Generative AI
- Time Duration: 2-3 Months
- Skill Level : Advance Course
- Certificate : Yes
COURSE DESCRIPTION:
Explore the creative side of artificial intelligence with the best Generative AI course at Unividya. This hands-on program takes you deep into the world of machine learning models that can create—from realistic images and synthesized text to music, art, and even video. You’ll learn powerful tools like GANs, VAEs, and transformers, and work with frameworks like TensorFlow and PyTorch. By the end, you’ll have the skills to build your own generative models and apply them to real-world innovation.
LEARNING OUTCOMES:
Understand the basics of generative models like GANs, VAEs & transformers
Build and train AI that generates text, images, audio & more
Work with TensorFlow and PyTorch to implement real generative projects
Apply these models to practical use cases like image generation, text-to-image, and style transfer
Who Can Join?
The Generative AI course at Unividya is perfect for students, developers, designers, and AI enthusiasts looking to explore the creative side of machine learning.
If you have a basic understanding of Python and deep learning, and a curiosity to build AI that can generate—this course is for you. No advanced experience required—just imagination and a willingness to learn.
What You’ll Learn!
In the Generative AI course at Unividya, you’ll learn through real projects:
Explore how GANs, VAEs, and transformer models work
Build models that create realistic images, text, music, and more
Use TensorFlow and PyTorch for hands-on development
Apply generative techniques in creative fields like design, content creation, and media
Understand the ethics and limitations of AI-generated content
- Time Duration: 2-3 Months
- Skill Level : Advance Course
- Certificate : Yes
COURSE DESCRIPTION
Generative AI courses introduce key concepts and techniques for creating new data using machine learning and neural networks. Covering topics like GANs, VAEs, and transformer models, students learn to generate images, text, music, and videos using frameworks like TensorFlow and PyTorch. Practical projects and exercises help apply these skills to real-world scenarios. By course end, learners gain a solid understanding of generative models, their applications, and ethical considerations, preparing them for innovation in AI.
LEARNING OUTCOMES
- Understand the foundational principles of generative AI, including models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders).
- Gain proficiency in building and training generative models to create realistic synthetic data, images, audio, and text.
- Develop skills in deep learning frameworks such as TensorFlow and PyTorch for implementing and optimizing generative AI models.
- Learn to apply generative AI techniques in real-world applications such as image generation, text synthesis, and style transfer.
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast