Machine Learning courses
1795 Courses
人工智能
《人工智能》英文版慕课从教学实际需求出发，面向学生国际化发展目标，教学内容紧紧围绕人工智能的基本思想、基本理论、基本方法及其应用展开，融合前沿内容与典型应用。具体包括：智能体、知识表示、知识推理、搜索、进化计算、群体智能、人工神经网络、机器学习、深度学习和专家系统等基本理论与实用方法。了解新兴应用等前沿内容，重点介绍人工智能的核心思想、基本理论，.
IA como Ferramenta de Aprendizagem e Pesquisa
O curso IA como Ferramenta de Aprendizagem e Pesquisa aborda uma visão abrangente sobre a IA, com enfoque especial na sua aplicação como ferramenta de aprendizagem e de pesquisa, preparando os estudantes para navegar e aproveitar as oportunidades que essa tecnologia revolucionária oferece.
AI and Machine Learning in Cybersecurity
Explore this fascinating field and develop the skills to leverage AI in your cybersecurity challenges. In this course, AI and Machine Learning in Cybersecurity, you’ll learn to use AI to leverage your cybersecurity skills. First, you’ll explore machine learning and anomaly detection. Next, you’ll discover AI cybersecurity strengths like ransomware,.
Enhancing Traditional ML with Generative AI
As AI evolves, professionals are challenged with understanding how emerging Generative AI capabilities can coexist with traditional machine learning approaches. In this course, Enhancing Traditional ML with Generative AI, you’ll learn when to use these technologies and how they compliment each other. First, you’ll explore the differences and synerg.
Introduction to Generative AI vs. Traditional ML
Understanding the difference between traditional machine learning and generative AI is crucial for making informed decisions about AI implementation. In this course, Introduction to Generative AI vs. Traditional ML, you’ll learn to evaluate, compare, and choose the best AI approach for your projects. First, you’ll explore the fundamentals of tradit.
AWS Certified Machine Learning Engineer - Associate (MLA-C01): ML Model Development
AWS has a broad range of machine learning services to help businesses approach complex problems. In this course, AWS Certified Machine Learning Engineer - Associate (MLA-C01): ML Model Development, you’ll learn to navigate these services and select the approach that is most appropriate for your machine learning (ML) solutions. First, you’ll explore.
AIOps: CI/CD for AI Systems
DevOps is a concept that has been around a long time and has been applied to ML and, recently, LLMs. In this course, AIOps: CI/CD for AI Systems, you’ll learn to apply CI/CD, a fundamental concept of DevOps, to ML, AI, and LLMs. First, you’ll explore how CI/CD pipelines work with ML models. Next, you’ll discover how to deploy to cloud environments.
AWS AI Practitioner
The AWS Certified AI Practitioner Specialization is meant for those who desire to establish a solid base in Artificial Intelligence (AI) and Machine Learning (ML) and have the ability to utilize AWS cloud services. This specialization is aligned with the AWS AI Practitioner Certification exam and offers a broad understanding of AI concepts, generat.
Q-Learning Unleashed: Building Intelligent Agents
In this course, we focus on building a Q-learning agent step by step. We start with the Bellman equation and the Q-table update, then implement a basic Q-learning function. Next, we incorporate an exploration policy (ε-greedy), and finally we demonstrate how to use the learned Q-table for decision making.
Azure AI Services: Core applications
"Core Applications of Azure AI Services" is an introductory course designed to familiarize users with the practical application of Microsoft's Azure AI services in various real-world scenarios. It aims to bridge the gap between theoretical AI concepts and their actual implementation. You will learn how Azure AI services are utilized to solve real-.
