Description
Generative AI Engineering with LLMs Specialization is a course that provides a deep understanding of how to build, fine-tune, and deploy large language models (LLMs) for various AI applications, published by Coursera Online Academy. The course covers the fundamentals of generative AI, an overview of advanced model architectures, training techniques, and optimization strategies. Participants will explore real-world use cases such as text generation, summarization, and conversational AI, while gaining hands-on experience using frameworks such as PyTorch and TensorFlow. This specialization emphasizes ethical considerations, scalability challenges, and integrating LLMs into production pipelines, making it ideal for aspiring AI engineers, data scientists, and developers.
Throughout the program, you will develop skills to build applications using pre-trained frameworks and models such as BERT, GPT, and LLaMA. You will use the Hugging Face transformer library, PyTorch deep learning library, RAG framework, and LangChain to develop and deploy LLM NLP-based applications. Additionally, you will explore tokenization, data loaders, language models and embedding, transformer techniques, attention mechanisms, and rapid engineering. In the final course, you will complete a Capstone Project, applying what you have learned to create a question-answering bot through a series of hands-on labs.
What you will learn in the Generative AI Engineering with LLMs Specialization course:
- In-demand and ready-to-work skills in the AI generation, NLP programs, and large language models
- How to tokenize and load text data for training LLMs and deploying Skip-Gram, CBOW, Seq2Seq, RNN-based, and Transformer models with PyTorch
- How to leverage frameworks and pre-trained models like LangChain and Llama to train, develop, fine-tune, and deploy LLM programs
- How to implement an NLP question and answer system by preparing, developing, and deploying NLP programs using RAG
- And …
Course details
Publisher: Coursera
Instructors: Sina Nazeri , Fateme Akbari , Wojciech ‘Victor’ Fulmyk , Kang Wang , Ashutosh Sagar , Joseph Santarcangelo , and Roodra Pratap Kanwar
Language: English
Learning level: Intermediate
Number of lessons: 77
Learning duration: 7 hours and 48 minutes
Course headings
Prerequisites for the Generative AI Engineering with LLMs Specialization course
None
Course images
Introduction video for the Generative AI Engineering with LLMs Specialization course
Installation Guide
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Subtitles: English
Quality: 720p
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File size
1 GB
