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Generative AI courses

659 Courses

California Institute of Technology Codecademy

Language Models in Python: Generative Chatbots

Embark on a journey to master the art of crafting AI chatbots with our advanced course, "Language Models in Python: Generative Chatbots". This comprehensive course is designed to equip you with the skills to create sophisticated generative chatbots using the power of deep learning and Python's seq2seq models. By enrolling, you'll dive deep into the.
provider Codecademy
pricing Free Trial Available
duration 1 hour
sessions On-Demand
California Institute of Technology Coursera

Data Visualization with OpenAI API: Generate code with GenAI

Title: Data Visualization with OpenAI API: Generate code with GenAI Description: Dive into the world of generative AI with our project-based course on Data Visualization with the OpenAI API. Over a span of 2 hours, you'll embark on a journey to master the art of generating Python code for data analysis and visualization using GPT-4. This course is.
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provider Coursera
pricing Paid Course
duration 1-2 hours
sessions On-Demand
California Institute of Technology Coursera

Google Bard for Beginners: Text Generation with Prompts

Title: Google Bard for Beginners: Text Generation with Prompts Description: Delve into the world of generative AI with our 1-hour project-based course on text generation, utilizing Google Bard, MakerSuite, and the PaLM API within Google Colab. This course is designed to introduce you to the integration of PaLM with Bard and MakerSuite through a ser.
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provider Coursera
pricing Paid Course
duration 1-2 hours
sessions On-Demand
California Institute of Technology Coursera

Marketing with Generative AI: Create Images & Videos

Embark on a fascinating journey to amplify your marketing efforts with the power of Generative AI in this captivating 1-hour project-based course, proudly offered by Coursera. Dive into the realm of creating stunning, eye-catching images and captivating videos tailored for marketing, using advanced AI tools. Your adventure begins with generating me.
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provider Coursera
pricing Paid Course
duration 2-3 hours
sessions On-Demand
California Institute of Technology Coursera

Landing.AI for Beginners: Build Data Visualization AI Models

Embark on a journey into the realms of Computer Vision and Generative AI with the "Landing.AI for Beginners: Build Data Visualization AI Models" course. This 1-hour project-based course, available on Coursera, is your gateway to mastering the innovative LandingLens platform. You'll begin with the basics of visual prompting and swiftly move to proje.
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provider Coursera
pricing Paid Course
duration 1-2 hours
sessions On-Demand
California Institute of Technology Pluralsight

Using Generative AI to Troubleshoot Microsoft Windows

Explore the cutting-edge approach to solving Windows operating system issues with our comprehensive course on Using Generative AI to Troubleshoot Microsoft Windows, offered by Pluralsight. Dive deep into the world of generative AI technologies such as ChatGPT and discover innovative methods for addressing both Windows Server and Windows client prob.
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provider Pluralsight
pricing Free Trial Available
duration 1 hour 26 minutes
sessions On-Demand
California Institute of Technology Pluralsight

Generative AI Techniques for Cyber Defense

Explore the cutting-edge application of generative AI in the realm of cybersecurity with our comprehensive course, "Generative AI Techniques for Cyber Defense," offered exclusively through Pluralsight. As the digital landscape evolves, so do the threats that challenge the security of our information systems. This course is meticulously designed to.
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provider Pluralsight
pricing Free Trial Available
duration 42 minutes
sessions On-Demand
California Institute of Technology Pluralsight

Exploring Generative AI Models and Architecture

Delve into the world of Generative AI models and architecture with this comprehensive course offered by Pluralsight. Whether you're intrigued by the creation of new content ranging from images to text or eager to apply these innovations to solve real-world challenges, this course is designed for you. Exploring Generative AI Models and Architecture.
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provider Pluralsight
pricing Free Trial Available
duration 48 minutes
sessions On-Demand
California Institute of Technology Pluralsight

Developing Generative AI Applications with Python and Open AI

Embark on a transformative journey through the developing world of Generative AI with our comprehensive course titled "Developing Generative AI Applications with Python and OpenAI (ChatGPT)". This groundbreaking course is designed to equip learners with the skills to create generative AI applications using the renowned OpenAI API and Python, markin.
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provider Pluralsight
pricing Free Trial Available
duration 2 hours 49 minutes
sessions On-Demand
California Institute of Technology Udemy

ChatGPT Complete Course - Prompt Engineering for ChatGPT

``` Explore the World of ChatGPT with Udemy's Comprehensive Course: Dive into the exciting realm of ChatGPT and prompt engineering with this meticulously designed course. Created for enthusiasts and professionals alike, this program covers a wide array of topics, including ChatGPT basics, the intricacies of the ChatGPT App Store, and advanced techn.
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provider Udemy
pricing Paid Course
duration 5 hours 22 minutes
sessions On-Demand

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!