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AI-Powered Course Recommendation Engine

Client: Corporate Training Provider
Duration: 2 months

Technologies Used

ReactPythonOpenAI APIFastAPIPostgreSQL

Overview

A corporate training provider offering dozens of professional development courses struggled to help potential students navigate their extensive catalog. Students often felt overwhelmed by choices and unsure which courses would best serve their career goals. The company needed an intelligent solution to guide learners toward the most relevant courses, improving enrollment rates and student satisfaction.

The Challenge

With numerous courses spanning multiple disciplines, students faced decision paralysis. Traditional course catalogs provided descriptions but couldn't account for individual learning goals, prior experience, career aspirations, or learning preferences. The sales team spent significant time in consultations trying to recommend appropriate courses, which didn't scale as the business grew. Many potential students abandoned the enrollment process due to uncertainty about which courses to choose.

Our Solution

We built an intelligent recommendation engine powered by OpenAI's language models. The system guides users through a thoughtful questionnaire combining multiple-choice and open-ended questions about their background, goals, learning style, and career objectives. The responses are structured and fed to the AI along with detailed course metadata including learning outcomes, prerequisites, difficulty levels, and career pathways. The AI analyzes this information to generate personalized course recommendations with detailed explanations of why each course fits the learner's profile. The React-based interface makes the experience engaging and conversational, while the Python backend handles the AI integration and recommendation logic.

Results & Impact

  • Increased course enrollment conversion rate through personalized recommendations
  • Reduced sales consultation time, allowing the team to focus on high-value interactions
  • Improved student satisfaction as learners felt more confident in their course selections
  • Generated detailed insights into student preferences and trends, informing course development
  • Enabled self-service course discovery, scaling the enrollment process

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