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  • Artificial Intelligence

Results for "artificial intelligence"


  • I

    IBM

    IBM RAG and Agentic AI

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

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    4.6
    Rating, 4.6 out of 5 stars
    ·
    1K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • G

    Google

    Google Advanced Data Analytics

    Skills you'll gain: Interactive Data Visualization, Statistics, Descriptive Statistics, Logistic Regression, Decision Tree Learning, Advanced Analytics, Probability & Statistics, Probability Distribution, Statistical Inference, Applied Machine Learning, Data-Driven Decision-Making, Supervised Learning, Workflow Management, Statistical Methods, Statistical Modeling, Data Cleansing, Data Structures, Interviewing Skills, NumPy, Professional Development

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    4.8
    Rating, 4.8 out of 5 stars
    ·
    12K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • G

    Google

    Google Business Intelligence

    Skills you'll gain: Data Modeling, Stakeholder Engagement, Dashboard, Business Intelligence, Tableau Software, Extract, Transform, Load, Data Warehousing, Database Systems, Interactive Data Visualization, Data Visualization, Data Pipelines, Interviewing Skills, Business Process, Business Analysis, Database Design, Data Mart, Applicant Tracking Systems, Data Analysis, SQL, Stakeholder Communications

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    4.8
    Rating, 4.8 out of 5 stars
    ·
    8.9K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • D

    Duke University

    MLOps | Machine Learning Operations

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

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    4.2
    Rating, 4.2 out of 5 stars
    ·
    622 reviews

    Advanced · Specialization · 3 - 6 Months

  • I

    IBM

    IBM AI Enterprise Workflow

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

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    4.4
    Rating, 4.4 out of 5 stars
    ·
    373 reviews

    Advanced · Specialization · 3 - 6 Months

  • G

    Google Cloud

    Advanced Machine Learning on Google Cloud

    Skills you'll gain: Model Deployment, Model Optimization, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Large Language Modeling, Reinforcement Learning, Model Training, Transfer Learning, Computer Vision, Keras (Neural Network Library), Systems Design, Applied Machine Learning, Image Analysis, AI Personalization, Cloud Deployment, Recurrent Neural Networks (RNNs), Machine Learning

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

    Advanced · Specialization · 3 - 6 Months

  • I

    Imperial College London

    Advanced Creative Thinking and AI: Tools for Success

    Skills you'll gain: Design Thinking, Creative Thinking, Creativity, AI powered creativity, Human Centered Design, Innovation, Artificial Intelligence, Generative AI

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    4.7
    Rating, 4.7 out of 5 stars
    ·
    129 reviews

    Advanced · Course · 1 - 3 Months

  • C

    Corporate Finance Institute

    Practical Data Science for Data Analysts

    Skills you'll gain: Classification Algorithms, Data Preprocessing, Feature Engineering, Data Visualization, Model Evaluation, Data Import/Export, Matplotlib, Exploratory Data Analysis, Data Presentation, Data Science, Plot (Graphics), Regression Analysis, Financial Data, Data Analysis, Business Analytics, Data Cleansing, Machine Learning Algorithms, Correlation Analysis, Advanced Analytics, Predictive Analytics

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    4.8
    Rating, 4.8 out of 5 stars
    ·
    31 reviews

    Advanced · Specialization · 3 - 6 Months

  • C

    Coursera

    Deep Learning with PyTorch : Siamese Network

    Skills you'll gain: Embeddings, PyTorch (Machine Learning Library), Feature Engineering, Artificial Neural Networks, Image Analysis, Deep Learning, Convolutional Neural Networks, Network Model, Model Training, Computer Vision

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    4.7
    Rating, 4.7 out of 5 stars
    ·
    49 reviews

    Advanced · Guided Project · Less Than 2 Hours

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  • U

    University of Michigan

    More Applied Data Science with Python

    Skills you'll gain: Unsupervised Learning, Data Mining, Social Network Analysis, ChatGPT, Embeddings, LLM Application, Applied Machine Learning, Data Quality, Unstructured Data, Anomaly Detection, Machine Learning Methods, Data Science, Machine Learning, Data Preprocessing, Data Transformation, Data Analysis, Social Media Analytics, Data Manipulation, Python Programming, Exploratory Data Analysis

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    Included with Coursera Plus

    4.6
    Rating, 4.6 out of 5 stars
    ·
    21 reviews

    Advanced · Specialization · 3 - 6 Months

  • 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

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    Included with Coursera Plus

    3.7
    Rating, 3.7 out of 5 stars
    ·
    9 reviews

    Advanced · Specialization · 3 - 6 Months

  • I

    IBM

    Generative AI for Mobile App Developers

    Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Generative AI, Data Ethics, Generative AI Agents, AI Personalization, Mobile Development, Software Design Documents, Software Design, Generative Model Architectures, Anthropic Claude, Mobile Development Tools, LLM Application, AI literacy, iOS Development, AI Integrations, Personalized Campaigns, Software Development, Artificial Intelligence and Machine Learning (AI/ML)

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    Included with Coursera Plus

    4.7
    Rating, 4.7 out of 5 stars
    ·
    12K reviews

    Advanced · Specialization · 3 - 6 Months

1234…15

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

  • IBM RAG and Agentic AI: IBM
  • Google Advanced Data Analytics: Google
  • Google Business Intelligence: Google
  • MLOps | Machine Learning Operations: Duke University
  • IBM AI Enterprise Workflow: IBM
  • Advanced Machine Learning on Google Cloud: Google Cloud
  • Advanced Creative Thinking and AI: Tools for Success: Imperial College London
  • Practical Data Science for Data Analysts: Corporate Finance Institute
  • Deep Learning with PyTorch : Siamese Network: Coursera
  • More Applied Data Science with Python: University of Michigan

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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