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Generative AI courses

1093 Courses

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California Institute of Technology edX

Use AI for Everyday Tasks

Use AI for Everyday Tasks offers a comprehensive introduction to utilizing AI for enhancing daily workflows. The course begins with an exploration of core generative AI concepts, including Language Learning Models (LLMs) and Natural Language Processing (NLPs), and their practical applications, from smart assistants to AI agents. With a focus on res.
provider edX
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California Institute of Technology Coursera

GenAI for Sales Managers: Data-Driven Sales Forecasting

Welcome to the course "GenAI for Sales Managers: Boosting Sales with GenAI," designed to empower sales professionals in incorporating Generative AI into their daily operations. This course covers everything from sales forecasting and customer engagement to pipeline management, demonstrating the effectiveness of GenAI tools like ChatGPT and Cla.
provider Coursera
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California Institute of Technology Coursera

GenAI for Risk Managers: Advanced Risk Analysis Techniques

Discover how Generative AI can elevate your risk analysis techniques through our specialized course. This program provides an in-depth exploration of how AI enhances risk detection, automates monitoring, and improves decision-making. Engage with real-world case studies and hands-on projects designed to equip you with AI-driven strategies tail.
provider Coursera
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California Institute of Technology Coursera

GenAI for Sales Reps: Streamlining Lead Qualification

Embark on a transformative journey with our course, "GenAI for Sales Reps: Streamlining Lead Qualification." Designed specifically for sales professionals, this course enables you to leverage Generative AI for automating and enhancing lead qualification processes. Begin by exploring the fundamentals of GenAI in sales and learn how AI can rev.
provider Coursera
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California Institute of Technology Coursera

GenAI for Onboarding: Automating Employee Journeys

In this course, discover how to use Generative AI to automate the employee onboarding journey, enhancing the overall experience. Tailored for HR professionals and business leaders, the curriculum delves into practical AI applications, offering hands-on experience with automation tools while addressing ethical considerations in AI-driven HR s.
provider Coursera
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California Institute of Technology Coursera

GenAI for Healthcare: Transforming Personalized Care

Join the journey to transform personalized care with our comprehensive course on Generative AI in healthcare. Discover how AI enhances diagnostics, streamlines patient care, and optimizes clinical workflows. Learn to spot AI opportunities, implement effective strategies, and maintain ethical and compliant AI adoption in medical practice. Del.
provider Coursera
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California Institute of Technology Coursera

GenAI for Paralegals: Streamlining Legal Drafting

Discover how Generative AI is revolutionizing the paralegal field by enhancing efficiency in legal research, document preparation, and workflow automation. This comprehensive course is designed to provide both the knowledge and practical skills necessary to harness AI for improved legal services. The course includes practical applications an.
provider Coursera
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California Institute of Technology Coursera

GenAI for Performance Reviews: Streamline Feedback Processes

Generative AI (GenAI) is revolutionizing the way performance reviews are conducted, offering a transformative approach to feedback processes. Organizations utilizing AI in talent management experience less bias and quicker employee growth. If you're not harnessing this innovative technology, you're potentially overlooking significant team en.
provider Coursera
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California Institute of Technology Coursera

GenAI for Call Centers: AI-Driven Customer Success

Join our transformative course, "GenAI for Call Centers: AI-Driven Customer Success" to explore how AI can reshape your customer interaction strategies. Dive deep into practical tools like ChatGPT’s Canvas Mode, Custom GPTs, and Voice Mode designed to revolutionize call center workflows and efficiency. This course is tailor-made for custome.
provider Coursera
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California Institute of Technology Coursera

GenAI for Azure: AI-Powered Cloud Optimization Strategies

Enroll in our exciting course on AI-Powered Cloud Optimization Strategies to explore how Generative AI is redefining cloud management. Designed for Cloud Solutions Architects, DevOps Professionals, and AI Enthusiasts, this course delivers hands-on experience with Azure OpenAI, Microsoft Copilot, and other cutting-edge Azure services. Learn to au.
provider Coursera

A generative ai course is a fast-growing field of machine learning that can create new content, translate languages, write different types of creative content, and answer your questions in an informative way. It has great potential to revolutionize the way we create and use products.

A generative ai course refers to any artificial intelligence model that generates new data, information, or documents.

For example, many companies record their meetings, both live and virtual. Here are a few ways generative AI could transform these recordings:

And this is only a small part of all processes.

Generative AI Model Examples

There are a number of products using generative ai courses already available on the market – we'll give you a few examples below. The underlying principle of the generative ai courses at AI Eeducation varies depending on the specific model or algorithm used, but some common approaches include:

  1. Variational Autoencoders (VAEs) are a type of generative model that learns to encode input data into a latent space and then decode it back into the original data. The "variational" part of the name refers to the probabilistic nature of the latent space, allowing the model to generate a variety of outputs.

  2. Generative Adversarial Networks (GaN): GaNs consist of two neural networks, a generator and a discriminator, that are trained simultaneously through adversarial learning. The generator creates new data, and the discriminator evaluates how well the generated data matches the real data. The competition between the two networks causes the generator to improve over time in producing realistic outputs.

  3. Recurrent Neural Networks (RNNS) and Long Short-Term Memory (LSTM): These types of neural networks are often used to generate sequences such as text or music. RNNS and LSTM have memory that allows them to process a series of events over time, making them suitable for tasks where the order of elements is important.

  4. Transformer models: Transformer models, especially those with attention mechanisms, are very successful in various generative tasks. They can remember long-term dependencies and relationships in data, making them effective for tasks such as language translation and text generation.

  5. Autoencoders: Autoencoders consist of an encoder and a decoder, and they are trained to reconstruct the input data. Although they are primarily used for learning to represent and compress data, variations such as denoising autoencoders (e.g. in images) can be used for generative tasks.

An ai generative course involves feeding a model a large data set and optimizing its parameters to minimize the difference between the generated output and the real information. A model's ability to produce realistic and rich content depends on the complexity of its architecture, the quality and quantity of training data, and the optimization techniques used during training!