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Stanford University is offering an online graduate course Artificial Intelligence: Principles and Techniques to provide students with complete knowledge of current artificial intelligence research and methodologies. The online program at Stanford School of Engineering offers professionals a complete educational experience that combines theoretical knowledge with practical algorithm design skills for developing AI solutions across different industries.
Understand foundational AI principles including problem solving, reasoning, learning, and interaction
Implement search algorithms for shortest paths, robot motion planning, and machine translation
Apply Markov Decision Processes (MDPs) to make optimal decisions under uncertainty
Design intelligent agents and strategies for adversarial games such as Pac-Man
Solve real-world problems using constraint satisfaction problems (CSPs)
Model uncertainty and causality with Bayesian networks
Integrate logic into algorithms using syntax, semantics, and inference rules
The program offers its entire content through online delivery which allows instructors to control the learning schedule thus making it suitable for professionals who work. Students need to spend 10 to 15 hours each week on their studies while they can access course content for 90 days after finishing their studies. The participants who achieve a score of 70% or higher will receive a Certificate of Achievement from Stanford University which enhances their academic credentials for their AI profile.
Core AI Foundations: Problem solving, reasoning, learning, and intelligent agents
Search and Planning: Graph search, shortest paths, planning, and game playing
Machine Learning: Core ML concepts integrated into AI systems
Uncertainty and Probability: Bayesian networks, graphical models, and probabilistic reasoning
Decision Making: Markov Decision Processes and policy optimization
Logic and Constraints: Logical reasoning, CSPs, and rule-based systems
Applied AI Skills: Algorithm design, testing, and implementation using Python and NumPy
Students must demonstrate their Python programming skills through completion of assignment tasks
Basic Linux command-line knowledge to meet the job requirements
Must demonstrate basic knowledge of college-level calculus and linear algebra.
Knowledge of probability theory together with its distribution patterns.
The Stanford Artificial Intelligence Principles and Techniques course offers students both academic knowledge and real-world applications. The course provides students with essential AI skills which professionals need for their work through instruction from Stanford faculty members who teach the course. The program is designed for students who wish to advance their studies in AI or conduct research or pursue specialized training in machine learning and intelligent systems.
Artificial Intelligence: Principles and Techniques (Online) by Stanford University is ideal for professionals and engineers who want to develop a complete understanding of AI fundamental concepts. The course provides students with essential skills through its theoretical framework and practical exercises and authenticates their achievements through a Stanford certificate which enables them to solve actual AI challenges and advance their professional development.
