VOOZH about

URL: https://www.coursera.org/learn/gen-ai-for-fraud-detection-analytics

⇱ Gen AI for Fraud Detection Analytics | Coursera

Gen AI for Fraud Detection Analytics

Ends soon! Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.

Gen AI for Fraud Detection Analytics

Instructor: Edureka

3,844 already enrolled

Included with

Gain insight into a topic and learn the fundamentals.
4.2

39 reviews

Beginner level

Recommended experience

3 hours to complete
Gain insight into a topic and learn the fundamentals.
4.2

39 reviews

Beginner level

Recommended experience

3 hours to complete

What you'll learn

  • Understand the foundations of fraud detection and how Generative AI transforms this field.

  • Apply advanced AI models such as GANs, NLP, and LSTM to fraud detection use cases.

  • Build hands-on project for fraud detection and anomaly analysis with AI.

  • Evaluate future trends, ethical considerations, and challenges in AI-driven fraud analytics.

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English
Flexible schedule
Learn at your own pace

There is 1 module in this course

Welcome to the '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.

Enhance your fraud detection skills with Generative AI. Learn core principles, real-world applications, and ethical practices to detect fraud with accuracy and compliance.

What's included

12 videos8 readings4 assignments3 discussion prompts

12 videos•Total 51 minutes
  • Gen AI for Fraud Detection Analytics•3 minutes
  • Introduction to Generative AI•5 minutes
  • Understanding Gen AI's part in Fraud Detection•5 minutes
  • Technological Advancements of Generative AI in Fraud Detection•6 minutes
  • Overview of the Project•3 minutes
  • Project Development•3 minutes
  • Data Collection and Pre-Processing•5 minutes
  • Setting-up LSTM Model•4 minutes
  • Setting-Up GAN Model Architecture•5 minutes
  • Ethical Challenges in Fraud Detection•5 minutes
  • Regulatory compliance and Privacy protection•5 minutes
  • Course Summary•2 minutes
8 readings•Total 68 minutes
  • Course Overview•5 minutes
  • How to Use Discussion Forums•2 minutes
  • Unleashing the Potential of Natural Language Processing (NLP)•10 minutes
  • Introduction to LSTM- A deatiled Explanation•7 minutes
  • Introduction to Generative Adversarial Networks- From core principles to diverse application•7 minutes
  • Unveiling Vital TensorFlow Keras Imports for GAN Development•7 minutes
  • Real world Application of Fraud Detection using GenAI•5 minutes
  • Practice Project•25 minutes
4 assignments•Total 33 minutes
  • Knowledge Check: Overview of Fraud detection and Generative AI•5 minutes
  • Knowledge Check: Email Fraud Detection using GAN model•5 minutes
  • Knowledge Check: Best Practices•3 minutes
  • End Course Knowledge Check: Module Wrap Up and Assessment•20 minutes
3 discussion prompts•Total 25 minutes
  • How do you envision the integration of generative AI in fraud detection transforming the landscape of fraud prevention? •10 minutes
  • How can generative AI models like GANs (Generative Adversarial Networks) be effectively utilized to improve the accuracy of email spam classification?•10 minutes
  • What ethical challenges do you foresee in implementing AI-driven fraud detection systems, and how can these challenges be mitigated?•5 minutes

Instructor

Instructor ratings
4.7 (8 ratings)
Edureka
211 Courses•190,189 learners

Explore more from Security

Why people choose Coursera for their career

👁 Image

Felipe M.

Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
👁 Image

Jennifer J.

Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
👁 Image

Larry W.

Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
👁 Image

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Frequently asked questions

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.

No, the course starts with fundamentals, making it beginner-friendly.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. 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.

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.

Financial aid available,