SIX MUST-HAVES IN A PROMISING ARTIFICIAL INTELLIGENCE COURSE LIST
Artificial intelligence has become the next big thing in the world, especially for employment. Also, it’s so easy to acquire AI skills today as you can earn them through certified learning from the online artificial intelligence course list. There are several approaches to initiate learning about artificial intelligence. This has only been possible through the provision of massive open online courses.
Artificial Intelligence Course list
Some of the renowned providers include names such as EdX, Coursera, and Udemy. Their capabilities extend beyond that of an informative video or article on artificial intelligence. Furthermore, an individual could browse through the artificial intelligence course list and select one based on time and commitment. Therefore, this article presents a list of AI courses that could be the next big step toward an individual’s success.
Udacity provides a training course with a duration of 10-11 weeks. It is a promising avenue to obtain an impression of data collection through machine learning systems and data processing. The course is well-known on the artificial intelligence course list. It would enable individuals to develop a comprehensive understanding of grouping, machine language algorithms, choice trees, SVMs, and Python.
The course facilitated by Google aims at developing the fundamental knowledge of participants regarding machine language and measurements. The course is not suitable for beginners as it requires participants to have a prior background in Python programming. Some of the other highlights of the online AI course include convolutional networks and deep neural networks. They also include opportunities for comprehensive learning of the models for texts and sequences.
Andrew Ng’s Machine Learning
The course takes place over a duration of 11-12 weeks by Andrew Ng who currently serves as an Associate Professor at Stanford University. The primary highlights of the course refer to Naive Bayes, linear and logistic regression, unmonitored learning, and regularization. The primary requirements for enrolling in this course include a basic understanding of software engineering, probability, and linear algebra.
AI: Principles and Techniques
This course is provided specifically by Stanford and it provides free training on the approaches in which AI leverages mathematical tools for the resolution of complex issues such as facial and speech recognition, machine interpretation, etc. Some of the essential highlights that participants would be able to find in this course from the artificial intelligence course list are heuristics, tree search, Markov decision procedures, rationale, and machine learning ideas, Bayesian systems, and constraint satisfaction issues.
Learning from Data
Known as EdX’s approach towards Introductory Machine learning, this course deals with the training participants in the basics of calculations. It also teaches the uses of machine learning and hypothetical standards. The course duration is estimated to be 10-11 weeks alongside the requirement of 10-20 hours every week.
AI for Robotics
The course is provided by Udacity and deals comprehensively with discussions on robotics programming approaches. Furthermore, these approaches are followed by Google and Stanford and are a part of the Deep Learning Nanodegree Foundation course. Participants need to depict promising conceptual knowledge of the aspects such as programming experience, Python, and mathematical concepts such as probability and linear algebra. Also, notable highlights of the course include references to the discussion on PID control, SLAM, and Kalman and Particle channels.
Therefore, the opportunities for having a prolific career in the domain of AI-related services could be improved further with a certification in one from the online Artificial intelligence course list.
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