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Computer Science Artificial Intelligence Course
Bula bokgoni jwa botlhale jwa maitirelo ka Khomputara Saense Botlhale jwa Maitirelo Course ya rona, e e diretsweng bomankge ba thekenoloji ba ba tlhagafaletseng go gaisa botlhe. Ithute ka mekgwa ya go baakanya data pele, itse ditsela tsa go ithuta tsa machine learning tse di jaaka Support Vector Machines le Naive Bayes, mme o rarabolole dikgwetlho tsa go lemoga spam. Ithute go sekaseka ditsela tsa go dira dilo ka go dirisa accuracy, precision, le recall, mme o di tokafatse ka maano a a nang le mosola. Bona maitemogelo a go thapisa model, go e leka, le go phutha data ka bothakga, go netefatsa gore o na le didirisiwa tse di go thusang go itlhamela dilo tse disha mo seemong sa AI.
- Itse metrics tsa tshekatsheko: Tokafatse accuracy le performance ya model.
- Diragatsa machine learning: Dirisa algorithms go lemoga spam ka tsela e e nang le mosola.
- Tokafatsa go thapisa model: Thiba overfitting le underfitting mo ditseleng tsa AI.
- Bona data ya bothakga: Lemoga mme o dirise open-source datasets ka boikarabelo.
- Baakanya data ka bonako: Thatafatsa, tokenize, mme o fetole text data.
from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Bula bokgoni jwa botlhale jwa maitirelo ka Khomputara Saense Botlhale jwa Maitirelo Course ya rona, e e diretsweng bomankge ba thekenoloji ba ba tlhagafaletseng go gaisa botlhe. Ithute ka mekgwa ya go baakanya data pele, itse ditsela tsa go ithuta tsa machine learning tse di jaaka Support Vector Machines le Naive Bayes, mme o rarabolole dikgwetlho tsa go lemoga spam. Ithute go sekaseka ditsela tsa go dira dilo ka go dirisa accuracy, precision, le recall, mme o di tokafatse ka maano a a nang le mosola. Bona maitemogelo a go thapisa model, go e leka, le go phutha data ka bothakga, go netefatsa gore o na le didirisiwa tse di go thusang go itlhamela dilo tse disha mo seemong sa AI.
Elevify advantages
Develop skills
- Itse metrics tsa tshekatsheko: Tokafatse accuracy le performance ya model.
- Diragatsa machine learning: Dirisa algorithms go lemoga spam ka tsela e e nang le mosola.
- Tokafatsa go thapisa model: Thiba overfitting le underfitting mo ditseleng tsa AI.
- Bona data ya bothakga: Lemoga mme o dirise open-source datasets ka boikarabelo.
- Baakanya data ka bonako: Thatafatsa, tokenize, mme o fetole text data.
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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