Predicting Student Success Using Machine Learning

Local Chapter Ankara, Turkey Chapter

Coordinated by Turkey ,

Status: Completed

Project Duration: 01 Jul 2023 - 17 Aug 2023

Open Source resources available from this project

Project background.

Student success in the education system in Turkey can be influenced by various factors. This project aims to develop a model using data science and machine learning techniques to predict student success.

Within the scope of the project, demographic information, socio-economic status, learning environments, school performance, and other relevant data of students will be used. These data will be analyzed to identify factors that affect student success and to create a machine learning model that predicts student performance.

During the development of the model, various machine learning algorithms can be utilized, such as linear regression, decision trees, support vector machines, or artificial neural networks. Additionally, based on data-driven insights, recommendations and strategies can be provided to improve student success.

Project plan.

  • Week 1

    Dataset Scoping

  • Week 2

    Dataset Scoping

  • Week 3

    Dataset Preprocessing

  • Week 4

    Dataset Preprocessing

  • Week 5

    Model Selection

  • Week 6

    Model Selection

  • Week 7

    Model Training & Evaluation

  • Week 8

    Model Training & Evaluation

Learning outcomes.

Machine Learning, Data Visualization, Data Analysis, EDA

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