About This Course
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Novahub Original
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COURSE OVERVIEW
COURSE LESSONS
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LESSON 1 - Foundations: LLMs and How They Work
Introduce the very rough and general concepts that provide context to LLM applications like ChatGPT and Claude.
Generally introduce what an LLM is and how it's trained, and how this impacts our interactions with an LLM.
eg. ChatGPT can't count, it just has been trained on many pieces of text that have specific lengths.
Generally summarize the strengths and weaknesses of an LLM, focusing on their strengths.
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LESSON 2 - Foundations: Introduction to Computer Vision
Exploring the fundamentals of computer vision, including applications, mathematical representations, and future developments.
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LESSON 3 - Foundations: Machine Learning Concepts and Applications
Introduce the concept of machine learning at a very high level. Focus on the idea of Supervised Learning and the applications of this approach. Briefly cover Unsupervised learning, and Reinforcement learning. Don't introduce too much math, just focus on the conceptual explanations, and helping the student remember these concepts.
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LESSON 4 - Foundations: Introduction to Deep Learning
This lesson provides an overview of deep learning, explaining its relationship to machine learning and artificial intelligence, the structure and functioning of neural networks, practical applications, and limitations.
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LESSON 5 - Foundations: Introduction to Natural Language Processing (NLP) and Transformers
The lesson covers the basics and applications of Natural Language Processing and Transformers in NLP, including how machines comprehend and process human language, the steps involved in NLP like tokenization, segmentation, stemming, lemmatization, part-of-speech tagging, and named entity recognition. It also discusses the practical uses of NLP in everyday technology and the job opportunities in the field.