Lvl.3 -> AI Expert
Pre-requisite: Lvl.2 AI Engineer
Approx. Time Required: 2 months
✅ NEW! Join our Mentorship Program for this Career Path here. 👈
Dive into the advanced realms of AI over two months, transforming into an AI Expert. Start with “PyTorch: From Zero to Hero”, to learn and practice PyTorch. Then continue with “Artificial Intelligence 2.0,” where you’ll master Deep Reinforcement Learning (DRL) from its core principles to complex control tasks using algorithms like Twin Delayed DDPG (TD3). This course gives you the hands-on experience to implement sophisticated DRL models, tackling challenges in gaming, robotics, and more. Then, elevate your expertise with the “Artificial Intelligence Masterclass,” exploring a wide array of neural network architectures and cutting-edge topics such as Deep NeuroEvolution. From foundational concepts to advanced model implementations, this path prepares you to innovate and lead in AI’s future, equipped with the skills to solve complex problems and contribute significantly to technological advancements.
This course provides a comprehensive introduction to deep learning using PyTorch. Starting from the basics, you’ll progressively build your skills, exploring neural network architectures, advanced PyTorch topics, and applying your knowledge to a final project. By the end of the course, you’ll be equipped to create complex machine learning models and implement real-world solutions.
- Learn the fundamentals of PyTorch, including tensor operations, automatic differentiation, and data handling.
- Explore how to build and train various neural network models using PyTorch’s powerful modules and layers.
- Dive into more complex topics such as custom layers, optimization techniques, and working with GPUs.
By the end of this course, you’ll have the skills to develop and deploy state-of-the-art models in PyTorch.
2. Artificial Intelligence 2.0
Embark on a journey through the cutting-edge world of Deep Reinforcement Learning (DRL). This course starts with the fundamentals, covering key concepts like Q-Learning, Policy Gradient, and Actor-Critic models, to give you a solid foundation in DRL. Dive deep into Twin Delayed DDPG (TD3) theory and implementation, learning to solve complex control tasks with advanced DRL algorithms.
- Understand the core principles behind deep reinforcement learning, including various algorithms and their applications.
- Master the Twin Delayed DDPG (TD3) algorithm, from theoretical concepts to practical implementation steps.
- Gain hands-on experience by coding DRL models in Python, preparing you to tackle your own DRL projects.
By the end of this course, you’ll have a comprehensive understanding of DRL and its applications. You’ll be equipped with the skills to implement sophisticated DRL models, enabling you to address and solve complex problems in various domains such as gaming, robotics, and beyond. This course not only teaches you the theory behind DRL but also guides you through implementing these advanced models, ensuring you’re ready to contribute to the future of AI innovations.
3. Artificial Intelligence Masterclass
Dive into the AI Masterclass, a comprehensive course designed to take you from the basics of neural networks to the complexities of implementing advanced AI models. This course is structured to provide a step-by-step guide through different neural network architectures, including Artificial Neural Networks, Convolutional Neural Networks, AutoEncoders, Variational AutoEncoders, and more, leading up to cutting-edge topics like Deep NeuroEvolution.
Build a strong foundation in neural network concepts, learning how they work and are trained.
Gain hands-on experience with Convolutional Neural Networks for image processing and Recurrent Neural Networks for sequence data.
Explore advanced models like AutoEncoders and Variational AutoEncoders for generative tasks.
Dive into the exciting field of Reinforcement Learning and understand how AI can learn complex behaviors.
Discover Deep NeuroEvolution techniques for optimizing neural networks.
Upon completing this course, you’ll have mastered the theory behind major AI models and have the practical skills to implement them. Whether you’re tackling image recognition, sequence prediction, or aiming to create AI that learns and evolves, this course equips you with the knowledge to push the boundaries of what’s possible with AI.
👉 Remember to join the Mentorship Program [here] to grow even faster!