❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [June 30th, 2023]

The Certified Artificial Intelligence Practitioner (CAIP) professional certificate's fourth and final course provides an introduction to more advanced algorithms used in both machine learning and deep learning. Learners will build multiple models that can solve business problems, and they will do so within a workflow. This course will cover decision trees, support-vector machines (SVMs), and artificial neural networks (ANNs). By the end of the course, learners will have a better understanding of how to select the best tool for the job.

[Applications]
Upon completion of this course, learners can apply the knowledge gained to build decision trees, SVMs, and artificial neural networks to solve various business problems. Learners can also use the workflow learned in this course to develop models that are tailored to the specific problem they are trying to solve. Additionally, learners can use the knowledge gained to select the best algorithm for the job, depending on the characteristics of the problem.

[Career Paths]
[Recommended Career Path]Data Scientist
[Description]Data Scientists are responsible for collecting, analyzing, and interpreting large amounts of data to identify trends and patterns. They use a variety of techniques, such as machine learning, artificial intelligence, and statistical analysis, to uncover insights from data. Data Scientists must be able to communicate their findings to stakeholders in a clear and concise manner. They must also be able to develop data-driven solutions to business problems.

[Development Trend]Data Science is an ever-evolving field, and the demand for Data Scientists is growing rapidly. As more organizations adopt data-driven decision-making, the need for Data Scientists with the skills to analyze and interpret data will continue to increase. Additionally, the development of new technologies, such as artificial intelligence and machine learning, will create new opportunities for Data Scientists to explore and develop innovative solutions.

[Education Paths]
The recommended educational path for learners is to pursue a degree in Artificial Intelligence (AI). This degree typically includes courses in mathematics, computer science, and engineering, as well as courses in AI-specific topics such as machine learning, deep learning, natural language processing, and robotics. Students will learn how to design, develop, and implement AI systems, as well as how to use AI to solve real-world problems. Additionally, students will gain an understanding of the ethical implications of AI and its potential impact on society.

The development trend of AI degrees is to focus on the practical application of AI, rather than just the theoretical aspects. This means that students will be expected to have a strong understanding of the fundamentals of AI, as well as the ability to apply AI to solve real-world problems. Additionally, AI degrees are increasingly focusing on the ethical implications of AI, as well as the potential impact of AI on society.