Graduate Program Planning Chatbot
Budget / Salary₹12,500–37,500
TypeFreelance project
LocationRemote
Posted2 hours ago
I want an intelligent chat interface that helps future graduate students plan their academic path, with a sharp focus on program selection. When users describe their interests, previous coursework, geographic preferences, or long-term goals, the bot should guide them toward the most suitable master’s or PhD programs, outline entry requirements, and point them to trustworthy information sources (official department pages, accreditation bodies, rankings, faculty research profiles, etc.).
Core expectations
• Natural, flowing conversation: no stiff question-answer trees—use an NLP engine (OpenAI GPT, Rasa, or comparable) so the guidance feels like talking to a real advisor.
• Target user = prospective graduate student: the dialogue must assume bachelor-level completion and dive straight into graduate-specific matters such as thesis vs. non-thesis tracks, research group fit, and interdisciplinary options.
• Program-selection logic: incorporate parameters like location, tuition tolerance, research interests, career outlook, and admission competitiveness, then rank or shortlist programs transparently for the user.
• Updatable knowledge base: file-driven or API-fed so I can refresh program data each application cycle without touching code.
• UX layer: simple web page or React component is fine—just give clear instructions for local deployment.
• Handoff artefacts: commented source code, setup guide, and a sample conversation transcript showing the bot recommending at least three distinct programs based on different user profiles.
Acceptance criteria
1. I install dependencies, run one command, and the chat loads in the browser.
2. The bot asks clarifying questions, then returns a ranked program list with reasoning.
3. Responses stay within graduate-level scope—no generic high-school or undergraduate tips.
4. All instructions and variables are easy to tweak from a config file.
If you’ve built academic advising or admissions chat tools before, let me know what stack you used and share a quick demo link or GIF.
Core expectations
• Natural, flowing conversation: no stiff question-answer trees—use an NLP engine (OpenAI GPT, Rasa, or comparable) so the guidance feels like talking to a real advisor.
• Target user = prospective graduate student: the dialogue must assume bachelor-level completion and dive straight into graduate-specific matters such as thesis vs. non-thesis tracks, research group fit, and interdisciplinary options.
• Program-selection logic: incorporate parameters like location, tuition tolerance, research interests, career outlook, and admission competitiveness, then rank or shortlist programs transparently for the user.
• Updatable knowledge base: file-driven or API-fed so I can refresh program data each application cycle without touching code.
• UX layer: simple web page or React component is fine—just give clear instructions for local deployment.
• Handoff artefacts: commented source code, setup guide, and a sample conversation transcript showing the bot recommending at least three distinct programs based on different user profiles.
Acceptance criteria
1. I install dependencies, run one command, and the chat loads in the browser.
2. The bot asks clarifying questions, then returns a ranked program list with reasoning.
3. Responses stay within graduate-level scope—no generic high-school or undergraduate tips.
4. All instructions and variables are easy to tweak from a config file.
If you’ve built academic advising or admissions chat tools before, let me know what stack you used and share a quick demo link or GIF.
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