Go to Course: https://www.coursera.org/learn/guided-tour-machine-learning-finance
**Course Review: Guided Tour of Machine Learning in Finance** If you’re looking to delve into the world of Machine Learning (ML) in the finance sector, Coursera’s "Guided Tour of Machine Learning in Finance" is an exceptional starting point. This course offers a well-rounded introduction to ML's fundamentals, particularly how they apply to the financial industry. ### Overview The course aims to provide learners with a broad yet insightful overview of Machine Learning, with a targeted focus on its applications within finance. Over the span of the course, participants explore fundamental concepts of artificial intelligence and machine learning, mathematical foundations, and the intricacies of supervised learning. The highlight is the capstone project, where learners utilize supervised machine learning methods to predict bank closures, solidifying theoretical knowledge with practical application. ### Syllabus Breakdown 1. **Artificial Intelligence & Machine Learning**: The course kicks off by introducing the concepts of AI and ML, laying down the necessary groundwork. It contextualizes how ML is revolutionizing the financial industry, helping participants understand its relevance. 2. **Mathematical Foundations of Machine Learning**: A solid comprehension of mathematics is crucial in ML, and this segment covers essential mathematical concepts that underpin machine learning algorithms, such as linear algebra and statistics. 3. **Introduction to Supervised Learning**: Here, learners gain insights into supervised learning practices, including various techniques and algorithms commonly employed in the field. This section paves the way for real-world applications, particularly in finance. 4. **Supervised Learning in Finance**: This module fuses together the concepts learned in the previous segments, showcasing specific use cases of supervised learning in finance—tackling problems such as predicting loan defaults and assessing credit risk. ### Capstone Project One of the most exciting aspects of this course is the capstone project. Students are challenged to apply everything they’ve learned to predict bank closures—a scenario that demands the integration of theoretical knowledge and hands-on problem-solving. This project is not only a fantastic way to reinforce learning but also a valuable addition to your portfolio, particularly if you’re aiming for a career in financial data analysis or risk management. ### Recommended For This course is perfect for beginners with little to no background in machine learning or finance. It's an excellent fit for finance professionals looking to enhance their tech skills, data analysts interested in expanding their algorithms knowledge, or anyone intrigued by the intersection of AI and finance. ### Conclusion The "Guided Tour of Machine Learning in Finance" course on Coursera effectively lays the groundwork for understanding how machine learning algorithms are shaping the financial industry. Its well-structured content, practical capstone project, and focus on real-world applications make it both educational and applicable. I highly recommend enrolling in this course as a stepping stone into the expanding field of machine learning in finance. Not only will you gain invaluable skills and knowledge, but you will also be practicing in an area that is becoming increasingly relevant in today’s technology-driven financial landscape. Dive in and start your journey into the future of finance!
Artificial Intelligence & Machine Learning
Mathematical Foundations of Machine LearningIntroduction to Supervised LearningSupervised Learning in FinanceThis course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. The goal of Guided Tour of Machine Learnin
To much math in lectures, assignments are not coherent and complicated, im not sure that i need tensorflow from scratch to work with finance(Keras fits better)
Great course! Relevant concepts are described in the videos and the bibliography is accurate to cover the rest.
The course is great, but the code assessment isn't very clear about how to solve the problem. Instead, I had to figure out how to code on my own.
The coding part could have been better explained and the reasoning for what is being done should be included in the coding videos.
Introduction of ML for Financial application with combination of Scikit learn, Statsmodels and Tensorflow with neuralnets made this class very interesting. Learned and Enjoyed lot.