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Student Placement Prediction Dataset
Education & Learning Analytics
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Free
About
This dataset aims to predict whether a student will be placed or not within a company. It provides essential information regarding students' academic performance, training, and placement status, serving as a valuable resource for developing predictive models. The core objective is to determine the 'PlacementStatus' of students, which is categorised as either 'placed' or 'not placed'.
Columns
- StudentID: A unique identifier for each student, ranging from 1 to 10000.
- CGPA: Represents the student's overall grades, with values typically between 6.5 and 9.1.
- Internships: Indicates the number of internships a student has completed, usually 0 to 2.
- Projects: Specifies the number of academic projects undertaken by a student, ranging from 0 to 3.
- Workshops/Certifications: Denotes the count of workshops or certifications a student has acquired, typically between 0 and 3.
- AptitudeTestScore: The score obtained in aptitude tests, usually falling between 60 and 90.
- SoftSkillsRating: A rating of a student's soft skills, particularly communication, on a scale of 3 to 4.8.
- ExtraCurricularActivities: A boolean indicator (true/false) showing whether a student participates in extracurricular activities.
- PlacementTraining: A boolean indicator (true/false) denoting if a student has received placement training.
- SSC_Marks: Marks obtained in Senior Secondary examinations, typically from 55 to 90.
- HSC_Marks: Marks obtained in Higher Secondary examinations, ranging from 57 to 88.
- PlacementStatus: The target column, indicating whether the student is 'Placed' or 'NotPlaced'.
Distribution
This dataset is provided as a CSV file, named
placementdata.csv, with a size of 447.3 kB. It comprises 12 distinct columns and contains 10,000 records. A sample file will be made available on the platform separately.Usage
This dataset is ideal for building and evaluating machine learning models, particularly for student placement prediction using techniques like CatBoost. It is also suitable for data visualisation, classification tasks, and exploratory data analysis to uncover insights into factors influencing student placements.
Coverage
The dataset focuses on student academic and training profiles, including their performance in CGPA, internships, projects, and various assessment scores. While specific geographic or time-range details are not provided, the data broadly covers student demographics relevant to their placement prospects.
License
CC0: Public Domain
Who Can Use It
This dataset is highly valuable for data scientists, machine learning engineers, and researchers interested in predictive analytics within the educational sector. It is particularly well-suited for beginners looking to practice with real-world classification problems. Educational institutions and career counselling services could also utilise this data to better understand placement trends and advise students.
Dataset Name Suggestions
- Student Placement Prediction Dataset
- Academic and Placement Status Data
- CatBoost Student Placement Predictor
- Higher Education Placement Outcomes
Attributes
Original Data Source: Student Placement Prediction Dataset
QUALITY