Description
Generative AI Engineering with LLMs is a comprehensive specialization offered by IBM on Coursera, designed to advance careers in machine learning and AI. This program focuses on generative AI and large language models (LLMs), providing learners with the skills needed to excel in roles such as AI engineer, NLP engineer, and data scientist. The specialization is self-paced, allowing learners to complete it in approximately 13-14 weeks by dedicating 4-5 hours per week.
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The curriculum covers a wide range of topics, including tokenization, text data loading, and deploying models like Skip-Gram, CBOW, Seq2Seq, RNN-based, and Transformer-based models using PyTorch. Learners will also gain hands-on experience with frameworks and pre-trained models such as LangChain and LLaMA, essential for training, developing, fine-tuning, and deploying LLM applications.
The program is suitable for individuals with a basic understanding of Python, while knowledge of PyTorch, machine learning, and neural networks is beneficial but not mandatory. It is entirely online, allowing learners to access lectures, readings, and assignments anytime and anywhere.
Upon completion, participants will have the confidence and skills to pursue careers in AI engineering, with practical experience gained through hands-on labs and projects. These projects include creating NLP data loaders, developing language models, and building AI applications using RAG and LangChain.
While the course is not free, financial aid is available for those who qualify. Completing the specialization earns a shareable certificate, enhancing career prospects and demonstrating expertise in generative AI and LLMs.
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Generative AI Engineering with LLMs's Core Features
Self-paced learning
13-14 weeks duration
Basic Python knowledge required
Hands-on labs and projects
Focus on generative AI and LLMs
Skills for AI and NLP engineering
Online access to materials
Certificate upon completion
Financial aid available
Pre-trained models and frameworks
Practical experience with PyTorch
Training and deploying LLM applications
Capstone project included
No university credit
Suitable for data scientists and ML engineers
How to use Generative AI Engineering with LLMs?
Enroll: Choose a course and enroll
Learn: Access lectures and materials online
Practice: Complete hands-on labs and projects
Complete: Finish the specialization and earn a certificate
Generative AI Engineering with LLMs's Use Cases
- AI Engineering
- NLP Applications
- Data Science
- Machine Learning
- Model Deployment
