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  • Artificial Intelligence

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
    Free Trial
    I

    IBM

    IBM RAG and Agentic AI

    Skills you'll gain: Prompt Engineering, LangChain, Tool Calling, LangGraph, Agentic systems, Multimodal Prompts, Generative AI, LLM Application, Generative AI Agents, Responsible AI, OpenAI, Artificial Intelligence and Machine Learning (AI/ML), Application Design, Application Deployment, Application Development, Large Language Modeling, UI Components, Semantic Web, Artificial Intelligence, Software Development

    4.6
    Rating, 4.6 out of 5 stars
    ·
    534 reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Google Business Intelligence

    Skills you'll gain: Data Modeling, Stakeholder Engagement, Database Design, Dashboard, Business Intelligence, Extract, Transform, Load, Tableau Software, Databases, Data Warehousing, Database Systems, Data Pipelines, Data-Driven Decision-Making, Data Visualization, Interviewing Skills, Business Process, Business Analysis, Professional Development, Google Gemini, Data Analysis, SQL

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6.2K 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 Presentation, Data Visualization Software, Feature Engineering, Regression Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Advanced Analytics, Data Analysis, Data Science, Tableau Software, Statistical Analysis, Machine Learning, Object Oriented Programming (OOP), Interviewing Skills, Python Programming

    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
    ·
    10K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Enterprise Workflow

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

    4.3
    Rating, 4.3 out of 5 stars
    ·
    350 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    MLOps | Machine Learning Operations

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

    4.2
    Rating, 4.2 out of 5 stars
    ·
    550 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Advanced Machine Learning on Google Cloud

    Skills you'll gain: Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Large Language Modeling, Reinforcement Learning, Computer Vision, Keras (Neural Network Library), Systems Design, Applied Machine Learning, Image Analysis, AI Personalization, Hybrid Cloud Computing, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Pandas (Python Package)

    4.5
    Rating, 4.5 out of 5 stars
    ·
    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    I

    IBM

    Generative AI for Mobile App Developers

    Skills you'll gain: Prompt Engineering, Prompt Patterns, Generative AI, Large Language Modeling, Responsible AI, AI Personalization, Mobile Development, ChatGPT, Anthropic Claude, Artificial Intelligence, LLM Application, Software Development Tools, Software Testing, Apple iOS, Test Automation, Software Development, Machine Learning Methods, DevSecOps, AI Product Strategy, Artificial Intelligence and Machine Learning (AI/ML)

    4.7
    Rating, 4.7 out of 5 stars
    ·
    11K reviews

    Advanced · Specialization · 1 - 3 Months

  • Status: New
    New
    P

    Packt

    Decoding Large Language Models

    Skills you'll gain: Large Language Modeling, Generative Model Architectures, Prompt Engineering, Generative AI, Deep Learning, Natural Language Processing, Responsible AI, Application Deployment, Scalability, Operational Efficiency, Machine Learning, Performance Tuning, Systems Integration

    Advanced · Course · 3 - 6 Months

  • C

    Coursera

    Semantic Segmentation with Amazon Sagemaker

    Skills you'll gain: AWS SageMaker, AWS Identity and Access Management (IAM), Image Analysis, Amazon Elastic Compute Cloud, Amazon S3, Applied Machine Learning, Application Deployment, Machine Learning Algorithms, Computer Vision, Deep Learning, Machine Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    94 reviews

    Advanced · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Advanced Creative Thinking and AI: Tools for Success

    Skills you'll gain: Design Thinking, Creative Thinking, Creativity, Brainstorming, Cognitive flexibility, Ideation, Innovation, Artificial Intelligence, Critical Thinking, Sustainable Design, Prototyping

    4.7
    Rating, 4.7 out of 5 stars
    ·
    108 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Foundations of Business Intelligence

    Skills you'll gain: Stakeholder Engagement, Business Intelligence, Data-Driven Decision-Making, Dashboard, Business Analytics, Real Time Data, Data Integration, Data Modeling, Data Analysis, Key Performance Indicators (KPIs), Business Metrics, Business Process, Project Implementation, Data Pipelines

    4.8
    Rating, 4.8 out of 5 stars
    ·
    2K reviews

    Advanced · Course · 1 - 4 Weeks

  • G

    Google Cloud

    Transformer Models and BERT Model

    Skills you'll gain: Large Language Modeling, Natural Language Processing, Generative Model Architectures, Artificial Neural Networks

    4.1
    Rating, 4.1 out of 5 stars
    ·
    124 reviews

    Advanced · Course · 1 - 4 Weeks

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1234…12

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
  • IBM AI Enterprise Workflow: IBM
  • MLOps | Machine Learning Operations: Duke University
  • Advanced Machine Learning on Google Cloud: Google Cloud
  • Generative AI for Mobile App Developers: IBM
  • Decoding Large Language Models: Packt
  • Semantic Segmentation with Amazon Sagemaker: Coursera
  • Advanced Creative Thinking and AI: Tools for Success: Imperial College London

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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