Artificial Intelligence and Machine Learning (AI/ML)

Artificial Intelligence and Machine Learning (AI/ML) refers to the science of making computers mimic human intelligence processes, learning from experiences, adjusting to new inputs, and performing human-like tasks. Coursera's AI/ML catalogue equips you with comprehensive knowledge on these rapidly growing fields. You'll learn about the foundational concepts of AI/ML, including the design of intelligent agents, problem-solving, and learning from observation. The catalogue also delves into advanced topics such as neural networks, deep learning, natural language processing, and reinforcement learning. By mastering these AI/ML concepts, you'll be prepared to develop and deploy AI systems, design intelligent agents, and create machine learning models for various applications in the tech industry.

Filter by

Subject
Required

Language
Required

The language used throughout the course, in both instruction and assessments.

Learning Product
Required

Learn from top instructors with graded assignments, videos, and discussion forums.
Get in-depth knowledge of a subject by completing a series of courses and projects.
Earn career credentials from industry leaders that demonstrate your expertise.

Level
Required

Duration
Required

Subtitles
Required

Educator
Required

Hands-on Learning
Required

Tools
Required

Results for "Artificial Intelligence and Machine Learning (AI/ML)"

  • Skills you'll gain: Model Deployment, Data Management, Artificial Intelligence and Machine Learning (AI/ML), Infrastructure Architecture, Data Infrastructure, AI Integrations, MLOps (Machine Learning Operations), Application Deployment, AI Workflows, Model Evaluation, Data Cleansing, Artificial Intelligence, Data Security, Application Frameworks, Machine Learning, Data Preprocessing, Data Pipelines, Scalability

  • Skills you'll gain: Unsupervised Learning, Fine-tuning, Model Deployment, Generative AI, Large Language Modeling, Data Management, Generative Model Architectures, Natural Language Processing, Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Infrastructure Architecture, LLM Application, Responsible AI, Data Infrastructure, Applied Machine Learning, Data Preprocessing, Model Optimization

  • DeepLearning.AI

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Model Training, Applied Machine Learning, Machine Learning Algorithms, Transfer Learning, Machine Learning, Machine Learning Methods, Jupyter, Decision Tree Learning, Model Evaluation, Responsible AI, Tensorflow, Scikit Learn (Machine Learning Library), Artificial Intelligence, NumPy, Predictive Modeling, Classification Algorithms, Reinforcement Learning

  • Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Deep Learning, Artificial Intelligence, Amazon Web Services, Applied Machine Learning, AI literacy, Machine Learning

  • Skills you'll gain: Unsupervised Learning, Generative AI, Supervised Learning, Deep Learning, LLM Application, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Reinforcement Learning, Machine Learning Algorithms, Artificial Neural Networks, Feature Engineering, Model Evaluation, Dimensionality Reduction, Model Optimization

  • Skills you'll gain: Generative AI Agents, Google Cloud Platform, Prompt Engineering, Generative AI, Cloud Infrastructure, MLOps (Machine Learning Operations), Artificial Intelligence and Machine Learning (AI/ML), AI Workflows, Natural Language Processing, Artificial Intelligence, Applied Machine Learning, Model Training, Machine Learning

  • Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Artificial Intelligence, Machine Learning Algorithms, Applied Machine Learning, Computational Logic, Machine Learning, Logical Reasoning, Unsupervised Learning, Artificial Neural Networks, Reinforcement Learning, Markov Model, Algorithms, Problem Solving, Systems Design

  • University of Illinois Urbana-Champaign

    Skills you'll gain: Responsible AI, Data Ethics, Wealth Management, Human Learning, Financial Services, Education Software and Technology, Learning Theory, Data Mining, Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Pedagogy, Machine Learning, Artificial Intelligence, AI literacy, AI Enablement, Digital pedagogy, AI Integrations, Financial Planning, Relationship Building, FinTech

  • Skills you'll gain: Oil and Gas, Petroleum Industry, Big Data, Data Management, Data Processing, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Production Process, Machine Learning Methods, Machine Learning

  • From the course: Exam Prep: Google Cloud Certified Cloud Digital Leader·Lesson: AI/ML & Monitoring Fundamentals

  • Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Artificial Intelligence, Tensorflow, Artificial Neural Networks, Machine Learning Methods, Deep Learning, Machine Learning, Applied Machine Learning, Supervised Learning, Responsible AI, Unsupervised Learning

  • Skills you'll gain: Supervised Learning, Machine Learning Methods, Applied Machine Learning, Computer Vision, Machine Learning Algorithms, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Natural Language Processing, Deep Learning, Artificial Neural Networks, Decision Tree Learning, Data Science, Logistic Regression, Data Preprocessing, Embeddings