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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 Artificial Intelligence Courses and Certifications


  • Status: Free Trial
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    IBM

    Introduction to Artificial Intelligence (AI)

    Skills you'll gain: Responsible AI, Generative AI, Generative Model Architectures, LLM Application, AI literacy, Natural Language Processing, Robotics, Risk Mitigation

    4.7
    Rating, 4.7 out of 5 stars
    ·
    23K reviews

    Beginner · Course · 1 - 4 Weeks

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    IBM

    Generative AI: Prompt Engineering Basics

    Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Generative AI

    4.7
    Rating, 4.7 out of 5 stars
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    7.9K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
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    IBM

    IBM Generative AI Engineering

    Skills you'll gain: Prompt Engineering, Prompt Patterns, Data Wrangling, Large Language Modeling, LangChain, Retrieval-Augmented Generation, Exploratory Data Analysis, Unsupervised Learning, Generative Model Architectures, PyTorch (Machine Learning Library), ChatGPT, Generative AI, Restful API, LLM Application, Keras (Neural Network Library), Supervised Learning, Responsible AI, Vector Databases, Fine-tuning, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
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    100K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
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    IBM

    IBM RAG and Agentic AI

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

    4.6
    Rating, 4.6 out of 5 stars
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    939 reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
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    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, PyTorch (Machine Learning Library), Large Language Modeling, Retrieval-Augmented Generation, Computer Vision, Unsupervised Learning, Generative Model Architectures, Prompt Patterns, Generative AI, PySpark, Keras (Neural Network Library), Supervised Learning, LLM Application, Generative AI Agents, Vector Databases, Fine-tuning, Machine Learning, Python Programming, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    22K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
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    IBM

    AI Foundations for Everyone

    Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Generative AI, Responsible AI, Generative Model Architectures, IBM Cloud, AI Workflows, LLM Application, Workflow Management, AI literacy, No-Code Development, Machine Learning Software, Natural Language Processing, Business Workflow Analysis, Artificial Intelligence, Self Service Technologies, Machine Learning, Deep Learning, Data Science

    4.7
    Rating, 4.7 out of 5 stars
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    36K reviews

    Beginner · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
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    IBM

    Developing AI Applications with Python and Flask

    Skills you'll gain: Restful API, Flask (Web Framework), Application Deployment, Application Programming Interface (API), Unit Testing, Cloud Applications, AI Integrations, Python Programming, Web Applications, Software Development Life Cycle, IBM Cloud, Web Development, Development Testing, Artificial Intelligence, Code Review, Integrated Development Environments, AI literacy, Server Side, Programming Principles

    4.4
    Rating, 4.4 out of 5 stars
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    1.4K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    I

    IBM

    IBM AI Product Manager

    Skills you'll gain: Prompt Engineering, Prompt Patterns, AI Product Strategy, Generative AI, New Product Development, Product Management, Product Lifecycle Management, Generative Model Architectures, Product Development, Innovation, ChatGPT, Product Roadmaps, Product Planning, Responsible AI, Commercialization, Generative Adversarial Networks (GANs), Artificial Intelligence, Product Strategy, Project Management Life Cycle, Product Design

    4.7
    Rating, 4.7 out of 5 stars
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    36K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Developer

    Skills you'll gain: Prompt Engineering, Prompt Patterns, Software Development Life Cycle, Retrieval-Augmented Generation, Large Language Modeling, Software Architecture, Computer Vision, LangChain, ChatGPT, Restful API, Responsive Web Design, Generative AI, Responsible AI, IBM Cloud, Data Ethics, AI Workflows, Python Programming, Software Development, Machine Learning, Data Science

    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
    ·
    82K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Generative AI: Introduction and Applications

    Skills you'll gain: Generative AI, Generative Model Architectures, ChatGPT, AI literacy, Artificial Intelligence and Machine Learning (AI/ML), Augmented and Virtual Reality (AR/VR), Machine Learning, Data Synthesis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.4K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM Machine Learning

    Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Autoencoders, Feature Engineering, Dimensionality Reduction, Supervised Learning, Generative AI, Classification Algorithms, Regression Analysis, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Data Science, Machine Learning, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    3.6K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    I

    IBM

    IBM Data Analyst

    Skills you'll gain: Data Storytelling, Dashboard Creation, Data Presentation, Data Wrangling, Generative AI, Plotly, Data Visualization Software, Web Scraping, Data Visualization, Exploratory Data Analysis, SQL, Plot (Graphics), Dashboard, Interactive Data Visualization, Data Analysis, Professional Networking, IBM Cognos Analytics, Excel Formulas, Python Programming, Microsoft Excel

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    99K reviews

    Beginner · Professional Certificate · 3 - 6 Months

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

  • Introduction to Artificial Intelligence (AI): IBM
  • Generative AI: Prompt Engineering Basics: IBM
  • IBM Generative AI Engineering: IBM
  • IBM RAG and Agentic AI: IBM
  • IBM AI Engineering: IBM
  • AI Foundations for Everyone: IBM
  • Developing AI Applications with Python and Flask: IBM
  • IBM AI Product Manager: IBM
  • IBM AI Developer: IBM
  • Generative AI: Introduction and Applications: IBM

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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