka bonako: Kopanya le ditiro tsa kgwebo ka thelelo.
- Sekaseka di-model ka nepo: Dirisa mekgwa ya RMSE, MAE, le cross-validation.
- Baakanya data pele ka botswerere: Tlhatswa, fetola, mme o samagane le dilo tse di tlhaelang.
- Tokafatasa ditsela tsa go dira dilo: Baakanya di-hyperparameter le go bapisa maduo a di-model.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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