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Pathway
AI Engineer
Published by Pearson
ISBN-13: 9780135440957
Product Information
Learn the fundamental skills needed to become an AI engineer. Discover how to develop, design, and program complex networks of algorithms to implement artificial intelligence systems and applications.
This pathway covers deep learning core concepts, deep learning frameworks, how to build a natural language translation application, how LLMs generate human language, useful tactics for prompt engineering, building agents and RAG with OpenAI and GPT-4, and Amazon Web Services fundamentals and tools.
Learning Deep Learning by Magnus Ekman
How LLMs Understand and Generate Human Language by Kate Harwood
Quick Guide to ChatGPT, Embeddings, and Other LLMs, 2nd Edition by Sinan Ozdemir
Learn GitHub Copilot by Example by Shaun Wassell
Dr. Magnus Ekman is a director of architecture at NVIDIA Corporation. He leads an engineering team working on CPU performance and power efficiency for chips used to run AI applications. Magnus is the author of the book Learning Deep Learning.
Kate Harwood is currently working with the New York Times' R&D team to integrate state-of-the-art large language models into the Times' reporting and products. She provides training on LLMs, Natural Language Processing and Ethical AI.
Sinan Ozdemir is the founder and CTO of LoopGenius. He has authored multiple books, videos and online courses on data science, machine learning, and generative AI. He most recently launched a new podcast audio series called AI Unveiled.
Shaun Wassell is a lifelong programmer whose goal is to help people build incredible software and solve meaningful problems. He is a popular trainer with Pearson Education and CBT Nuggets. He focuses on Web Development, Programming, and AI.