Intro to ML with Python
A comprehensive course on machine learning using Python, covering deep learning, GANs, image processing, various algorithms, and industrial applications, accessible to all skill levels.
Description for Intro to ML with Python
Features of Course
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Arizona State University
Duration: 12 hours (approximately)
Schedule: Flexible
Pricing for Intro to ML with Python
Use Cases for Intro to ML with Python
FAQs for Intro to ML with Python
Reviews for Intro to ML with Python
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Intro to ML with Python
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Welcome to the 'Gen AI for Code Generation for Python' course, where you will begin a journey to hone and expand your abilities in the field of code generation using Generative AI.
Learn to use the latest LLM APIs, the LangChain Expression Language (LCEL), and develop a conversational agent.
This course covers the development, impact, and future of Generative AI through lectures, critical AI technologies, and interactive assessments.
Master coding basics and create a Hangman game using generative AI tools like Google Bard in a beginner-friendly, 1.5-hour guided project.
Learn about AI principles and platforms like IBM Watson and Hugging Face, integrate RAG technology for chatbot intelligence, create web apps using Python libraries, and develop interfaces with generative AI models and Python frameworks.
Acquire practical skills to build a generative AI application by constructing a retrieval augmented generation (RAG) system using data, Qdrant, and LLMs.
Gain a comprehensive understanding of AI's potential, ethical considerations, and applications in efficient programming and common coding tasks using various LLMs.
Gain expertise in deploying and managing LLMs on Azure, optimizing interactions with Semantic Kernel, and applying Retrieval Augmented Generation (RAG) techniques.
Gain expertise in deploying and managing LLMs on Azure, optimizing interactions with Semantic Kernel, and applying Retrieval Augmented Generation (RAG) techniques.
Featured Tools
This course offers a concise summary of essential multivariate calculus for machine learning, including practical tools, vector calculations, function approximation, and neural network applications, to build confidence for advanced studies.
Learn to leverage Google Cloud's data-to-AI tools, generative AI capabilities, and Vertex AI for comprehensive ML model development.
Learn to explain Azure Machine Learning Studio's no-code capabilities, fundamental machine learning principles, key development tasks, and common ML categories.
Gain a comprehensive understanding of AI terminology, applications, development, and strategy, while navigating ethical and societal considerations in a non-technical context.
Become proficient in the use of algorithmic programming techniques. Enhance your Software Engineering or Data Science career by acquiring an understanding of algorithms through programming and puzzle solving.