Large Language Models for Artificial Intelligence Certificate Program
California Institute of Technology
Pasadena, CA
Throughout this immersive course, participants will actively engage with the core functionalities of Large Language Models (LLMs), including natural language understanding, text generation, sentiment analysis, and language translation. You will not only learn how to train, fine-tune, and deploy LLMs effectively through coding but also explore the use of intuitive low-code platforms for machine learning, ensuring a comprehensive understanding of both technical and accessible AI development approaches.
Our program is deeply committed to hands-on learning, blending direct coding exercises with the exploration of low-code tools to interact with some of the most advanced LLMs available today. Through practical exercises, case studies, and projects that mirror real-world challenges, you will acquire firsthand experience in leveraging LLMs for diverse applications, fully equipping you with the skills needed for your professional growth.
By bridging the gap between theoretical knowledge and practical, applicable skills, this program ensures you are ready to implement LLMs in your work environment.
Benefits
Upon successful completion of this course, you will be able to:
- Describe how NLP is used to solve business problems
- Write functional code using Scikit-Learn, Keras, NLTK, TextBlob, and Pandas to solve business-related queries and process data
- Describe the concept of Tokenization and Vectorization
- Develop word embeddings using several different approaches
- Classify text using several different approaches (e.g., sentiment analysis, intent)
- Analyze transformer architecture: Positional Encoding + Attention Mechanism
- Extract transformers from HuggingFace portals and use them for business applications
- Communicate with Large Language Models (LLM) using prompt engineering
Who Should Attend
This short course is designed for professionals who are eager to expand their expertise into the realm of generative AI and Large Language Models. It is particularly beneficial for individuals with a background in computer science, data science, software engineering, and related technical fields. Ideal candidates will have a foundational understanding of machine learning concepts, proficiency in programming languages such as Python, and a passion for innovative AI technologies.
The Machine Learning for Advanced Analytics course or similar introductory courses in Python and machine learning are prerequisites for this program.