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    • Ibm Ai

    IBM AI Courses Online

    Explore IBM AI for artificial intelligence applications. Learn to use IBM's AI tools and platforms for machine learning and data analysis.

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    Explore the IBM AI Course Catalog

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Data Wrangling, Data Visualization, SQL, Supervised Learning, Feature Engineering, Plotly, Interactive Data Visualization, Jupyter, Data Literacy, Exploratory Data Analysis, Data Mining, Data Cleansing, Matplotlib, Data Analysis, Unsupervised Learning, Generative AI, Pandas (Python Package), Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      142K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Generative AI for Cybersecurity Professionals

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI, Cyber Threat Intelligence, Security Information and Event Management (SIEM), Threat Modeling, OpenAI, Threat Detection, Cybersecurity, Incident Response, Malware Protection, Large Language Modeling, Artificial Intelligence, Natural Language Processing, Program Development, Anomaly Detection, Vulnerability Management, Image Analysis, Content Creation, Virtual Environment

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.3K reviews

      Intermediate · Specialization · 1 - 3 Months

    • I

      IBM

      IBM Product Manager

      Skills you'll gain: Usability Testing, New Product Development, Product Management, Product Lifecycle Management, Agile Software Development, Product Development, Innovation, Product Roadmaps, Agile Methodology, Kanban Principles, Product Planning, Product Strategy, Product Testing, Project Management Life Cycle, Agile Project Management, User Story, Stakeholder Engagement, Sprint Retrospectives, Stakeholder Management, Competitive Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Generative AI Engineering with LLMs

      Skills you'll gain: Prompt Engineering, Large Language Modeling, Generative AI, Natural Language Processing, Generative AI Agents, PyTorch (Machine Learning Library), Text Mining, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Deep Learning, Application Development, Artificial Intelligence, Feature Engineering, Document Management, Machine Learning Methods, Jupyter, Data Processing, Applied Machine Learning, Performance Tuning, Application Frameworks

      4.5
      Rating, 4.5 out of 5 stars
      ·
      397 reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Generative AI Fundamentals

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, OpenAI, Data Ethics, Large Language Modeling, Leadership and Management, Business Leadership, Strategic Leadership, Business Ethics, Legal Risk, IBM Cloud, Google Cloud Platform, Artificial Intelligence, Program Development, Artificial Neural Networks, Business Development, Deep Learning, Content Creation, Business Transformation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New
      M

      Microsoft

      Microsoft AI & ML Engineering

      Skills you'll gain: Unsupervised Learning, Generative AI, Large Language Modeling, Data Management, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Infrastructure Architecture, Cloud Infrastructure, Generative AI Agents, Applied Machine Learning, Reinforcement Learning, Data Ethics, Prompt Engineering, Data Processing, Artificial Intelligence, Application Deployment

      4.6
      Rating, 4.6 out of 5 stars
      ·
      127 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM AI Enterprise Workflow

      Skills you'll gain: Feature Engineering, Data Visualization, Data Ethics, Exploratory Data Analysis, Unsupervised Learning, Data Presentation, Tensorflow, Application Deployment, Dimensionality Reduction, MLOps (Machine Learning Operations), Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Dashboard, Unit Testing, Artificial Neural Networks, Data Science, Artificial Intelligence

      4.3
      Rating, 4.3 out of 5 stars
      ·
      319 reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: New
      New
      I

      IBM

      IBM Deep Learning with PyTorch, Keras and Tensorflow

      Skills you'll gain: PyTorch (Machine Learning Library), Keras (Neural Network Library), Deep Learning, Reinforcement Learning, Unsupervised Learning, Image Analysis, Data Manipulation, Tensorflow, Verification And Validation, Generative AI, Artificial Neural Networks, Data Processing, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Artificial Intelligence, Scientific Visualization, Time Series Analysis and Forecasting, Predictive Modeling, Natural Language Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • M

      Microsoft

      Microsoft Azure AI Fundamentals AI-900 Exam Prep

      Skills you'll gain: Anomaly Detection, Image Analysis, Text Mining, Unsupervised Learning, Computer Vision, Artificial Intelligence, Natural Language Processing, Microsoft Azure, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data Ethics, Machine Learning, Large Language Modeling, Regression Analysis, Predictive Modeling, Machine Learning Methods, Statistical Machine Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Automation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Generative AI for Software Developers

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI, Large Language Modeling, OpenAI, CI/CD, Software Development, Software Development Life Cycle, DevSecOps, Data Ethics, Natural Language Processing, Prototyping, Software Architecture, Artificial Intelligence, Program Development, Code Review, Software Testing, Software Design Patterns, Image Analysis, Content Creation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.3K reviews

      Intermediate · Specialization · 1 - 3 Months

    • I

      IBM

      Generative AI for Data Analysts

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, Data Storytelling, OpenAI, Analytics, Data Analysis, Artificial Intelligence and Machine Learning (AI/ML), Dashboard, Large Language Modeling, Data Ethics, Artificial Intelligence, Program Development, Data Visualization Software, SQL, Python Programming, Query Languages, Image Analysis, Content Creation, Virtual Environment

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.3K reviews

      Intermediate · Specialization · 1 - 3 Months

    • I

      IBM

      IBM Back-End Development

      Skills you'll gain: Istio, Open Web Application Security Project (OWASP), Software Development Life Cycle, Linux Commands, Kubernetes, Unit Testing, Object-Relational Mapping, Application Deployment, NoSQL, Bash (Scripting Language), MongoDB, Shell Script, Cloud-Native Computing, OpenShift, Git (Version Control System), Cloud Applications, Containerization, GitHub, Jupyter, Grafana

      4.6
      Rating, 4.6 out of 5 stars
      ·
      48K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    IBM AI learners also search

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    1234…186

    In summary, here are 10 of our most popular ibm ai courses

    • IBM Data Science: IBM
    • IBM Generative AI for Cybersecurity Professionals: IBM
    • IBM Product Manager: IBM
    • Generative AI Engineering with LLMs: IBM
    • Generative AI Fundamentals: IBM
    • Microsoft AI & ML Engineering: Microsoft
    • IBM AI Enterprise Workflow: IBM
    • IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
    • Microsoft Azure AI Fundamentals AI-900 Exam Prep: Microsoft
    • Generative AI for Software Developers: IBM

    Frequently Asked Questions about Ibm Ai

    IBM AI refers to artificial intelligence technologies developed by IBM. IBM has been at the forefront of AI research and development for many years and has created various AI-powered solutions and tools. These solutions use machine learning, deep learning, natural language processing, and other AI techniques to analyze and interpret data, make predictions, automate processes, and assist in decision-making. IBM Ai is used in various industries, including healthcare, finance, retail, and manufacturing, to enhance operational efficiency, improve customer experiences, drive innovation, and solve complex problems.‎

    To excel in IBM AI, you should focus on the following skills:

    1. Artificial Intelligence (AI): Gain a comprehensive understanding of AI concepts, including machine learning, deep learning, natural language processing, and computer vision.

    2. Data Science: Acquire skills in data analysis, statistical modeling, and data visualization. Familiarize yourself with tools like Python, R, SQL, and Apache Spark for data manipulation and predictive modeling.

    3. Machine Learning: Develop expertise in building and implementing machine learning algorithms for tasks such as classification, regression, and clustering. Gain hands-on experience with popular ML frameworks like TensorFlow or PyTorch.

    4. Programming: Master a programming language like Python or Java to effectively work with IBM Ai technologies and frameworks. Learn programming constructs, data structures, and algorithms to write efficient and scalable code.

    5. Cloud Computing: Familiarize yourself with IBM Cloud and its AI services like Watson AI, Watson Machine Learning, and IBM Watson Studio. Gain knowledge of deploying and managing AI models on cloud platforms.

    6. Natural Language Processing (NLP): Understand how to process and analyze natural language using techniques like sentiment analysis, text classification, and named entity recognition. Learn NLP libraries and frameworks like NLTK, SpaCy, or IBM Watson Natural Language Understanding.

    7. Big Data Technologies: Acquaint yourself with tools like Apache Hadoop and Apache Spark for managing and analyzing large-scale datasets. Learn about distributed computing and parallel processing for efficient data processing.

    8. Cognitive Computing: Study the principles behind cognitive computing systems and how they mimic human cognition. Gain knowledge of IBM Watson technologies and explore their various cognitive services.

    9. Problem-Solving: Enhance your problem-solving capabilities by practicing real-world AI problems and challenges. Understand how to approach complex problems, break them down, and apply AI techniques to find effective solutions.

    10. Communication and Collaboration: Develop strong communication skills to effectively convey AI solutions and collaborate with cross-functional teams. Learn to present complex AI concepts in a simplified manner to non-technical stakeholders.

    Remember, constantly staying updated with the latest advancements in AI and regularly practicing your skills through projects and real-world applications will further enhance your expertise in IBM AI.‎

    With IBM AI skills, you can pursue various job opportunities in the field of artificial intelligence. Some of the potential roles you can consider are:

    1. AI Engineer/Developer: As an AI engineer, you would be responsible for designing, developing, and implementing AI models and algorithms using IBM AI technologies. You would collaborate with software engineers and data scientists to create AI applications.

    2. Machine Learning Engineer: With IBM AI skills, you can work as a machine learning engineer to develop and deploy machine learning models using IBM Watson and other AI frameworks. You would train models, optimize algorithms, and work on data preprocessing tasks.

    3. Data Scientist: IBM AI skills can also enable you to work as a data scientist, leveraging AI technologies to analyze large datasets, extract insights, and drive data-driven decision-making. You would use IBM AI tools for data exploration, visualization, and predictive modeling.

    4. AI Researcher: With IBM AI skills, you can contribute to the academic or industrial research on artificial intelligence. Working as an AI researcher, you would explore new AI algorithms, models, and techniques, and push the boundaries of AI technologies.

    5. AI Consultant: As an AI consultant, you can provide guidance and expertise to businesses or organizations looking to adopt AI solutions. With IBM AI skills, you would assess their requirements, design AI strategies, and help implement AI applications using IBM tools and platforms.

    6. AI Product Manager: IBM AI skills can also lead you to a role as an AI product manager. In this position, you would be responsible for identifying market opportunities, evaluating customer needs, and managing the development and launch of AI-powered products and solutions.

    These are just a few examples of the diverse career paths you can pursue with IBM AI skills. The field of AI is rapidly growing, and acquiring these skills can open doors to numerous exciting job opportunities.‎

    People who are interested in artificial intelligence, have a strong background in computer science or related fields, and are willing to learn and adapt to new technologies. Additionally, individuals who have a passion for problem-solving, critical thinking, and data analysis would be well-suited for studying IBM AI.‎

    Here are some topics that you can study related to IBM AI:

    1. Artificial Intelligence: Start by understanding the basics of artificial intelligence, its history, and its various applications.

    2. Machine Learning: Dive deeper into machine learning algorithms, which are the backbone of AI technologies. Learn about supervised and unsupervised learning, decision trees, neural networks, and more.

    3. Deep Learning: Explore the field of deep learning, a subset of machine learning that focuses on neural networks with multiple layers. Discover how deep learning algorithms power technologies like image recognition, natural language processing, and speech recognition.

    4. Natural Language Processing (NLP): Understand how AI enables computers to understand, interpret, and respond to human language. Study topics such as sentiment analysis, language generation, text mining, and chatbots.

    5. Computer Vision: Learn about computer vision, which involves training computers to interpret and understand visual data. Delve into topics like image classification, object detection, image segmentation, and image generation.

    6. Data Science: Gain expertise in data science, a vital skill when working with AI technologies. Learn about data preprocessing, feature engineering, statistical analysis, and data visualization.

    7. IBM Watson: Explore IBM Watson, a comprehensive suite of AI tools and services. Study how Watson's various components, like Watson Assistant or Watson Discovery, can be utilized in different domains such as healthcare, finance, or customer service.

    8. AI Ethics: Understand the ethical implications and considerations surrounding the development and deployment of AI technologies. Study topics like bias, transparency, privacy, and the responsible use of AI.

    Remember, these are just a few of the many topics you can study related to IBM AI. Depending on your interests and goals, there may be even more specific areas to explore within the broad field of artificial intelligence.‎

    Online IBM Ai courses offer a convenient and flexible way to enhance your knowledge or learn new IBM Ai refers to artificial intelligence technologies developed by IBM. IBM has been at the forefront of AI research and development for many years and has created various AI-powered solutions and tools. These solutions use machine learning, deep learning, natural language processing, and other AI techniques to analyze and interpret data, make predictions, automate processes, and assist in decision-making. IBM Ai is used in various industries, including healthcare, finance, retail, and manufacturing, to enhance operational efficiency, improve customer experiences, drive innovation, and solve complex problems. skills. Choose from a wide range of IBM Ai courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in IBM AI, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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