What are the learning objectives of our Artificial Intelligence Program? Becoming a Certified Artificial Intelligence Professional puts you on the path to an exciting, evolving career that is predicted to grow sharply into 2025 and beyond. Artificial intelligence and Machine Learning will impact all segments of daily life by 2025, with applications in a wide range of industries such as healthcare, transportation, insurance, transport and logistics and even customer service. The need for AI specialists exists in just about every field as companies seek to give computers the ability to think, learn and adapt.
Design and build your own intelligent agents and apply them to create practical AI projects including games, machine learning models, logic constraint satisfaction problems, knowledge-base systems, probabilistic models, agent decision-making functions and more.
Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline.
Understand and master the concepts and principles of machine learning, including its mathematical and heuristic aspects Implement deep learning algorithms in TensorFlow and interpret the results, Understand neural networks and multi-layer data abstraction, empowering you to analyze and utilize data like never before.
Comprehend and differentiate between theoretical concepts and practical aspects of machine learning.
Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces Learn about major applications of Artificial Intelligence across various use cases in various fields like customer service, financial services, healthcare etc Implement classical Artificial Intelligence techniques, such as search algorithms, minimax algorithm, neural networks, tracking, robot localization and more.
Ability to apply Artificial Intelligence techniques for problem-solving and explain the limitations of current Artificial Intelligence techniques.
Formalize a given problem in the language/framework of different AI methods. (e.g., as a search problem, as a constraint satisfaction problem, as a planning problem, etc)