AI And Machine Learning Course
What will I learn?
Simudzira basa rako re Business Intelligence ne AI ne Machine Learning Course yedu. Dzidza kugadzirira data, kusanganisira kuligadzirisa, kubata data risipo, nekubvisa zvinhu zvisina kukodzera. Pinda mukati mema algorithm anofembera zvinhu zvakadai se linear regression, miti yekutema mitongo, uye nzira dzakanyanya kunge random forests. Gadzirisa mamodels nenzira dzekuunganidza ne hyperparameter tuning. Dzidza cross-validation, kupatsanura data, uye zviyero zvekuita. Wedzera hunyanzvi hwako mukududzira mhedzisiro uye kunyora mishumo inoshanda. Joinha izvozvi kuti uwane dzidzo yakapfupika, yemhando yepamusoro yakagadzirirwa nyanzvi dzeBI.
Apoia's Unique Features
Develop skills
Enhance your development of the practical skills listed below
Gadzirisa data zvakakwana: Bata data risipo nezvinhu zvisina kukodzera nemazvo.
Shandisa ML algorithms: Shandisa linear regression nemiti yekutema mitongo zvinobudirira.
Gadzirisa mamodels: Wedzera mashandiro ne hyperparameter tuning nenzira dzekuunganidza.
Ongorora kurongeka kwemamodel: Shandisa cross-validation nezviyero zvekuita senge MAE ne RMSE.
Taura zvawakawana: Gadzira mishumo inokwezva uye ongorora mafembero emamodel nechivimbo.
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.