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Artificial Intelligence Courses

Artificial intelligence courses can help you learn machine learning algorithms, natural language processing, computer vision, and neural networks. You can build skills in data analysis, predictive modeling, and automating tasks using AI techniques. Many courses introduce tools like TensorFlow, PyTorch, and Scikit-learn, that support implementing AI solutions and developing applications that leverage these advanced technologies.


Popular AI Courses and Certifications


  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM RAG and Agentic AI

    Skills you'll gain: Prompt Engineering, AI Orchestration, AI Workflows, Model Context Protocol, LangChain, Retrieval-Augmented Generation, Agentic Workflows, Tool Calling, LangGraph, LLM Application, Agentic systems, Multimodal Prompts, Generative AI, Generative AI Agents, Vector Databases, Generative Model Architectures, OpenAI API, Embeddings, Responsible AI, Software Development

    4.6
    Rating, 4.6 out of 5 stars
    ·
    672 reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
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    Google

    Google Business Intelligence

    Skills you'll gain: Data Modeling, Stakeholder Engagement, Database Design, Dashboard, Business Intelligence, Extract, Transform, Load, Tableau Software, Data Warehousing, Data Pipelines, Interactive Data Visualization, Business Reporting, Data-Driven Decision-Making, Data Visualization, Interviewing Skills, Applicant Tracking Systems, Business Process, AI Enablement, Business Analysis, Data Analysis, SQL

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
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    6.8K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Google Advanced Data Analytics

    Skills you'll gain: Data Storytelling, Data Visualization, Data Ethics, Exploratory Data Analysis, Sampling (Statistics), Data Visualization Software, Feature Engineering, Regression Analysis, Descriptive Statistics, Logistic Regression, Statistical Hypothesis Testing, Model Evaluation, Data Analysis, Tableau Software, Data Science, Statistical Analysis, Machine Learning, Object Oriented Programming (OOP), Interviewing Skills, Python Programming

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    11K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    MLOps | Machine Learning Operations

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, Responsible AI, Data Manipulation, Exploratory Data Analysis, Containerization, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

    4.2
    Rating, 4.2 out of 5 stars
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    573 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Enterprise Workflow

    Skills you'll gain: Feature Engineering, Model Deployment, Data Visualization, Data Ethics, Exploratory Data Analysis, Model Evaluation, Unsupervised Learning, Data Presentation, Tensorflow, Dimensionality Reduction, MLOps (Machine Learning Operations), Probability Distribution, Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Data Science, Machine Learning, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
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    354 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    S

    SAS

    SAS Machine Learning Engineer

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Data Preprocessing, Exploratory Data Analysis, Logistic Regression, Statistical Machine Learning, Model Evaluation, Supervised Learning, Decision Tree Learning, Probability & Statistics, Statistics, Machine Learning Software, Classification And Regression Tree (CART), Workflow Management, Predictive Modeling, Random Forest Algorithm, Feature Engineering, SAS (Software), Machine Learning, Applied Machine Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    103 reviews

    Advanced · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

  • C

    Coursera

    Deep Learning with PyTorch : Siamese Network

    Skills you'll gain: Embeddings, PyTorch (Machine Learning Library), Artificial Neural Networks, Image Analysis, Deep Learning, Applied Machine Learning, Convolutional Neural Networks, Computer Vision

    4.7
    Rating, 4.7 out of 5 stars
    ·
    49 reviews

    Advanced · Guided Project · Less Than 2 Hours

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Advanced Machine Learning on Google Cloud

    Skills you'll gain: Model Deployment, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Reinforcement Learning, Transfer Learning, Computer Vision, Systems Design, Machine Learning Methods, Applied Machine Learning, Image Analysis, AI Personalization, Cloud Deployment, Recurrent Neural Networks (RNNs), Hybrid Cloud Computing, Systems Architecture, Performance Tuning, Embeddings

    4.5
    Rating, 4.5 out of 5 stars
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    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Advanced Project Operations & Automation

    Skills you'll gain: Earned Value Management, Workflow Management, Business Process Automation, Change Management, Project Management, Project Controls, Performance Measurement, Automation, Predictive Modeling, AI Enablement, Strategic Communication, Data-Driven Decision-Making, Risk Analysis, Process Improvement and Optimization, Process Optimization, Analytics, Cloud-Based Integration, Generative AI, Systems Integration, Machine Learning

    Advanced · Specialization · 3 - 6 Months

  • Status: New
    New
    P

    Packt

    Decoding Large Language Models

    Skills you'll gain: Large Language Modeling, LLM Application, Model Deployment, AI Enablement, Transfer Learning, Prompt Engineering, Generative AI, Model Evaluation, Deep Learning, Natural Language Processing, Recurrent Neural Networks (RNNs), Responsible AI, Scalability, Machine Learning, Performance Tuning, Systems Integration

    Advanced · Course · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Probabilistic Graphical Models

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Bayesian Statistics, Statistical Modeling, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Machine Learning Methods, Statistical Inference, Sampling (Statistics), Statistical Methods, Algorithms, Model Evaluation, Computational Thinking

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    T

    Tecnológico de Monterrey

    Leadership and Critical Thinking

    Skills you'll gain: Critical Thinking, Organizational Leadership, Positivity, Self-Awareness, Stress Management, Leadership, Resilience, Influencing, Motivational Skills, Decision Making, Personal Development, Leadership Development, Industrial and Organizational Psychology, Leadership and Management, Emotional Intelligence, Business Leadership, Systems Thinking, Strategic Decision-Making, Research, Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    351 reviews

    Advanced · Specialization · 1 - 3 Months

What brings you to Coursera today?

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In summary, here are 10 of our most popular artificial intelligence courses

  • IBM RAG and Agentic AI: IBM
  • Google Business Intelligence: Google
  • Google Advanced Data Analytics: Google
  • MLOps | Machine Learning Operations: Duke University
  • IBM AI Enterprise Workflow: IBM
  • SAS Machine Learning Engineer: SAS
  • Deep Learning with PyTorch : Siamese Network: Coursera
  • Advanced Machine Learning on Google Cloud: Google Cloud
  • Advanced Project Operations & Automation: Coursera
  • Decoding Large Language Models: Packt

Frequently Asked Questions about Artificial Intelligence

Artificial intelligence (AI) refers to the simulation of human intelligence in machines programmed to think and learn like humans. This technology is crucial because it has the potential to transform industries, enhance productivity, and improve decision-making processes. AI systems can analyze vast amounts of data quickly, identify patterns, and make predictions, which can lead to innovative solutions in various fields such as healthcare, finance, and education.‎

A variety of job opportunities exist in the field of artificial intelligence. Roles such as AI engineer, data scientist, machine learning engineer, and AI researcher are in high demand. Additionally, positions in AI ethics, data analysis, and AI project management are emerging as organizations increasingly integrate AI into their operations. These roles often require a blend of technical skills and domain knowledge, making them accessible to individuals from diverse backgrounds.‎

To pursue a career in artificial intelligence, you should focus on developing a strong foundation in programming languages such as Python and R, as well as understanding algorithms and data structures. Knowledge of machine learning, statistics, and data analysis is also essential. Familiarity with AI frameworks and tools, such as TensorFlow or PyTorch, can enhance your skill set. Additionally, soft skills like problem-solving, critical thinking, and effective communication are valuable in this field.‎

There are numerous online courses available for learning about artificial intelligence. Some notable options include the Artificial Intelligence: an Overview Specialization and the Artificial Intelligence with Python: Foundations to Projects Specialization. These courses cover fundamental concepts and practical applications, making them suitable for learners at various levels.‎

Yes. You can start learning artificial intelligence on Coursera for free in two ways:

  1. Preview the first module of many artificial intelligence courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in artificial intelligence, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn artificial intelligence effectively, start by identifying your current skill level and goals. Begin with introductory courses to build foundational knowledge, then progress to more advanced topics. Engage in hands-on projects to apply what you've learned, and consider joining online communities or forums to connect with other learners. Consistent practice and exploration of real-world applications will reinforce your understanding and boost your confidence.‎

Typical topics covered in artificial intelligence courses include machine learning, natural language processing, computer vision, and robotics. Courses often explore the ethical implications of AI, data bias, and algorithm limitations. Additionally, learners may study specific applications of AI in various industries, such as finance, healthcare, and scientific research, providing a comprehensive understanding of the field.‎

For training and upskilling employees in artificial intelligence, courses like the CertNexus Certified Artificial Intelligence Practitioner Professional Certificate are particularly beneficial. These programs are designed to equip professionals with the necessary skills to implement AI solutions effectively in their organizations, fostering a culture of innovation and adaptability in the workforce.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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