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Generative AI skills are becoming an essential part of a cybersecurity professional’s toolkit. The US Bureau of Labor Statistics projects a 32% increase in the number of cybersecurity professionals needed through 2032, with a current median salary of $112,000. This Specialization is designed to build skills enabling you to enter this lucrative and exciting field. Begin by learning how to distinguish generative AI from discriminative AI. You’ll explore real-world generative AI use cases and discover popular generative AI models and tools for text, code, image, audio, and videos. Next, delve into generative AI prompts engineering concepts, their real-world business uses, and prompt techniques like zero-shot and few-shot, andothers. You’ll explore popular prompt engineering tools including IBM Watsonx, Prompt Lab, Spellbook, and Dust. Then dive intofundamental concepts of generative AI usefor cybersecurity. Gain valuable job job-ready skills when you apply generative AI techniques to real-world scenarios, including UBEA, threat intelligence, report summarization, and playbooks, and assess their impact and vulnerabilities. Learn how generative AI models can help mitigate attacks, analyze real-world case studies,and learn toidentify key implementation factors. Throughout your learning journey, you’ll create a project portfolio to share your provable skills with potential employers. And earn a shareable course certificate and badge that verifies your achievement. Applied Learning Project This Specialization emphasizes applied learning and includes a series of hands-on activities and projects. In these exercises, you’ll take the theory and skills you’ve gained and practice them with real-world scenarios. Projects include: - Generate Text, Images, and Code using Generative AI - Apply Prompt Engineering Techniques and Best Practices’ - Use Generative AI in Cybersecurity for content filtering, threat analysis, and automated response generation

Artificial intelligence (AI) is rapidly evolving as a multidimensional paradigm, with critical implications for individuals, communities, organizations, businesses, national and regional economies and human society at large. This unique course will help you understand AI on three dimensions: Practice, Principles & Strategy. The course is introductory in nature but will provide a reasonably rigorous learning experience towards gaining a state of the art applied and philosophical overview of AI. Course Objectives are to: 1. Impart a simplified philosophical understanding of the nature and capabilities of Artificial Intelligence 2. Improve understanding of AI-concepts, AI-ideas and AI-strategy 3. Provide a foundational explanation of AI Ethics and Risks 4. Encourage development of strategic thinking on AI, and a future with AI. Note this course is a subset of MPI program at Bloustein: - Students are encouraged to follow the instructor on Twitter / X for latest updates on AI events and news.

Imagine a world where your photos don't just capture memories, but also become intelligent assistants, helping you navigate and manage daily tasks. Welcome to "GPT Vision: Seeing the World Through Generative AI", a course designed to revolutionize how you interact with the world around you through the lens of Generative AI and photos. In this course, you will learn to how take a picture of anything and turn it into: - a recipe - a shopping list - DIY plans to make it - a plan to reorganize it - a description for a social media post - organized text for your notes or an email - an expense report or personal budget entry This course will teach you how to harness GPT Vision's power to transform ordinary photos into problem-solving tools for your job and personal life. No experience is required, just access to GPT-4(V) Vision, which is part of the ChatGPT+ subscription. Whether it's ensuring you've ticked off every item on your grocery list or creating compelling social media posts, this course offers practical, real-world applications of Generative AI Vision technology. Social Media Mastery: Learn to create compelling descriptions for your social media photos with AI, enhancing your digital storytelling. Capture Your Brainstorming: Take a picture of notes on a marker board or napkin and watch them be turned into well-organized notes and emailed to you. DIY and Culinary Creations: Explore how to use photos for DIY home projects and cooking. Discover how to generate prompts that guide you in replicating or creating dishes from images or utilizing household items for creative DIY tasks. Data Extraction and Analysis: Gain expertise in extracting and analyzing data from images for various applications, including importing information into tools like Excel. Expense Reporting Simplified: Transform the tedious task of expense reporting by learning to read receipts and other documents through GPT Vision, streamlining your financial management. Progress Tracking: Develop the ability to compare photos of the real world with plans, aiding in efficient monitoring and management of project progress, such as how your construction project is progressing. Knowledge Discovery: Learn about anything you see. Snap a picture, generate a prompt, and uncover a world of information about objects, landmarks, or any item you encounter in your daily life. Organizational Mastery: Learn how to organize your personal spaces, like closets or storage areas, by using AI to analyze photos and suggest efficient organization strategies and systems.

Introduction video: https://youtu.be/TRhwIHvehR0 This course is for a complete novice of Python coding, so no prior knowledge or experience in software coding is required. This course selects, introduces, and explains Python syntaxes, functions, and libraries that were frequently used in AI coding. In addition, this course introduces vital syntaxes, and functions often used in AI coding and explains the complementary relationship among NumPy, Pandas, and TensorFlow, so this course is helpful for even seasoned python users. This course starts with building an AI coding environment without failures on learners’ desktop or notebook computers to enable them to start AI modeling and coding with Scikit-learn, TensorFlow, and Keras upon completing this course. Because learners have an AI coding environment on their computers after taking this course, they can start AI coding and do not need to join or use the cloud-based services.

Today’s learners need to know what artificial intelligence (AI) is, how it works, how to use it in their everyday lives, and how it could potentially be used in their future. Using AI requires skills and values which extend far beyond simply having knowledge about coding and technology. This course is designed by teachers, for teachers, and will bridge the gap between commonly held beliefs about AI, and what it really is. AI can be embedded into all areas of the school curriculum and this course will show you how. This course will appeal to teachers who want to increase their general understanding of AI, including why it is important for learners; and/or to those who want to embed AI into their teaching practice and their students’ learning. There is also a unique opportunity to implement a Capstone Project for students alongside this professional learning course. Macquarie School of Education at Macquarie University and IBM Australia have collaborated to create this course which is aligned to AITSL ‘Proficient Level’ Australian Professional Standards at AQF Level 8.

Prepare for a career in the high-growth field of software development. In this program, you’ll learn in-demand skills and tools used by professionals for front-end, back-end, and cloud native application development to get job-ready in less than 4 months. Full stack refers to the end-to-end computer system application, including the front end and back end coding. This Professional Certificate covers development for both of these scenarios. Cloud native development refers to developing a program designed to work on cloud architecture. The flexibility and adaptability that full stack and cloud native developers provide make them highly sought after in this digital world. You’ll learn how to build, deploy, test, run, and manage full stack cloud native applications. Technologies covered includes Cloud foundations, GitHub, Node.js, React, CI/CD, Containers, Docker, Kubernetes, OpenShift, Istio, Databases, NoSQL, Django ORM, Bootstrap, Application Security, Microservices, Serverless computing, and more. After completing the program you will have developed several applications using front-end and back-end technologies and deployed them on a cloud platform using Cloud Native methodologies. You will publish these projects through your GitHub repository to share your portfolio with your peers and prospective employers. This program is ACE® and FIBAA recommended—when you complete, you can earn up to 18 college credits and 6 ECTS credits. Applied Learning Project Throughout the courses in the Professional Certificate, you will develop a portfolio of hands-on projects involving various popular technologies and programming languages in Full Stack Cloud Application Development. These projects include creating: - HTML pages on Cloud Object Storage - An interest rate calculator using HTML, CSS, and JavaScript - An AI program deployed on Cloud Foundry using DevOps principles and CI/CD toolchains with a NoSQL database - A Node.js back-end application and a React front-end application - A containerized guestbook app packaged with Docker deployed with Kubernetes and managed with OpenShift - A Python app bundled as a package - A database-powered application using Django ORM and Bootstrap - An app built using Microservices & Serverless - A scalable, Cloud Native Full Stack application using the technologies learned in previous courses You will publish these projects through your GitHub repository to share your skills with your peers and prospective employers.

In this course, you will learn about AI-powered applications that can enhance the customer journey and extend the customer lifecycle. You will learn how this AI-powered data can enable you to analyze consumer habits and maximize their potential to target your marketing to the right people. You will also learn about fraud, credit risks, and how AI applications can also help you combat the ever-challenging landscape of protecting consumer data. You will also learn methods to utilize supervised and unsupervised machine learning to enhance your fraud detection methods. You will also hear from leading industry experts in the world of data analytics, marketing, and fraud prevention. By the end of this course, you will have a substantial understanding of the role AI and Machine Learning play when it comes to consumer habits, and how we are able to interact and analyze information to increase deep learning potential for your business.

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