Build on your existing knowledge with intermediate gpt prompting techniques and real-world applications.
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Probability, linear algebra, attention mechanisms
Python data science skills; experience with NLP libraries
Generative AI: Prompt Engineering Basics
Beginner99% Of People STILL Don't Know The Basics Of Prompting (ChatGPT, Gemini, Claude)
BeginnerFunctions, Tools and Agents with LangChain
IntermediateTransformers Explained - How transformers work
IntermediateIllustrated Guide to Transformers Neural Network: A step by step explanation
IntermediateTransformer Neural Networks - EXPLAINED! (Attention is all you need)
IntermediateGoogle Prompting Essentials
AdvancedGoogleDiscover the Art of Prompting
IntermediateGenerative AI: Prompt Engineering Basics
Beginner99% Of People STILL Don't Know The Basics Of Prompting (ChatGPT, Gemini, Claude)
BeginnerFunctions, Tools and Agents with LangChain
IntermediateTransformers Explained - How transformers work
IntermediateIllustrated Guide to Transformers Neural Network: A step by step explanation
IntermediateTransformer Neural Networks - EXPLAINED! (Attention is all you need)
IntermediateGoogle Prompting Essentials
AdvancedGoogleDiscover the Art of Prompting
IntermediateFollow these courses in order to complete the learning path. Click on any course to enroll.
Generative AI: Prompt Engineering Basics
Learn 99% Of People STILL Don't Know The Basics Of Prompting (ChatGPT, Gemini, Claude)
Learn Functions, Tools and Agents with LangChain
Transformers Explained - How transformers work
Illustrated Guide to Transformers Neural Network: A step by step explanation
Transformer Neural Networks - EXPLAINED! (Attention is all you need)
Taught by AI experts at Google, this course introduces a 5-step framework for generating effective outputs from AI. It covers multimodal prompting, prompt chaining, and building reusable prompt libraries.
Explore related content to expand your skills beyond this learning path.
Build on your existing knowledge with intermediate gpt prompting techniques and real-world applications.
You'll work through Deepen your understanding with advanced concepts; Build more complex real-world projects; Learn optimization and best practices; Process and tokenize text data effectively; Build text classification and sentiment analysis models; Implement named entity recognition (NER) systems.
About 11 hours of study across 8 courses — and you can go at your own pace.
It's pitched at intermediate level, so a little prior familiarity helps.
8 curated courses, sequenced from foundational to advanced.
Around $49 total if you buy every course — but many include free audit options.
Enroll in this path to track your progress and stay motivated.