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GENERATIVE AI COURSE FOR BEGINNERS
Welcome to our Generative AI Course for Beginners, where you’ll embark on a journey into the fascinating world of artificial intelligence and its generative capabilities. This course is designed to provide you with a foundational understanding of generative AI techniques, empowering you to create innovative and compelling AI-driven content.
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Anil Bidari
YOUR EXPERIENCED MENTOR
Anil Bidari is a versatile trainer and consultant specializing in GitLab, AWS, Azure, Google, DevOps, Jenkins, Kubernetes, Ansible, Docker, Agile, and Machine Learning. His expertise drives successful technology adoption and implementation, benefiting organizations and individuals alike.
- Instructor: Anil Bidari
- Participants: 1,550 Students
- Study Lecture : 30 Lectures
- Time Duration : 35 Hours - 5 Days
- Certificate : Yes
- Training Delivery Mode : Online - Live Instructor Led training
COURSE OBJECTIVE
- Introduction to generative AI concepts, including neural networks and probabilistic modeling.
- Basic understanding of generative models' applications in various fields like art, music, and text generation.
- Hands-on experience with entry-level generative AI tools and platforms.
- Guidance on ethical considerations and responsible AI development practices.
- Interaction with instructors and peers for support and collaborative learning.
- Preparation for further advancements in generative AI through foundational knowledge acquisition.
COURSE DESCRIPTION
Our Generative AI Course for Developers is designed to equip you with the knowledge and skills needed to leverage generative AI techniques effectively in your projects. Through hands-on learning and practical exercises, you’ll gain a comprehensive understanding of generative models, algorithms, and their applications in various domains.
COURSE SUMMARY
Generative AI Course for Beginners” offers an accessible introduction to generative AI concepts and applications. Participants gain hands-on experience, learn ethical considerations, and engage in collaborative learning. By the end, beginners are equipped with foundational knowledge and skills to embark on their journey in gen AI development.
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Course Outline
- Understanding generative models
- Applications of generative AI
- Basics of neural networks
- Training and evaluation techniques
- Architecture and components
- Training GANs for image generation
- Encoder-decoder architecture
- Learning latent representations
- Text generation with RNNs
- Music generation using RNNs
- Conditional generative models
- Attention mechanisms in generative models
- Bias and fairness
- Responsible AI development