[D3] Hands-On Machine Learning for Business

Description:
This course equips learners to design natural language processing (NLP)-powered applications for business communication and customer engagement. Students will use modern tools to build intelligent chatbots, analyze sentiment, and create text-based automation workflows.

Why: Practical model-building for problem-solving.

Tools: Lobe.ai, Scikit-learn, Teachable Machine.

Outcomes:

• Train basic ML models.
• Apply supervised/unsupervised learning.
• Deploy models to solve real problems.

Prerequisite: Python for AI Professionals (#D1) or equivalent.

Course Outline:

• Module 1: NLP Essentials (3 hrs)
  • What is NLP?
  • Tools: OpenAI API, Rasa, Hugging Face, Dialogflow.

• Module 2: Text Processing & Sentiment Analysis (4 hrs)
  • Tokenization, stemming, embeddings.
  • Hands-on: customer sentiment analysis.

• Module 3: Chatbot Development with NLP (4 hrs)
  • Conversational AI design.
  • Integrating Rasa or Dialogflow into business apps.

• Module 4: Advanced Applications & Deployment (4 hrs)
  • Building FAQ bots and assistants.
  • Capstone: deploy an NLP chatbot with real-world data.

Learning Outcomes:

• Understand the fundamentals of NLP and text analysis.
• Perform sentiment analysis on text datasets.
• Build and train a conversational chatbot.
• Integrate NLP models into customer-facing applications.
• Evaluate chatbot performance and optimize workflows.

Course Development Lead:
L. Kim. is an NLP researcher and practitioner with 10 years of experience building chatbots and language systems for enterprises in finance and customer service.