Identify course description sentiment
using AI
Below is a free classifier to identify course description sentiment. Just input your text, and our AI will predict the sentiment of your course descriptions. - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("course-description-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/course-description-sentiment/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_text_here"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_text_here"}' \
https://www.nyckel.com/v1/functions/course-description-sentiment/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict the sentiment of your course descriptions..
This pretrained text model uses a Nyckel-created dataset and has 8 labels, including Mixed, Negative, Neutral, Positive, Slightly Negative, Slightly Positive, Very Negative and Very Positive.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of your course descriptions.).
Whether you're just curious or building course description sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify course description sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Course Feedback Analysis: This function can automatically classify the sentiment of student feedback on course descriptions. By evaluating the overall tone, educational institutions can quickly identify which courses are well-received and which may need improvements.
- Marketing Strategy Development: By analyzing the sentiment of course descriptions, education marketers can gauge how prospective students perceive various offerings. This insight can guide marketing initiatives to enhance appealing courses and rework less favorable ones.
- Curriculum Improvement: Academic departments can use sentiment analysis to assess the effectiveness of their course descriptions. If certain descriptions consistently yield negative sentiments, it can prompt a review and revision to better align with student expectations.
- Competitor Analysis: Educational institutions can analyze the sentiment of competitor course descriptions to benchmark their offerings. Understanding what is resonating with potential students can inform their own course development and marketing strategies.
- Student Engagement Monitoring: By regularly assessing the sentiment of updated course descriptions, institutions can track shifts in student interest and engagement. This data can inform outreach efforts and curriculum updates to foster higher enrollment rates.
- Accreditation Reports: Accreditation bodies can benefit from sentiment analysis to gauge perceptions of course descriptions. By including these insights in reports, institutions can demonstrate a commitment to continuous improvement based on stakeholder feedback.
- Predictive Enrollment Trends: By leveraging historical sentiment data from course descriptions, institutions can predict future enrollment trends based on past performance. This can help allocate resources and plan recruitment strategies effectively to maximize student intake.