Data Science
Create AI Chatbots & Sentiment Engines for Customer Service Enhancement in the banking sector
A hands-on virtual internship to enhance customer service in a real-world banking environment, through the application of AI
Certified by
Role
Data Scientist
Industry
Education
No. of Subscribers
18
Level
Basic
Time Commitment
60 Hours
Duration
30 days
Tools you’ll learn
Here’s What You Work On
About the Company
This virtual internship offers learners the opportunity to experience how artificial intelligence is applied in real-world banking customer support environments. Participants step into the role of an AI intern working alongside customer experience, digital banking, and operations teams to design AI-assisted support systems.
Through this Menternship, learners gain exposure to conversational AI design, sentiment analysis, escalation workflows, and responsible AI decision-making; skills that are increasingly critical for careers in banking, fintech, and regulated industries where trust and customer experience are paramount.
Through this Menternship, learners gain exposure to conversational AI design, sentiment analysis, escalation workflows, and responsible AI decision-making; skills that are increasingly critical for careers in banking, fintech, and regulated industries where trust and customer experience are paramount.
Explore
the following work techniques
Conversational AI Design
Sentiment Analysis
Bridging the gap
Banks handle thousands of customer support interactions daily, ranging from simple queries to emotionally charged, high-risk financial issues. Traditional support systems struggle to balance speed, empathy, and operational efficiency, while poorly designed automation can damage customer trust.
The purpose of this internship is to explore how AI, when thoughtfully designed, can enhance customer support by handling repetitive requests, identifying emotional urgency through sentiment analysis, and ensuring timely human intervention for sensitive cases. Learners are challenged to design AI systems that improve efficiency without compromising trust, compliance, or human judgment.
The purpose of this internship is to explore how AI, when thoughtfully designed, can enhance customer support by handling repetitive requests, identifying emotional urgency through sentiment analysis, and ensuring timely human intervention for sensitive cases. Learners are challenged to design AI systems that improve efficiency without compromising trust, compliance, or human judgment.
Apply
the following skills
Conversational AI Design
Customer Experience
Expected output
By the end of this virtual internship, learners will produce a complete AI-assisted banking support solution blueprint. Deliverables include a customer support journey analysis, conversational chatbot flow designs, a sentiment classification and escalation framework using banking support data, and a capstone system architecture that integrates chatbots, sentiment intelligence, and human agent workflows.
Learners also submit a business-focused impact summary outlining how the proposed system improves response times, customer satisfaction, and operational effectiveness within a regulated banking environment.
Learners also submit a business-focused impact summary outlining how the proposed system improves response times, customer satisfaction, and operational effectiveness within a regulated banking environment.
Create
the following deliverables
AI Assisted Banking Support System (Blue Print)
Report on Business Impact & Metrics
What you’ll need before starting
This virtual internship is designed for learners who have a foundational understanding of data and technology concepts and are eager to apply them in real-world business contexts.
Participants should be comfortable with basic data handling (such as working with spreadsheets or simple datasets), have a conceptual understanding of how AI or machine learning systems work, and possess strong analytical and logical thinking skills.
Familiarity with customer service processes, business workflows, or digital products is helpful but not mandatory. Most importantly, learners should be willing to think critically, communicate their reasoning clearly, and approach AI design with a customer-centric and responsible mindset.
Participants should be comfortable with basic data handling (such as working with spreadsheets or simple datasets), have a conceptual understanding of how AI or machine learning systems work, and possess strong analytical and logical thinking skills.
Familiarity with customer service processes, business workflows, or digital products is helpful but not mandatory. Most importantly, learners should be willing to think critically, communicate their reasoning clearly, and approach AI design with a customer-centric and responsible mindset.
