Programme Parameters
Advanced Postgrad
4 Weeks (40 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
Real-World Applications Apply Create Your Own Hybrid Chatbot and Live Chat System for Customer Support skills directly to academic research, thesis work, and publications. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
Real-World Applications
Apply Create Your Own Hybrid Chatbot and Live Chat System for Customer Support skills directly to academic research, thesis work, and publications
📋 Course Objectives
1. Translate Artificial Intelligence theory into practical, reproducible analysis.
2. Produce a reproducible, portfolio-ready project you can cite in a thesis, paper, or job application.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence
🚀 Key Learning Outcomes
• A portfolio-grade Artificial Intelligence deliverable you can defend and extend.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
What the Bot Is Actually For
• Deflection, triage and assistance as three different product goals
• Mapping the support queries that automation genuinely resolves
• Setting the containment target honestly rather than aiming at one hundred percent
Intent and Retrieval
• Intent classification against retrieval over a knowledge base
• Grounding answers in help-centre content so responses stay current
• Handling the out-of-scope question without inventing an answer
State and Flow
• Slot filling, context carry-over and multi-turn state management
• Authentication and account actions before anything sensitive is exposed
• Failure recovery when the user rephrases the same question a third time
The Hybrid Part
• Escalation triggers: sentiment, repetition, explicit request and low confidence
• Passing full transcript and context so the agent does not restart the conversation
• Queueing, availability and what the bot does outside staffed hours
Measuring and Improving
• Containment rate, resolution rate and CSAT split by bot and human
• Reviewing failed conversations as the main source of improvement
• Privacy, transcript retention and disclosing that the user is talking to a bot
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | NLTK |
| Covered Tool / Platform | spaCy |
| Covered Tool / Platform | Hugging Face Transformers |
| Covered Tool / Platform | Gensim |
| Covered Tool / Platform | BERT |
| Covered Tool / Platform | GPT |
Frequently Asked Questions
Scholar Feedback & Reviews
Based on 0 scholar submissions
Rating Breakdown
No verified reviews published yet. Be the first to share your academic experience.
Leave Scholar Feedback
Your rating will help prospective scholars. Ratings below 3 stars are routed privately to the faculty mentor for immediate response.
