Data Science in Finance Course
What will I learn?
Vhurai simba re data science mu mari ne course yedu yakadzama yakagadzirirwa vanhu vanoshanda nezve technology. Nyatso dzika munyaya dzinokosha sedata collection, preprocessing, uye feature engineering yezvinhu zvinoitika nekufamba kwenguva (time series). Batsiridzai hunyanzvi hwemachine learning models, kusanganisira LSTM ne ARIMA, kuwedzera kurongeka kwekufembera zvichaitika. Wongororai kuonesa data, kuwana maitiro, nekududzira model kutyaira kufunga kwakakodzera. Wanai hunyanzvi hunobatsira kushandura data rezvemari kuti rive mazano anoshandisika, zvese kuburikidza nezvidzidzo zvipfupi, zvemhando yepamusoro.
Apoia's Unique Features
Develop skills
Enhance your development of the practical skills listed below
Batsirai data collection nekuchenesa kuti muwane nzwisiso yakarurama yezvemari.
Rovedzai nekuyera machine learning models yezvemari.
Onesai data kuti muwane mafambiro nemaitiro mumaseti edata rezvemari.
Gadzirai features dzekuongorora time series mumamiriro ezvemari.
Dudzirai zviri kufanotaurwa nemodel kuti muvandudze kufunga kwakakodzera munezvemari.
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.