The "Artificial Intelligence A-Z 2024" course is designed to provide students with hands-on experience in building seven AI projects for various applications. It covers fundamental AI theories, state-of-the-art models, and offers practical applications, making it suitable for learners looking to master both foundational and advanced AI techniques.
What You'll Learn
Building AI Applications
- Create 7 AI projects, each tailored for different real-world applications.
Core AI Knowledge
- Understand foundational AI theories.
- Master state-of-the-art AI models.
Practical Problem Solving
- Apply AI techniques to solve complex, real-world issues.
Reinforcement Learning Techniques
- Q-Learning
- Deep Q-Learning
- Deep Convolutional Q-Learning
- A3C (Asynchronous Advantage Actor-Critic)
- PPO (Proximal Policy Optimization)
- SAC (Soft Actor-Critic)
Large Language Models (LLMs)
- Transformers
- Low-Rank Adaptation (LoRA) and Quantization (QLoRA)
- NLP for Chatbots: Tokenization and Padding
- Fine-tuning LLMs with Knowledge Augmentation
Additional AI Methods
- DDPG (Deep Deterministic Policy Gradient)
- Full World Model
- Evolution Strategies & Genetic Algorithms
By completing this course, students gain in-depth knowledge and practical skills in building complex AI and LLM applications. From foundational understanding to tackling real-world challenges, this course equips learners with versatile AI tools and techniques to stay ahead in the rapidly evolving field of artificial intelligence.
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AI