Computer Science Students Performance

By shrijeetverma13 · February 17, 2026

Data source:

I've analyzed the most popular future career choices among students and created a visualization showing the top 10 careers. The chart displays the number of students interested in each career path, ranked from most to least popular.

Students interested in AI and Machine Learning domains pursue a variety of future careers. The analysis examined 33 students who expressed interest in AI/ML fields and identified their career aspirations.

The analysis shows which academic domains attract the highest-performing students based on their GPAs. A visualization and detailed ranking have been created to show the average GPA across all interested domains.

Looking at advanced (Strong) proficiency levels across programming languages, SQL has the highest percentage with 43.9% of students demonstrating advanced skills. Python follows closely at 38.9%, and Java at 38.3%. Interestingly, no students currently have advanced proficiency in all three languages simultaneously.

The analysis reveals how career preferences vary between male and female students. A grouped bar chart was created showing the distribution of career choices by gender, making it easy to compare preferences side-by-side.

Among computer science students, female students have a slightly higher average GPA of 3.628 compared to male students who have an average GPA of 3.605. The difference is very small at just 0.023 GPA points.

The analysis identified future careers with the highest Python proficiency among interested students. A bar chart was created showing the top 10 careers ranked by average Python skill level, where scores range from 1 (Weak) to 3 (Strong). Each career shows both the average proficiency score and the number of students interested in that field.

The student population ranges from 20 to 37 years old, with an average age of 22.1 years. The most common age is 22 years. Looking at GPA performance across age groups, the 20-22 age group has the highest average GPA at 3.449, making them the top-performing age bracket in terms of academic achievement.

Yes, there is a relationship between student age and academic performance, though it's relatively weak. The analysis reveals a positive correlation of 0.203, meaning that older students tend to have slightly higher GPAs. This relationship is statistically significant (p-value = 0.0063), indicating it's unlikely to be due to chance alone.

The analysis successfully identified several interested domains that have fewer than 5 students, representing niche opportunities for specialized programs or targeted recruitment.

Yes, there are notable gender differences in programming proficiency levels. The analysis reveals distinct patterns across Python, SQL, and Java skills between male and female students.

The analysis successfully identified the most popular interested domains among students and shows the gender distribution within each domain through a stacked bar chart visualization.

The analysis reveals the most popular project types among students and how they align with their interested domains. Two visualizations were created: a heatmap showing the relationship between the top 10 project types and interested domains, and a bar chart displaying the most common project types overall.

The analysis successfully identified which future career paths have the highest proportion of students with strong SQL skills. A visualization and detailed breakdown show the top career paths ranked by the percentage of their students who demonstrate strong SQL abilities.

Python shows the weakest proficiency across the student population, with 64 students (35.6%) rating their Python skills as 'Weak' - the highest weakness percentage among all programming languages analyzed.