Are you looking for the Best Generative AI Courses Online & Certifications?… If yes, then this article is for you. In this article, you will find the Best Generative AI Courses Online & Certifications.
Now, without further ado, let’s get started-
Best Generative AI Courses Online & Certifications
1. Introduction to Generative Adversarial Networks– Udacity
Time to Complete-1 Month
Level-Intermediate
Rating-NA
In the Advanced Generative Adversarial Networks (GANs) course, you will learn cutting-edge techniques to create realistic images and perform image-to-image translation tasks.
Through hands-on exercises, you’ll gain practical skills in building and training GAN models using various layer types. The course covers modern GAN variants like Wasserstein loss and adaptive instance normalization (StyleGAN) to enhance stability and generate high-quality results.
The engaging course project on face generation allows you to apply your knowledge and experiment with different loss functions. With knowledgeable instructors and a supportive learning community, this course provides a comprehensive learning experience in the world of advanced GANs.
Extra Benefits-
- You will get a chance to work on real-world projects from Industry Experts.
- You will get Technical mentor support.
- Along with this, you will get a personal coach & career services.
Who Should Enroll?
- Those who already have knowledge in Convolutional neural networks, Recurrent neural networks, Intermediate Python, PyTorch, Basic calculus, Linear algebra, Basic probability, and Jupyter notebooks.
Interested to Enroll?
If yes, then start learning here- Introduction to Generative Adversarial Networks
2. Generative Adversarial Networks (GANs) Specialization– Coursera
Time to Complete- 3 months ( If you spend 8 hours per week)
Level-Intermediate
Rating- 4.7/5
A generative Adversarial Network (GAN) is a powerful algorithm of Deep Learning. Generative Adversarial Network is used in Image Generation, Video Generation, and Audio Generation. In short, GAN is a Robot Artist, who can create any kind of art perfectly.
And in this Generative Adversarial Networks (GANs) Specialization, you will learn how to build basic GANs using PyTorch and advanced DCGANs using convolutional layers.
You will use GANs for data augmentation and privacy preservation, survey GANs applications, and examine and build Pix2Pix and CycleGAN for image translation.
There are 3 courses in this Specialization program where you will gain hands-on experience in GANs. Now, let’s see all the 3 courses of this Specialization Program-
Courses Include-
- Build Basic Generative Adversarial Networks (GANs)
- Build Better Generative Adversarial Networks (GANs)
- Apply Generative Adversarial Networks (GANs)
Extra Benefits-
- You will get a Shareable Certificate and Course Certificates upon completion.
- Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.
Who Should Enroll?
- Those who have a working knowledge of AI, deep learning, and convolutional neural networks. And have intermediate Python skills plus familiarity with any deep learning framework (TensorFlow, Keras, or PyTorch).
- You should also be proficient in basic calculus, linear algebra, and statistics.
Interested to Enroll?
If yes, then check it out here–Generative Adversarial Networks (GANs) Specialization
3. Generative Deep Learning with TensorFlow– Coursera
Time to Complete-16 hours
Level-Intermediate
Rating-4.8/5
This course is all about learning exciting things in deep learning. You’ll start by discovering how to combine the content from one image with the style of another image, making really cool visuals.
Then, you’ll learn about AutoEncoders, which are models that can remove noise from pictures, and understand different types of AutoEncoders.
Next up are Variational AutoEncoders (VAEs), where you’ll create completely new things, like anime faces, and compare them to pictures you already have.
Lastly, you’ll dive into Generative Adversarial Networks (GANs), understanding how they work and building your own model to make realistic faces. By the end of the course, you’ll be able to use these techniques to create amazing visual outputs using deep learning.
Extra Benefits-
- You will get a Course Certificate upon completion.
- Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.
Who Should Enroll?
- Those who have a previous understanding of Python, TensorFlow, and deep learning.
Interested to Enroll?
If yes, then start learning here- Generative Deep Learning with TensorFlow
4. Deep Learning– Udacity
Time to Complete- 4 months (If you spend 12 hours per week)
Level-Advanced
Rating- 4.7/5
This Nano-Degree program from Udacity will give you a complete understanding of Deep Learning. In this program, you will build convolutional networks for image recognition, recurrent networks for sequence generation, and generative adversarial networks for image generation.
You will also learn how to implement gradient descent and backpropagation using NumPy matrix multiplication, how to prevent overfitting of training data and minimize the error of a network, how to define and train neural networks for sentiment analysis, etc.
This Nanodegree program will also teach you how to use Amazon’s GPUs to train neural networks faster. The instructor Sebastian Thrun will explain about detecting skin cancer with CNN. There are 5 courses in this Nanodegree program. Now let’s see the details of the courses-
Courses Include-
- Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Generative Adversarial Networks
- Updating a Model
Extra Benefits-
- You will get a chance to work on Real-world projects.
- You will get Technical mentor support.
- Along with that, you will get Resume services, GitHub review, and LinkedIn profile review.
Who Should Enroll?
- Those who have intermediate-level Python programming knowledge and experience with NumPy and pandas.
- And those who have math knowledge, including- algebra and some calculus.
Interested to Enroll?
If yes, then check it out here– Deep Learning
5. Introduction to Generative AI with Google Cloud– Udacity FREE Course
Time to Complete-1 hour
Level-Beginner
Rating-NA
This introductory course on Generative AI with Google Cloud is designed for individuals who are new to the field. Throughout the course, you will gain a clear understanding of Generative AI, its functionalities, and how it differs from traditional machine learning methods.
Furthermore, you will learn how to leverage Google Cloud tools to develop your own Generative AI applications. The course is estimated to be completed in less than an hour and covers essential topics such as defining Generative AI, explaining its working principles, exploring different model types, and discussing real-world applications.
By the end of the course, you will have the knowledge and skills to embark on your own Generative AI projects using Google Cloud resources.
Who Should Enroll?
- Those who are beginners.
Interested to Enroll?
If yes, then start learning here- Introduction to Generative AI with Google Cloud
6. AWS Machine Learning Foundations Course– Udacity FREE Course
Time to Complete-2 Months
Level-Intermediate
Rating-NA
This course covers the basics of machine learning, using AWS services, software engineering practices, and object-oriented programming. It’s designed to be easy to understand.
You will learn about different types of machine learning, like supervised and unsupervised learning. You’ll also explore algorithms such as linear regression and logistic regression and how to measure the performance of models.
In addition, the course introduces AWS machine learning services and explains computer vision basics. It even touches on reinforcement learning and generative AI.
The course emphasizes good coding practices, like writing clean and efficient code. You’ll learn about refactoring, version control, and essential testing techniques. It also provides an introduction to object-oriented programming using Python.
Who Should Enroll?
- Those who have basic mathematical concepts such as calculation, average, variance, and beginning-level Python programming.
Interested to Enroll?
If yes, then start learning here- AWS Machine Learning Foundations Course
7. Master Generative AI: Automate Content Effortlessly with AI– Udemy
Time to Complete-8.5 hours
Level-Beginner
Rating-4.1/5
In this course, you will learn effective techniques for text-to-text and text-to-image generation. Additionally, you’ll discover AI tools such as ChatGPT, DALLE-2, Stable Diffusion, and others to streamline your content creation process.
This course goes beyond technical aspects, offering insights into the latest concepts and news in Generative AI. You’ll gain knowledge about GANs, GAI, LMMs, Transformers, and AI content generation, ensuring a comprehensive understanding of the field.
Extra Benefits-
- You will get a Certificate of completion and 3 articles.
Who Should Enroll?
- Those who are a beginner.
Interested to Enroll?
If yes, then check it out here– Master Generative AI: Automate Content Effortlessly with AI
8. Deep Generative Models– Udemy
Time to Complete-4.5 hours
Level-Beginner to Intermediate
Rating-4.5/5
In this course, you will delve into every aspect of generative models, gaining a comprehensive understanding of their mechanics and capabilities. The course covers various types of generative models, ensuring a well-rounded knowledge base.
You will start by exploring autoregressive (AR) models in detail, learning how to write and train them from scratch using Python. The course provides a comprehensive understanding of the principles and intricacies involved.
Next, you will dive into variational autoencoder (VAE) models, gaining insights into their principles and coding them in Python. This section equips you with the skills to train VAE models effectively.
The course also focuses on Generative Adversarial Networks (GANs), providing a deep understanding of their principles and specifics. You will learn how to code and train GANs in Python, enabling you to create realistic and diverse generated content.
Additionally, you will familiarize yourself with Normalizing Flows models, and understand their fundamental principles. The course covers diffusion models, including DALL-E2, Imagen, and Stable diffusion, teaching you how to code and train them in Python.
Extra Benefits-
- You will get a Certificate of completion and 4 downloadable resources.
Who Should Enroll?
- Those who have a basic knowledge of mathematics, statistics, and neural networks.
Interested to Enroll?
If yes, then check it out here– Deep Generative Models
And here the list of “Best Generative AI Courses Online & Certifications” ends.
Conclusion
In this article, I tried to cover the 8 Best Generative AI Courses Online & Certifications. If you have any doubts or questions regarding “Best Generative AI Courses Online“, feel free to ask me in the comment section.
All the Best!
Enjoy Learning!
NOTE- Some of the links in the post are Affiliate Links. This means if you click on the link and purchase the course, I will receive an affiliate commission at no extra cost to you😊.
