Google Cloud’s Generative AI Learning Path is a thorough educational program created to assist students in comprehending the principles of generative AI, responsible AI, large language models (LLMs), and how generative AI technologies can be used with Google Cloud resources. The learning route covers subjects including prompt design, AI model [...]
Google Cloud offers a free introductory microlearning course called Introduction to Generative AI through Google Cloud Skills Boost. It offers a basic overview of generative artificial intelligence (AI), describing what it is, how it functions, how it varies from conventional machine learning, and the various kinds of generative AI models. [...]
Vertex’s Prompt Design AI is a free beginning course offered by Google Cloud that shows students how to use Gemini and Vertex AI to construct powerful prompts for generative AI models. Essential prompt engineering strategies are covered in the course, including creating precise and unambiguous prompts, decomposing tasks, offering examples, [...]
IBM offers a beginner-friendly course called Introduction to Prompt Engineering that teaches students how to write efficient prompts for generative AI tools like ChatGPT and other large language models. Prompt engineering principles, best practices, zero-shot and few-shot prompting, Chain-of-Thought and Tree-of-Thought approaches, multimodal prompting, and practical AI applications are all [...]
A beginner-friendly course called Prompt Engineering for ChatGPT teaches students how to interact with AI systems like ChatGPT and other large language models (LLMs). The course, which was developed by Vanderbilt University and instructed by Dr. Jules White, covers fundamental prompt engineering techniques, few-shot prompting, prompt patterns, chain-of-thought approaches, and [...]
OpenAI and DeepLearning collaborated to build the beginner-friendly short course Intro to ChatGPT Prompt Engineering for Developers.AI. The course, which is taught by Isa Fulford and Andrew Ng, teaches students how to create strong AI-powered applications utilizing large language models (LLMs) and the OpenAI API, as well as how to [...]
A beginner-friendly introduction to the principles of data science and machine learning may be found in Microsoft’s Intro to Machine Learning and Data Science study materials. Data analysis, the machine learning lifecycle, supervised and unsupervised learning, model training, evaluation, and responsible AI are among the key topics covered in the [...]
SuperDataScience’s Machine Learning A-ZTM: AI, Python & R is a practical machine learning course that introduces students to the entire machine learning workflow, including data preprocessing, supervised and unsupervised learning, reinforcement learning, model evaluation, and real-world Python and R implementation. To help students practice machine learning concepts with real-world examples, [...]
This online course teaches students how to analyze data using a machine learning technique and introduces them to the principles of machine learning. Using Python and scikit-learn, it covers important topics like supervised and unsupervised learning, Naive Bayes, Support Vector Machines (SVM), Decision Trees, Linear Regression, Clustering, Feature Selection, PCA, [...]
For programmers who wish to learn how to create real-world machine learning models, Introduction to Machine Learning for Coders is a useful, hands-on machine learning course. Important subjects like data preparation, Random Forests, model validation, feature importance, neural networks, and developing data-driven applications are covered in the course. It is [...]