Reinforcement Learning Specialization

Colleagues, in the “Reinforcement Learning Specialization” you will understand the foundations of much of modern probabilistic artificial intelligence (AI) and be prepared to take more advanced courses or to apply AI tools and ideas to real-world problems. Skill-based training modules address: 1) Fundamentals of Reinforcement Learning, 2) Sample-based Learning Methods, 3) Prediction and Control with Function Approximation, and 4) A Complete Reinforcement Learning System (Capstone). Learn to: Build a Reinforcement Learning system for sequential decision making. Understand the space of RL algorithms (Temporal- Difference learning, Monte Carlo, Sarsa, Q-learning, Policy Gradients, Dyna, and more), how to formalize your task as a Reinforcement Learning problem, and how to begin implementing a solution, and how RL fits under the broader umbrella of machine learning, and how it complements deep learning, supervised and unsupervised learning. Acquire high-demand skills involving  Machine Learning, Reinforcement Learning, Decision Intelligence, Model Evaluation, Simulations, Agentic Systems, Systems Development, Artificial Neural Networks, Machine Learning Methods, Feature Engineering, Markov Model, Deep Learning, Artificial Intelligence, Sampling (Statistics), Model Training, Applied Machine Learning, Algorithms, Solution Architecture, Machine Learning Algorithms, and Supervised Learning.

Enroll today (teams & executives are welcome): https://imp.i384100.net/B5d9MW

For your listening-reading pleasure:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) or (Kindle) 

3 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) (Kindle)

Much career success, AI Academy (please subscribe and share with your team)