ML Engineer Course
What will I learn?
Simudzira hunyanzvi hwako hwe Business Intelligence ne Injiniya we ML Kirasi yedu, yakagadzirirwa nyanzvi dzinoda kugona machine learning mumamiriro ezvinhu ebhizinesi. Tsvaga data rekutengesa re retail, ongorora marudzi edata, uye shandisa advanced exploratory techniques. Dzidza kufembera kwenguva refu uchishandisa ARIMA, SARIMA, uye LSTM models. Simudzira hunyanzvi hwako hwe data preprocessing, kudzidzisa model, uye kuongorora. Pakupedzisira, wana hunyanzvi mukutumira model uye kuripota, uchiita kuti nzwisiso yako itungamirire sarudzo dzebhizinesi dzine simba. Joinha izvozvi kuti ushandure hunyanzvi hwako hweBI.
Apoia's Unique Features
Develop skills
Enhance your development of the practical skills listed below
Gona kuongorora data: Ongorora uye ududzire data re retail rekutengesa rakaoma.
Vaka forecasting models: Shandisa ARIMA, SARIMA, uye LSTM kuti ufanotaure.
Simudzira kuona data: Gadzira machati ane nzwisiso kuti uone maitiro.
Optimize data preprocessing: Chenesa, shandura, uye gadzira maficha zvinobudirira.
Tumira models zvinobudirira: Ronga uye uite kutumirwa kwemhando kusina musono.
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.