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Udemy
Chat GPT for Public Speaking: Craft, Captivate, Conquer (AI)
beginner
AI in Education
Welcome to the "Chat GPT for Public Speaking" course, where the power of artificial intelligence meets the art of persuasive communication. This comprehensive course is designed to transform you into a dynamic and influential public speaker In today's fast-paced world, the ability to convey ideas, captivate audiences, and inspire action is a skill in high demand. Whether you're a professional, a business leader, or an aspiring communicator, this workshop offers invaluable insights into mastering speechcraft. Our journey begins by introducing you to Chat GPT, the AI genius ready to be your speechwriting partner. You'll discover how Chat GPT can help you brainstorm and refine speech topics effortlessly. Say goodbye to writer's block as you unleash a flood of inspiration! Next, you'll master the SPEAKING UP framework, a systematic approach to crafting speeches that engage and resonate. From setting the perfect tone to structuring your content for maximum influence, you'll gain the skills to captivate any audience. We'll dive deep into topics, research, and content creation, infusing stories and personalizing your voice. You'll learn to construct powerful speeches that move people and drive action At the end, you'll compile all elements of the SPEAKING UP framework and insights gained throughout your journey. You'll leave with not just knowledge but the confidence to craft speeches that inspire, persuade, and captivate. Join us in the revolution of AI-driven public speaking. Enroll now and become a true wordsmith, equipped to make an impact with every speech you deliver. NOTE: This course is built upon helping with the speech creation process, NOT the techniques of "performing" your speech in front of a live audience.
Udemy
Develop AI Apps, Automations & Chatbots [No-code x ChatGPT]
beginner
AI in Business
Welcome to a groundbreaking course that’s set to revolutionize the way you work, earn, and create in the digital age. “Build AI Apps, Automations & Chatbots [No-code x ChatGPT]” is not just a learning experience; it’s a doorway to untapped opportunities in the realm of AI, designed for the visionary, the innovator, and the game-changer. Why This Course? - Monetization Mastery: Learn how to monetize AI solutions and turn your newfound skills into revenue streams. - Expert Instructors: Benefit from the combined expertise of Khadin Akbar and Muhammad Afzal, who bring over 200,000 students’ worth of teaching experience. - Practical Projects: Apply your knowledge to real-world scenarios, building AI systems that not only impress but also perform. Course Curriculum Deep Dive: - Introduction: Set the stage with an understanding of VectorShift’s role in the AI landscape and how it can be a game-changer for your income potential. - VectorShift Essentials: Explore the core features like pipelines, storage, and chatbots, and learn how they can be leveraged for financial gain. - Pipeline Proficiency: Master the creation of pipelines and discover how each node type can contribute to more efficient and profitable AI applications. - E-Commerce Enhancements: Dive into AI for e-commerce and uncover strategies to enhance customer experience and drive sales, directly impacting your bottom line. - Website Wisdom: Equip yourself with AI tools for business, real estate, and consultancy websites to provide top-tier services and maximize earnings. - WhatsApp Wonders: Integrate AI chatbots with WhatsApp to open up new channels for monetization and customer engagement. - Email Excellence: Set up an AI-based email support system that not only saves time but also opens up avenues for scalable business models. …and that’s just the start! With content creation automation, lead generation techniques, and competitive research tools, you’ll be well on your way to building a portfolio of profitable AI solutions. What’s in It for You? - Career Advancement: Propel your career forward with skills that are in high demand in today’s tech-driven marketplace. - Income Opportunities: Discover innovative ways to monetize your skills and knowledge through AI-driven applications and services. - Community and Support: Join a community of like-minded individuals and receive ongoing support to ensure your success in the AI space. So if you are ready to embark on this transformative journey? Enroll now in “Build AI Apps, Automations & Chatbots [No-code x ChatGPT]” and start building not just AI solutions, but a future where your skills translate into tangible success.
Udemy
Guida ai Linguaggi C e C++17
intermediate
Machine Learning
If you are new to programming, this course is for you. Even if you already know another programming language but want to learn C/C++, you will still find everything you need in this course. The first section of the course, which I offer you as a bonus, is a sort of course within the course... You will in fact learn in depth the Object-Oriented Paradigm in all its main aspects, according to a path that I have drawn from my (alas) many years of experience in the field as an object-oriented analyst and designer. The skills that you will acquire in the theoretical lessons of this first section are also valid for any object-oriented language, such as Python, C#, Swift, C++. The course is then made up of two parts . In the first part, the C programming language is explained , starting from scratch, in a way that is easy to understand even for those with little or no programming experience. In the second part , the C++17 programming language is explained in detail , as an extension to the C language introduced in the first part. By purchasing this course, you will actually participate in two programming courses : a C course (version 11) and a C++ course (version 17). Why should you learn to program in C and C++? First of all, C is the language from which many other programming languages ​​have been derived (including in particular Java, C++, C#, Swift, Objective-C) which are by far among the most used in the world: knowing C will allow you to access these languages ​​much more easily - and with a level of depth that cannot be achieved in these languages ​​without first really knowing the syntax of C. Furthermore, despite C having been introduced to the market in the late 70s (!), the TIOBE index (the main index measuring the diffusion of programming languages ​​in the world) elected C as the language of the year 2017 , as it was the language that has grown the most in terms of use. Knowing the C language, through this course, will also allow you to learn the main mechanisms of software programming in general. Furthermore, given the very nature of the language, you will also learn how "low level" programming occurs, that is, at the level where it becomes important to be aware of the architecture of the CPU and the computer's memory, to obtain optimized and extremely high-performance code. Learning to develop in C++ will then lead you to know and use object-oriented programming , and to master one of the most powerful programming languages ​​in the world . What you will learn in this course First things first: this course is not a long generic tutorial on the C/C++ language: it is a real guide in which every single element of both languages ​​is examined, defined, illustrated and explained in detail. The topics themselves have been arranged in an order that allows you to understand each of the two languages ​​in a progressive but complete way. While this course is an in-depth guide to the C language (version 11, the most recent), and the C++ language (version 17, also the most recent), nothing has been taken for granted: each topic is introduced with the understanding that you may have no programming experience whatsoever. In particular, in this course you will learn in depth: - Using the open-source GNU C and C++ compiler, and an online C/C++ compiler - The general architecture of a computer and a compiler - Variables, constants, and basic data types of the C language - Arithmetic operators - Arrays (one-dimensional and multidimensional) - The enumerations - The structures - The unions - Control structures (conditional and iteration) - Designing the functions - Using pointers (in all its aspects, even the most advanced ones) - The memorization classes - Using preprocessor directives - I Namespace e gli Stream in C++ - Classes and Objects in C++ A very large section of the course was dedicated to the description of pointers, one of the most important - but also one of the most complex - topics that we face when learning the C language. Your instructor, Alessandro Bemporad, has personally designed and programmed complex software systems in the C and C++ languages ​​for many years - which were actually his first programming languages! - and therefore knows the subject of this course very well.
Udemy
AI Essentials: Introduction to Artificial Intelligence
beginner
AI in Business
Welcome to course: AI Essentials: A Simple Introduction to Artificial Intelligence Technologies by MTF Institute Course provided by MTF Institute of Management, Technology and Finance MTF is the global educational and research institute with HQ at Lisbon, Portugal, focused on business & professional hybrid (on-campus and online) education at areas: Business & Administration, Science & Technology, Banking & Finance. MTF R&D center focused on research activities at areas: Artificial Intelligence, Machine Learning, Data Science, Big Data, WEB3, Blockchain, Cryptocurrency & Digital Assets, Metaverses, Digital Transformation, Fintech, Electronic Commerce, Internet of Things. MTF is the official partner of: IBM, Intel, Microsoft, member of the Portuguese Chamber of Commerce and Industry. MTF is present in 208 countries and has been chosen by more than 380,000 students. Hello everyone, and welcome to our course in Artificial Intelligence (AI)! My name is Mohamed Elfateh, I have been working in the Information Technology field for over a decade. I am interested in learning about modern technologies and sharing my knowledge with others. What is AI? AI is a field of computer science that studies how to create machines that can process information, make decisions, and perform specific tasks. The History of modern AI The field of artificial intelligence (AI) has a long and rich history, dating back to the early days of computing. However, the field as we know it today was founded in 1956 at a conference at Dartmouth College in New Hampshire. This conference brought together the leading researchers in AI at the time, including Alan Turing, John McCarthy, and Marvin Minsky. The conference is credited with helping to define the field of AI and to set the agenda for future research. Artificial Intelligence “AI” is a complex field that needs the ability of people from diverse disciplines to work together. As an example, manufacturing autonomous vehicles like self-driving cars requires the work of people from different fields, such as AI Researchers, Automotive Engineers, and Computer Vision Researchers. AI Researchers develop algorithms that enable self-driving cars to perceive their surroundings, make decisions, and control their movements. Automotive Engineers develop the hardware and software systems that are needed to implement these algorithms, and Computer Vision Researchers develop new techniques for enabling self-driving cars to see and understand the world. What is Machine Learning? Machine Learning is a type of Artificial Intelligence (AI) that allows computers to learn from data without explicit programming. In other words, machine learning algorithms can recognize patterns and make predictions based on data, without getting a command. This enables computers to learn new tasks and improve their performance over time without human intervention. Where is Machine Learning used? Machine learning is in use by a wide range of applications, including email filtering, Social Media Personalization, Image Recognition, Speech Recognition, fraud detection, Text prediction, Product recommendation, medical diagnosis, Healthcare Personalization, Traffic Prediction. Neural networks are a type of machine learning algorithm that is inspired by the structure and function of the human brain. Neural networks can learn complex patterns from data. Neural networks have been successfully used in areas such as natural language processing. Deep Learning is a type of machine learning that uses neural networks with multiple layers. Each layer consists of multiple nodes that can perform diverse tasks. This allows deep learning models to learn more complex patterns from data. Deep learning has been used to achieve significant results in a wide range of tasks, including image recognition, speech recognition, and machine translation.
Udemy
Deploy machine learning models on Google Cloud AI Platform
beginner
AI in Education
My Course is meant for anyone who already knows how to build both machine and deep learning models that is interested in deploying them easily on Google Cloud AI Platform. So that they can send the deployed models post requests. Also you must be familiar with Natural Language Processing and some basic cloud concepts. I will explain everything in the videos. But most importantly you do not need to be an expert in python to do this. However this is again intended for those who already know how to build models with scikitlearn and tensorflow. Because these are the frameworks we will be using and selecting for deployment. Be sure when you do it to select the correct frameworks or you will most likely not be able to deploy your model. That I will also explain in these featured videos. But more importantly enjoy your time learning because should be a very smooth course. If you pay attention you will easily pass my quizzes. Again this is intermediate level not advanced or basic. In this video we will be doing predictions not in jupyter lab with the notebook but be sending post requests to the deployed model. You will mostly be sending post requests to classifiers and regressors the majority of the time. Also in this video you will learn how to build an very accurate neural network for predicting sentiment with the IMDB movie reviews dataset. Then you will deploy it. The datasets we will be working with are the malware dataset from kaggle, the car price dataset from kaggle, and the car purchase dataset from kaggle. However feel free to use your own datasets since you know how to build models. In fact that is strongly encouraged.
Udemy
AI MBA- 25 Courses in 1: ChatGPT, Midjourney, Prompt Mastery
beginner
AI in Education
Embark on an unparalleled journey into the heart of artificial intelligence with our AI MBA – a comprehensive, all-encompassing masterclass designed to unlock the full potential of AI technology and its applications in the digital world. This unique program amalgamates over 25 meticulously curated courses into one monumental learning experience, ensuring you gain mastery over the most cutting-edge AI tools and methodologies.
Udemy
AI-900 - Fundamentos de Microsoft Azure AI
beginner
AI in Education
This course introduces fundamental concepts related to artificial intelligence (AI) and services in Microsoft Azure that can be used to build AI solutions. The course is not designed to teach students how to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience. The hands-on exercises in the course are based on Learning Modules, and students are encouraged to use the content as reference materials to reinforce what they learn in class and explore the topics in greater depth. The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solutions that artificial intelligence (AI) makes possible and the services in Microsoft Azure that you can use to build them. You don't need to have any experience using Microsoft Azure before taking this course, but a basic level of familiarity with computing technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret graphs. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful. The course is based entirely on the official Microsoft AI-900 - Microsoft Azure AI Fundamentals material . I hope you can pass the exam with the different aids that I will present to you. The course includes PDF study material for the exam. I wish you much success! THIS COURSE IS FOR EXCLUSIVE USE ON THE UDEMY PLATFORM. ITS COMMERCIALIZATION IS PROHIBITED.
Udemy
From Deep Learning CV Engg. to Ai Resercher - Ai Expert TM
intermediate
AI in Business
Embark on a transformative learning journey designed to elevate your expertise from a Deep Learning Engineer to a globally recognized AI Researcher. This comprehensive course is meticulously crafted to provide you with the skills, knowledge, and strategic mindset essential for making a significant impact on the forefront of artificial intelligence research. Deep Learning Fundamentals Review Refresh your understanding of core deep learning concepts, frameworks, and model architectures. Dive into advanced topics, including neural network architectures, optimization techniques, and transfer learning. Expanding into Broader AI Domains Broaden your expertise by exploring diverse AI domains such as natural language processing, computer vision, reinforcement learning, and robotics. Analyze real-world applications and challenges in each domain to foster a comprehensive understanding. Strengthening Mathematical Foundations Deepen your mathematical knowledge with a focus on linear algebra, calculus, probability, and statistics. Apply advanced mathematical concepts to analyze, optimize, and innovate within machine learning algorithms. Pursuing Advanced Education in AI Consider advanced education options such as pursuing a master's or Ph.D. in AI or a related field. Engage with leading researchers, attend conferences, and explore opportunities for research collaboration. Engaging in Research Projects Participate in hands-on research projects to apply theoretical knowledge to real-world scenarios. Collaborate with experienced researchers and mentors to develop practical research skills. Navigating Research Methodologies Master effective research methodologies specific to AI, including experimental design, data collection, and analysis. Formulate impactful research questions and hypotheses to drive innovative projects. Building a Strong Research Portfolio Craft a comprehensive research portfolio showcasing your achievements, projects, and contributions. Learn the art of effective communication to present research findings to both technical and non-technical audiences. Specialization in Niche Areas Identify a specific niche within AI that aligns with your passion and strengths. Develop deep expertise in your chosen area, contributing unique insights to advance the field. Continuous Learning and Innovation Embrace a culture of continuous learning to stay updated on the latest AI research trends. Foster innovation by exploring novel ideas, experimenting with new approaches, and pushing the boundaries of existing knowledge. Recognition and Contribution to AI Community Strategically position yourself for recognition within the AI community through conference presentations, awards, and active participation. Give back to the community by mentoring aspiring researchers and contributing to educational initiatives. Key Takeaways Mastery of advanced AI concepts, methodologies, and mathematical foundations. Hands-on experience in executing impactful research projects. Strategic networking and collaboration skills within the global AI community. Expertise in niche areas of AI research. Graduation with a robust research portfolio and recognition as a top-tier AI researcher. Who Should Enroll Deep Learning Engineers aiming to transition into AI research and make substantial contributions to the field. Experienced professionals seeking to elevate their careers by becoming globally recognized AI researchers. Enroll now in "Mastering the Transition" and take the definitive step towards making a lasting impact on the forefront of artificial intelligence research. Unleash your potential and join a community dedicated to shaping the future of AI research! Courtesy, Dr. FAK Noble Ai Researcher, Scientists, Product Developer, Innovator & Pure Consciousness Expert Founder of Noble Transformation Hub TM
Kennesaw State University
Ethical AI Use
beginner
AI in Finance
The "Ethical AI Use" course delves into the critical intersection of technology and ethics, focusing on the responsible development and deployment of artificial intelligence (AI). Participants will explore the evolution of AI, distinguishing between the two fundamental types, and examine the ethical considerations inherent in the realm of generative AI. Through a combination of theoretical discussions and practical exercises, students will learn about the intricate process of prompt engineering, which involves crafting inputs to guide AI systems towards ethically sound outputs. They will investigate the four qualifiers that govern AI output and master the techniques of proper prompting to ensure adherence to ethical standards. Drawing from real-world examples, including case studies centered on images, participants will analyze the ethical implications of AI applications and develop a comprehensive understanding of the ethical wheel guiding prompt engineering decisions. Ultimately, students will come to appreciate prompt engineering as both a skill and an art, essential for the ethical use of AI in various domains. This course equips participants with the knowledge and tools necessary to navigate the ethical complexities of AI, empowering them to contribute positively to the development and implementation of AI technologies in society.
Google Cloud
Responsible AI for Digital Leaders with Google Cloud
beginner
AI in Education
This course equips learners with the essential knowledge and practical tools to develop and implement artificial intelligence (AI) responsibly. Through an exploration of ethical considerations, best practices, and governance procedures, participants will gain an understanding of how to navigate the complex landscape of AI while upholding ethical standards and minimizing potential risks.
Michigan University
AI-Powered Data Analysis: A Practical Introduction
beginner
Data Science for AI
As generative artificial intelligence (AI) reshapes our world, the ability to analyze data is quickly becoming as fundamental as reading and writing. “AI-Powered Data Analysis: A Practical Introduction” explores how AI tools like ChatGPT are revolutionizing our approach to data, making advanced analysis accessible to everyone. Whether you're a complete novice or looking to enhance your skills, you'll learn how to navigate this new terrain. You'll learn to think critically about the context of data analysis, delve into the specifics of analyzing and visualizing data using AI, and consider broader factors that support but are not directly part of data analysis. This practical approach focuses on generative AI tools, ensuring you know how to ask the right questions to avoid common mistakes. Your final activity will allow you to set yourself up for continued learning with a prepared Python environment and data sets, which you can voluntarily showcase on GitHub—a code-sharing hub. By the end of this course, you'll be adept at using AI tools to analyze data effectively and seamlessly apply these skills to future projects.
AWS
Security, Compliance, and Governance for AI Solutions
beginner
AI in Education
This course helps you understand some common issues of around security, compliance, and governance associated with artificial intelligence (AI) solutions. You will learn how to recognize governance and compliance requirements for AI systems. You will also learn about various Amazon Web Services (AWS) services and features that will help you apply governance controls and achieve your compliance objectives. Finally, you will be introduced to AWS services that can help you secure your AI systems.
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