SkillFloor’s Generative AI course provides a thorough, hands-on learning experience, combining theoretical knowledge with practical applications. Designed for individuals eager to explore the creative potential of artificial intelligence, this course covers a wide range of generative models, including Generative Adversarial Networks (GANs), Transformers, and Diffusion Models. Students will delve into the inner workings of these models, understanding how they can be used to generate high-quality text, images, audio, and more. The course starts with the fundamentals of machine learning, gradually progressing to advanced techniques, ensuring learners develop a deep understanding of Generative AI. This progression makes the course suitable for both beginners and those with some prior experience in AI or machine learning.
Throughout the course, students will engage in practical exercises and projects to reinforce their learning. These projects are tailored to replicate real-world applications of Generative AI, such as AI art creation, chatbot development, personalized content generation, and synthetic data creation. By working on these projects, students will learn how to fine-tune models, optimize results, and address common challenges such as model instability and bias. SkillFloor’s emphasis on project-based learning ensures that students not only gain theoretical insights but also develop the technical skills required to apply them in professional settings.
₹60,000
Explore Generative Models – Dive deep into the fundamentals of Generative Adversarial Networks (GANs), Transformers, and Diffusion Models, understanding how these models generate creative outputs such as images, text, and more.
Practical Learning – Engage in hands-on projects that allow you to apply the theory learned in class to real-world scenarios, including building AI-driven art, chatbots, and content generators.
Industry-Standard Tools – Master the use of TensorFlow, PyTorch, and Hugging Face, three of the most widely-used platforms in the AI industry, to build and deploy your models.
Text, Image, and Content Generation – Learn how to create high-quality text (e.g., articles, stories), images (e.g., artwork, photographs), and other forms of content using generative models.
AI Ethics Awareness – Gain insights into the ethical considerations of using AI, addressing issues like bias, fairness, and the impact of generative AI on society and industries.
Real-World Use Cases – Apply Generative AI to solve problems across various industries, such as marketing, healthcare, entertainment, and media.
Customizable Projects – Learn how to fine-tune and customize AI models to generate unique outputs based on specific requirements or creative goals.
Collaboration Opportunities – Work with fellow learners in team-based projects, gaining valuable collaboration experience while sharing ideas and knowledge.
Expert Mentorship – Receive ongoing guidance from experienced AI practitioners and mentors who provide support and share industry insights throughout the course.
AI Portfolio Development – Build a strong portfolio showcasing your projects, demonstrating your ability to generate high-quality, innovative AI solutions for potential employers.
Beginner to Advanced Learning – Whether you're new to AI or have some experience, this course is designed to take you from the basics to advanced generative AI concepts, ensuring a comprehensive understanding.
Real-World Applications – Learn how to apply generative AI to real-world problems, from creating marketing materials to generating personalized content for clients in various sectors.
Industry-Relevant Tools – Master cutting-edge tools like TensorFlow, PyTorch, and Hugging Face, which are used by AI professionals and tech companies to build AI models and solutions.
Interactive Projects – Benefit from hands-on projects that simulate actual industry challenges, where you will generate text, images, and even full AI applications.
Strong Career Prospects – The demand for Generative AI professionals is growing rapidly across industries, from creative sectors to technology and business. Completing this course opens up a wide range of career opportunities.
Expert Guidance – Receive mentorship from industry professionals and AI experts who will help you navigate complex topics and provide practical insights, helping you grow your AI skills.
Work on Real Problems – Solve practical problems using Generative AI, such as building chatbots for customer service, creating digital art, or developing AI-powered content generators.
Ethical AI Focus – Develop a strong understanding of the ethical implications of working with AI, including issues of privacy, bias, and fairness in model training and deployment.
Certificate of Completion – Upon finishing the course, earn a SkillFloor certification, which can add credibility to your resume and help you stand out in the AI job market.
Flexible Learning – Enjoy the freedom to learn at your own pace with online access to course materials, allowing you to study according to your schedule without compromising on the quality of the content.
What is Generative AI? – Overview with simple examples like ChatGPT and DALL-E.
Tools Setup – Install and explore TensorFlow and Hugging Face.
Practical: Generate text or images using pre-trained AI models.
Applications – Examples in text, image, and video generation.
Discussion: Ethical use of generative AI (bias and deepfakes).
Neural Networks Basics – Simple explanation with diagrams.
Practical: Build and train a basic neural network (e.g., classify handwritten digits).
Training Data – How to prepare and preprocess datasets.
Pre-trained Models – Introduction to using models like GPT or MobileNet.
Practical: Fine-tune a pre-trained model for a simple task.
What are GANs? – Simple explanation of Generators and Discriminators.
Practical: Build a basic GAN to generate simple images.
Applications – Create realistic images or improve image quality.
Challenges in GANs – Learn about training difficulties and solutions.
Project: Train a GAN to create new artwork or designs.
What are Transformers? – Basics of GPT and BERT models.
Practical: Fine-tune GPT to create a chatbot or summarize text.
Applications – Build tools like content generators or question-answering bots.
Real-Time Text Generation – Use APIs to generate responses.
Project: Develop a custom text generator or chatbot.
What are Diffusion Models? – Basics with simple examples.
Practical: Generate images using tools like Stable Diffusion.
Applications – Text-to-image generation and artistic effects.
Practical: Create custom AI-generated artwork.
Project: Compare outputs of GANs and diffusion models for similar tasks.
Choose a project – AI art, chatbot, or content generator.
Build your solution – Work step by step to create the application.
Test and improve – Fix issues and make it better.
Deploy the project – Learn how to share your work online.
Present your project – Show and explain your work to others.