
This online, self-paced course explores how artificial intelligence (AI) and machine learning are revolutionizing investment and wealth management. You will examine the evolution of AI-driven platforms, including robo-advisors, and understand their operational mechanisms and success factors. The course transitions from traditional human-based and data-driven investment strategies to neural networks, assessing AI's capability in making investment decisions and its role in trading. You will learn to evaluate the strengths and limitations of AI in investing through practical frameworks, gain insights into modern fintech business models, and develop skills in constructing diversified portfolios aligned with risk preferences. This course is the final component of the Financial Technology (Fintech) Innovations Specialization.
The course is structured into four modules, covering key aspects of AI in investment technology.
This course equips you with skills relevant to the evolving landscape of investment and wealth management, driven by technology.
Course materials are self-paced and accessible throughout the duration of the course.
Pricing details for general enrollment via Coursera are not provided on the program page.
This is an online, self-paced course, allowing you to learn at your own speed. The programme content is delivered across four modules.
Enrollment is available via Coursera, but pricing details are not specified on the program page. University of Michigan students, alumni, faculty, and staff receive free access.
No prior experience is required for this beginner-level course. Specific English language proficiency requirements are not detailed.
You will learn about AI and machine learning in investment management, robo-advisors, and fintech business models. Skills gained are relevant to AI Innovation and Algorithmic Trading roles in investment and wealth management.
You can enroll through Coursera by visiting the program page on their platform. If you are a University of Michigan affiliate, you can access it for free using your U-M credentials.