Introduction to AI and NLP
Master NLP and Generative AI for Business Strategy. This program broadens your comprehension of artificial intelligence, with a specific focus on the rapidly-evolving realm of Natural Language Processing (NLP) within the context of business. You will gain valuable insights into how NLP algorithms proficiently analyze text. Crucially, you will explore the various buy versus build options available in the market, equipping you to make strategic AI decisions.
Who is this for?
This course is designed for Program Managers and professionals who need to understand, evaluate, and strategically implement NLP and Generative AI within a business context.
Prerequisites:
No formal technical prerequisites are listed; the focus is on strategic application and comprehension.
What You Will Achieve
- Master the strategic factors for navigating the build vs. buy options for Large Language Models (LLMs).
- Understand business use cases for ChatGPT and frameworks like LangChain.
- Learn to evaluate NLP models for classification (effectiveness) and regression (RMSE, MAE).
- Grasp the business use cases for clustering algorithms (like K-means) and the data science pipeline.
- Strategically mitigate the drawbacks, automation issues, and personalization implications of using ChatGPT in business.
Key Topics Covered
This 8-session, 1.5-hour-per-session curriculum is structured around in-demand business use cases:
- AI & NLP Foundations: Supervised learning (classification, regression), unsupervised learning (K-means), neural networks, and transfer learning.
- Generative AI Mastery: Introduction to transformers, the HuggingFace library, Introduction to ChatGPT, and Prompt Engineering.
- Strategic Implementation: The ChatGPT API, LangChain apps, usage patterns, and mitigating drawbacks.
- LLM Strategy: Exploring counterparts (GPT-2, GPT-3), analyzing the “Build vs buy” options for LLMs.
- Data Science Context: The data science pipeline, tools landscape, and data best practices.
Assessment & Certification
Mastery is demonstrated through various hands-on activities, including Building a sentiment detection AI model from text or building a ChatGPT model. Students who successfully complete the course will receive a certificate of completion.