Course Overview
Generative AI is revolutionizing how content is created, predictions are made, and insights are generated across industries. This track is designed for beginners, guiding them from the fundamentals of AI to building and deploying advanced Generative AI models using Python, TensorFlow, and PyTorch.
Through hands-on coding, real-world projects, and industry case studies, learners will master deep learning, neural networks, AI ethics, and deployment strategies. With a focus on practical applications, this course prepares students for high-demand Generative AI roles in healthcare, finance, marketing, and beyond
What You’ll Experience
- Hands-on coding – Develop AI models using Python, TensorFlow, and PyTorch
- End-to-end AI development – Train, fine-tune, and deploy AI-powered solutions
- Diverse industry case studies – Explore real-world applications in healthcare, finance, and marketing
- Project-based learning – Build and showcase a portfolio of AI projects
- Ethical AI development – Understand bias mitigation, fairness, and responsible AI practices
- Collaborative learning – Work on group projects, hackathons, and peer reviews
Syllabus
Core AI Foundations
- Introduction to AI & Machine Learning
- Deep Learning Basics
- Data Preparation & Feature Engineering
Generative AI Models
- Introduction to Generative AI
- Text Generation – Large Language Models (LLMs) & Chatbots
- Image Generation – GANs, Stable Diffusion, and AI Art
Advanced AI Techniques
- Reinforcement Learning & AI Model Training
- AI Ethics & Bias Mitigation
- Model Optimization & Performance Tuning
Real-World Applications of Generative AI
- AI in Business – Use Cases in Marketing, Healthcare, and Finance
- Building AI-Powered Applications
- Deploying & Integrating AI Models
Learning Outcomes
- Ability to develop Generative AI models for text, images, and data analysis
- Proficiency in deep learning frameworks like TensorFlow and PyTorch
- Expertise in AI model deployment and integration into real-world applications
- Understanding of AI ethics, bias mitigation, and responsible AI development
- Strong project portfolio** showcasing AI-powered applications
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