The Microsoft AI-900 Exam is specifically designed to aid candidates prepare for, and pass, the Microsoft AI-900 certification test. This examination is aimed at qualified candidates with fundamental knowledge of artificial intelligent (AI) and machine learning (C / C++) concepts and technologies who wish to verify their abilities in this fast-changing field. The test must be taken in an official Microsoft certified testing center. The test can be taken online or in a traditional classroom setting. The exam is divided into three sub examinations.
The first sub-examination of the AI-900 Exam consists of an eight-step review of key areas of the course. The topics are artificial intelligent systems, learning and data structures, learning applications, and data analysis/optimization. These are the topics that any good AI course should cover. The second sub-examination focuses on supervised and unsupervised machine learning, and their current state, as well as their future.
The third and last sub-examination of the AI-900 Exam tests each candidate’s knowledge in supervised and unsupervised machine learning using the Microsoft Cognitive Services Evaluator software. Microsoft Cognitive Services Evaluators is a specially designed software program that administers the Microsoft AI-900 Exam. These programs are based on previous versions of the exams and contain testing instruments that measure the cleverness of candidates’ solution solving abilities. To prepare for these exams, one must take a full version of the Microsoft AI-900 practice test, which is available from the Microsoft site. The practice test simulates the real exam and simulates the real-time scenarios that will appear on the actual exam. This makes it easier for a person to familiarize themselves with the various procedures and to familiarize themselves with the terms and definitions.
When taking the practice exam, a person can choose to focus on either supervised or unsupervised machine learning, with the option of choosing between tasks based on real world scenarios. They can also choose between multiple-shot estimation, neural networks, artificial neural networks, deep neural networks, distributed decision trees, neural stack, neural network protocols, batching, and many more. Candidates who wish to maximize their chances of success on the Microsoft AI-900 Exam can take both supervised and unsupervised machine learning, as they are equally important during examination time.
A supervised learning path is the most traditional way of taking the Microsoft AI-900 Exam. In this scenario, a candidate will be provided with an actual Microsoft AI-900 Pro exam book containing all the questions that will appear on the actual test. The candidate will be guided accordingly by the book and then will need to spend several months studying and practicing for the exam. In most cases, this type of learning path offers excellent results, as it enables candidates to tackle new problems in a straightforward manner. However, it is very difficult to predict which questions will appear on the exam, which explains why it is more common for people to stick to unsupervised learning paths.
On the other hand, unsupervised machine learning has been especially designed for people who want a hands-on experience of the exam. It involves creating a simulated self-test environment using the Microsoft AI-900 simulator. All that is needed from the student is to enter questions into the simulator, and the software will prompt them the correct answer. The only drawback is that this type of workloads is quite hard to predict, and the difficulty level increases as the workload becomes higher. As a result, most test-takers tend to stick to supervised learning paths, because they offer a much higher reliability of results and the ability to quickly adjust to any changes in the exam schedule. This particular workload is also well suited for individuals who are preparing to take the exam after spending several months away from the workforce.
Another option for the test-taker who prefers to learn the exam without supervision is the blended learning path. In this approach, many different types of workloads are placed on the student, but he or she still uses the same textbook. Furthermore, self-testing is allowed, and the student can choose to repeat an answer if it is incorrect. For this reason, this type of workload is often recommended for people who plan to spend several months away from work and do not have the time to learn each question thoroughly. The downside is that this method usually requires the student to have reasonable reading comprehension skills, and it is not uncommon for students to forget what they have learned.
Regardless of which of these Microsoft AI 900 exam learning paths a student chooses to follow, it is important to spend enough time studying and practicing so that a correct score is attained. In addition, a student needs to choose one of the workloads that fit his or her style. This allows the individual to easily focus on each section of the test and make sure that he or she fully comprehends the material.
