Data Science Machine Learning Course
What will I learn?
Vhurai simba redata ne Chirongwa chedu che Data Science ne Muchina Kudzidza, chakagadzirirwa vashandi ve Business Intelligence. Pindai mukugadzira maficha, muchinzwisisa nzira dzinoshanda nenguva uye dzinobva munzvimbo dzamunenge muchishanda. Simbisai hunyanzvi hwenyu nekugadzirisa data, kubata data risipo, nekushandura (encoding) zvinhu zvinogona kupatsanurwa mumapoka. Ongororai muchina kudzidza ma algorithms akaita se Decision Trees ne Gradient Boosting. Dzidzai kudzidzisa model, kuongorora, nekuisa muchishandiswa, muchizviunganidza zvakanaka mumabasa ebhizinesi. Simudzirai hunyanzvi hwenyu hwe BI ne mazano anoshanda, emhando yepamusoro.
Apoia's Unique Features
Develop skills
Enhance your development of the practical skills listed below
Iva nyanzvi mukugadzira maficha: Gadzirai maficha ane simba, anobva munzvimbo dzamunoshanda.
Isai ma model muchishandiswa zvakanaka: Unganidzai mumabasa ebhizinesi zvinobudirira.
Ongororai ma model nemazvo: Shandisai nzira dze RMSE, MAE, nekuyedza muchishandisa data rakasiyana (cross-validation).
Gadzirirai data zvinobudirira: Chenesai, shandurai (encode), nekubata data risipo.
Gadzirisai ma algorithms: Rongedzai ma hyperparameters uye muenzanise mashandiro ema model.
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 will 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.