Our Generative AI syllabus is designed to equip you with the in-demand skills needed to thrive in the era of Generative AI. We will cover the core concepts and technologies of this transformative technology such as deep learning, neural networks, VAEs, GANs, LLMs, TensorFlow, PyTorch, and reinforcement learning, and apply them to real-world applications in art, music, text generation, and more in our Generative AI course content. You will acquire practical expertise with well-known Generative AI technologies and build a solid basis for a prosperous career in this quickly changing subject by combining theoretical and practical study, which forms the framework of our Generative AI course outline.
Generative AI Course Syllabus (2025)
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Syllabus for The Generative AI Course Syllabus Course
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Module 1: Foundations of Generative AI
1
- Introduction to Artificial Intelligence and Machine Learning
- Supervised, Unsupervised, and Reinforcement Learning
- Deep Learning Fundamentals: Neural Networks, Backpropagation, Gradient Descent
- Generative vs. Discriminative Models
- Key Concepts in Generative AI: Latent Space, Sampling, Noise
Module 2: Core Generative Models
2
- Generative Adversarial Networks (GANs):
- Architecture of GANs: Generator and Discriminator
- Training Process, Challenges, and Variants (DCGAN, StyleGAN)
- Applications of GANs: Image Generation, Style Transfer, Data Augmentation
- Variational Autoencoders (VAEs):
- Encoding and Decoding Process, Latent Space Representation
- Applications of VAEs: Dimensionality Reduction, Anomaly Detection, Generative Modeling
- Diffusion Models:
- Forward and Reverse Diffusion Processes, Noise Scheduling
- Applications of Diffusion Models: Image Generation, Text-to-Image Synthesis, Audio Generation
Module 3: Applications of Generative AI
3
- Image Generation and Manipulation:
- Creating photorealistic images, artistic styles, and novel concepts
- Image-to-image translation, inpainting, and super-resolution
- Natural Language Processing:
- Text generation, translation, summarization, and dialogue systems
- Large Language Models (LLMs) and their applications
- Music and Audio Generation:
- Composing music, creating sound effects, and generating speech
- Other Applications:
- Drug discovery, material design, and creative content generation
Module 4: Ethical Considerations and Future Directions
4
- Ethical Implications:
- Bias and Fairness, Misinformation and Deepfakes, Job Displacement
- Responsible AI Development and Deployment
- Future Trends:
- Multimodal Generative AI, Reinforcement Learning for Generative Models
- Explainable AI and Interpretability for Generative Models
Breakdown of Generative AI Course Syllabus Course Fee and Batches
Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
May 2025
Week days
(Mon-Fri)
Online/Offline
2 Hours Real Time Interactive Technical Training
1 Hour Aptitude
1 Hour Communication & Soft Skills
(Suitable for Fresh Jobseekers / Non IT to IT transition)
Course Fee
May 2025
Week ends
(Sat-Sun)
Online/Offline
4 Hours Real Time Interactive Technical Training
(Suitable for working IT Professionals)
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