What Does MVP Stand For? It’s Not What You Think.
October 7, 2024
Article
(19 reviews)
Recommended experience
Beginner level
Prior working experience in Python Programming is recommended but not mandatory.
(19 reviews)
Recommended experience
Beginner level
Prior working experience in Python Programming is recommended but not mandatory.
Working with Generative AI, delve into email spam classification models, and explore ethical challenges in the field of Fraud Detection.
Add to your LinkedIn profile
4 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
Welcome to the 'Unlocking the Power of Generative AI in Fraud Detection Analytics' course, where you'll embark on a transformative journey to acquire practical expertise in generative AI for fraud prevention.
Throughout this course, you'll delve into the world of AI-driven fraud detection, mastering the fundamentals and exploring real-world applications. By the end of this course, you will be able to: - Gain a comprehensive understanding of generative AI in fraud detection. - Utilize generative AI techniques, especially the LSTM and GAN model, for practical email fraud detection projects, strengthening the capacity to employ AI in real-world fraud prevention scenarios. - Grasp the key concepts of generative AI's role in fraud detection, encompassing ethical considerations and best practices for data handling, establishing a strong foundation in AI-driven fraud analytics. This course is tailored for learners from diverse backgrounds, including data scientists, fraud analysts, AI enthusiasts, and professionals aiming to enhance their skills in fraud analytics. Prior experience in AI and fraud detection is beneficial but not required. Embark on this educational journey to master Generative AI for Fraud Detection Analytics and elevate your expertise in fraud prevention.
This short course is designed for learners to enhance their capabilities in the field of fraud detection. Throughout the course, participants embark on a journey that explores the innovative intersection of generative AI and fraud analytics. The curriculum covers essential topics, including the principles of generative AI, practical application in fraud detection scenarios, ethical considerations, and regulatory compliance. By combining theoretical knowledge, hands-on experiences, and real-world examples, learners gain the expertise to leverage generative AI effectively in fraud detection. Upon completion, students are equipped with the skills to detect fraud with precision, ensure ethical practices, and comply with regulatory standards, making them proficient in this evolving field.
12 videos8 readings4 assignments3 discussion prompts
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Edureka is an online education platform focused on delivering high-quality learning to working professionals. We have the highest course completion rate in the industry and we strive to create an online ecosystem for our global learners to equip themselves with industry-relevant skills in today’s cutting edge technologies.
Coursera Instructor Network
Course
Coursera Project Network
Course
Johns Hopkins University
Course
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
This course is a comprehensive exploration of the application of generative AI in the field of fraud detection and prevention. It covers a range of topics, including the fundamentals of generative AI, the development of email spam classification models, and the ethical challenges associated with fraud detection using AI.
This course is suitable for Data Scientists, IT/Cybersecurity professionals, AI enthusiasts, students, and business leaders, offering a broad audience the opportunity to master generative AI for fraud detection and prevention.
While prior experience in Python programming is recommended, it's important to note that it's not mandatory to enroll in this course. This means that learners with varying levels of familiarity with Python can still benefit from the course.
In this comprehensive course, you'll embark on a journey to gain a deep understanding of how generative AI can be effectively employed in the field of fraud detection and prevention. You'll develop practical skills in building and optimizing email spam classification models, a crucial component of contemporary fraud detection efforts. Additionally, the course emphasizes the ethical considerations and challenges associated with the use of AI in fraud detection, equipping you with the knowledge and ethical awareness to navigate this specialized domain responsibly.
This course is designed to span approximately two hours, encompassing a diverse range of learning materials and activities. Throughout this course, learners will engage with various educational resources, including video content on the Generative AI and Fraud Detection , reading materials to deepen understanding, graded quizzes to assess comprehension, and thought-provoking discussion prompts to encourage collaborative learning and critical thinking.
Within this course, we extensively utilize Python programming as the primary language for developing an Email Spam Classification model. This model is specifically designed using the advanced GAN (Generative Adversarial Network) model, which is a prominent deep learning technique. Through hands-on exercises and practical examples, you'll gain proficiency in Python programming and explore the intricacies of GAN models for email spam classification.
You won't require any prerequisites for software installation or setup because all the tasks and activities are conveniently conducted within the Google Colab environment. This means you can seamlessly follow along with the course content without the need to install additional software or configure specific settings on your local machine. Google Colab provides a user-friendly and cloud-based platform for hands-on learning, making it accessible and hassle-free for all learners.
Throughout the course, we have extensively explored and utilized essential libraries and frameworks to empower your understanding of generative AI and its applications in fraud detection. Two key frameworks covered in detail are Tensorflow and Keras. Tensorflow, an open-source machine learning framework developed by Google, forms the foundation of our practical exercises. Keras, a high-level neural networks API, is seamlessly integrated with Tensorflow, offering a user-friendly interface for building and training deep learning models.
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work.
These cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. They are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising.
These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance.
These cookies enable the website to provide enhanced functionality and personalization. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly.