Student Intern-AI HK
Siemens
Student Interns integrate classroom studies with learning through productive work experiences in a field related to a student's academic or career goals. Internships are generally one term experiences, generally in the summer, though some can translate into part time work or follow on terms. Student interns may or may not receive college credit or a grade for their internship experience.
2-Week Training Plan
Week 1: Foundations of AI and Conversational Technologies
Topics:
Introduction to AI and Natural Language Processing (NLP)
Basics of AI Voice Agents: architecture, conversation flow design, and training
ChatBot fundamentals: architecture, prompt engineering, and knowledge base setup
Week 2: Practical Implementation
Topics:
Data preparation and annotation for AI models
Hands-on creation of a basic AI Voice Agent prototype
Development of a functional ChatBot prototype for APAC finance use cases
R&D Phase Plan
Week 3-4: Develop AI Voice Agent Framework
Objective: Create a standardized framework and company guidelines for implementing AI Voice Agents.
Focus on data structuring, training methodologies, and performance evaluation.
Deliverable: A documented framework tailored for organizational use.
Week 5-6: APAC Finance ChatBot Implementation
Objective: Develop and test a functional ChatBot for deal guidelines and revenue recognition.
Tasks include data preparation, knowledge base setup, testing, and validation.
Deliverable: A working prototype with detailed testing documentation.
Week 7: Cross-Project Optimization
Objective: Identify synergies between the AI Voice Agent and ChatBot projects.
Develop error analysis frameworks and maintenance protocols.
Deliverable: Recommendations for integrating both systems.
Week 8: Final Presentation Preparation
Objective: Summarize findings, deliverables, and recommendations.
Structure:
Project Overview
Technical Approach
Key Findings
Implementation Recommendations
Future Opportunities
Deliverable: Final presentation to stakeholders.
This concise plan ensures structured learning in the first two weeks, followed by focused R&D work leading to impactful deliverables.
2-Week Training Plan
Week 1: Foundations of AI and Conversational Technologies
Topics:
Introduction to AI and Natural Language Processing (NLP)
Basics of AI Voice Agents: architecture, conversation flow design, and training
ChatBot fundamentals: architecture, prompt engineering, and knowledge base setup
Week 2: Practical Implementation
Topics:
Data preparation and annotation for AI models
Hands-on creation of a basic AI Voice Agent prototype
Development of a functional ChatBot prototype for APAC finance use cases
R&D Phase Plan
Week 3-4: Develop AI Voice Agent Framework
Objective: Create a standardized framework and company guidelines for implementing AI Voice Agents.
Focus on data structuring, training methodologies, and performance evaluation.
Deliverable: A documented framework tailored for organizational use.
Week 5-6: APAC Finance ChatBot Implementation
Objective: Develop and test a functional ChatBot for deal guidelines and revenue recognition.
Tasks include data preparation, knowledge base setup, testing, and validation.
Deliverable: A working prototype with detailed testing documentation.
Week 7: Cross-Project Optimization
Objective: Identify synergies between the AI Voice Agent and ChatBot projects.
Develop error analysis frameworks and maintenance protocols.
Deliverable: Recommendations for integrating both systems.
Week 8: Final Presentation Preparation
Objective: Summarize findings, deliverables, and recommendations.
Structure:
Project Overview
Technical Approach
Key Findings
Implementation Recommendations
Future Opportunities
Deliverable: Final presentation to stakeholders.
This concise plan ensures structured learning in the first two weeks, followed by focused R&D work leading to impactful deliverables.
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