Are you interested in learning how to use some of the most powerful and popular open source AI models and tools to create amazing applications and projects? Do you want to learn how to customize and fine-tune these models and tools for your own needs and preferences? Do you want to learn how to share and distribute your models, integrate them with other applications and services, and update and monitor them? If yes, then this course is for you!
In this course, you will learn how to use some of the main categories and applications of open source AI projects, such as:
Deep Learning Frameworks: These are software libraries that provide the basic building blocks and functionalities for creating and training deep learning models. You will learn how to use some of the most popular open source deep learning frameworks, such as TensorFlow, PyTorch, Keras, and MXNet, and how to compare and contrast them.
Natural Language Processing and Language Models: These are models and tools that deal with the processing and generation of natural language texts, such as text classification, sentiment analysis, named entity recognition, and machine translation. You will learn how to use some of the state-of-the-art open source language models, such as BERT, GPT-3, and T5, and how to fine-tune and customize them for specific tasks and domains.
Computer Vision and Image Processing: These are models and tools that deal with the analysis and manipulation of images, such as object detection, face recognition, and image generation. You will learn how to use some of the cutting-edge open source computer vision and image processing models, such as YOLO, FaceNet, and StyleGAN, and how to fine-tune and modify them for specific tasks and scenarios.
Machine Learning Libraries and Tools: These are software libraries and tools that provide the basic algorithms and functionalities for performing machine learning tasks, such as data preprocessing, feature engineering, model selection, and evaluation. You will learn how to use some of the most widely used open source machine learning libraries and tools, such as scikit-learn, XGBoost, and MLflow, and how to apply them to common machine learning problems.
By the end of this course, you will be able to:
Understand the concepts and principles of open source AI models and tools
Install, configure, and use some of the most popular open source AI models and tools
Fine-tune and customize open source AI models and tools for specific tasks and domains
Create and deploy your own open source AI applications and projects
To follow along with this course, you will need:
A computer with an internet connection and a web browser
A basic knowledge of Python programming and mathematics
A curiosity and enthusiasm for learning and exploring open source AI
This course is designed for anyone who wants to learn and practice open source AI, from beginners to experts, from students to professionals, from hobbyists to enthusiasts. Whether you want to enhance your skills, advance your career, or pursue your passion, this course will help you achieve your goals and dreams.
So what are you waiting for? Join this course today and start your journey with open source AI!
Welcome to the cutting-edge realm of Artificial Intelligence (AI), Generative AI, and you like it or not but to help you leverage this innovation for the betterment of humanity, you need to have Cyber Security, which is to defend the digital landscapes. This comprehensive training program is designed to equip participants with the understanding of these technologies offering a holistic perspective on the transformative power of AI and its associated challenges in the cybersecurity landscape.
Artificial Intelligence stands as a technological juggernaut, reshaping industries and daily life. This training will delve into the core principles of AI, elucidating its diverse applications, from machine learning algorithms that enable intelligent decision-making to natural language processing that enhances human-computer interactions.
Generative AI, a subset of AI, takes the capabilities of machines to new heights by enabling them to create original content, mimic human creativity, and even generate synthetic data. In this training, participants will unravel the mechanisms behind AI, Generative AI and explore its potential, challenges and mechanism to put it for the good
Simultaneously, the rapid evolution of technology brings forth unprecedented challenges in the realm of Cyber Security. As AI and Generative AI advance, so too do the tactics and sophistication of cyber threats. This program will equip participants with the knowledge and skills to safeguard digital environments, understand threat landscapes, and develop robust cybersecurity strategies that leverage the capabilities of AI to stay one step ahead of adversaries.
Join us on this transformative journey, where theoretical insights will help you develop practical strategies, and emerge prepared to navigate the dynamic intersection of AI, Generative AI, and Cyber Security.
Welcome to the cutting-edge realm of Artificial Intelligence (AI), Generative AI, and you like it or not but to help you leverage this innovation for the betterment of humanity, you need to have Cyber Security, which is to defend the digital landscapes. This comprehensive training program is designed to equip participants with the understanding of these technologies offering a holistic perspective on the transformative power of AI and its associated challenges in the cybersecurity landscape.
Artificial Intelligence stands as a technological juggernaut, reshaping industries and daily life. This training will delve into the core principles of AI, elucidating its diverse applications, from machine learning algorithms that enable intelligent decision-making to natural language processing that enhances human-computer interactions.
Generative AI, a subset of AI, takes the capabilities of machines to new heights by enabling them to create original content, mimic human creativity, and even generate synthetic data. In this training, participants will unravel the mechanisms behind AI, Generative AI and explore its potential, challenges and mechanism to put it for the good
Simultaneously, the rapid evolution of technology brings forth unprecedented challenges in the realm of Cyber Security. As AI and Generative AI advance, so too do the tactics and sophistication of cyber threats. This program will equip participants with the knowledge and skills to safeguard digital environments, understand threat landscapes, and develop robust cybersecurity strategies that leverage the capabilities of AI to stay one step ahead of adversaries.
Join us on this transformative journey, where theoretical insights will help you develop practical strategies, and emerge prepared to navigate the dynamic intersection of AI, Generative AI, and Cyber Security.
Course Title: Master 20+ AI Websites: From Image to Video
Course Description:
Welcome to the cutting edge of creative innovation! Dive into the world of artificial intelligence and harness its transformative power to revolutionize your visual content creation. In this comprehensive course, you'll embark on a hands-on journey, mastering over 20 AI-powered websites that seamlessly bridge the gap between static images and captivating videos.
What You'll Learn:
AI for Image Enhancement:
Explore AI tools that enhance and transform static images, turning ordinary visuals into extraordinary masterpieces.
Dynamic Video Creation with AI:
Learn how to leverage AI algorithms to generate dynamic and engaging video content from your enhanced images.
Hands-On Practice with 20+ AI Platforms:
Immerse yourself in practical exercises, guiding you through the functionalities of more than 20 AI websites, each offering unique capabilities.
Optimizing Workflow Efficiency:
Streamline your creative process as you discover tips and techniques for seamlessly integrating AI into your workflow.
AI Ethics and Considerations:
Delve into discussions about the ethical considerations surrounding AI in the creative process and how to use these tools responsibly.
Real-world Applications and Case Studies:
Witness real-world applications of AI-generated visuals and study case studies highlighting successful integration in various industries.
Troubleshooting and Best Practices:
Navigate potential challenges with confidence, armed with troubleshooting skills and industry best practices.
Who Is This Course For:
Content creators seeking to elevate their visuals with cutting-edge AI technology.
Marketers aiming to stay ahead by incorporating AI-generated content in their campaigns.
Video editors eager to explore the fusion of AI and video creation.
Students and educators looking to explore the intersection of AI and creative arts.
Small business owners and entrepreneurs seeking innovative branding solutions.
Requirements:
Basic computer skills and internet access.
A desire to explore the limitless possibilities of AI in creative endeavors.
Enthusiasm for hands-on learning and experimentation.
Unlock the door to a new era of creativity. Enroll now and join us on a transformative journey from static images to dynamic videos with the power of artificial intelligence!
Note: Lifetime access to course materials and updates included.
Course Title: Master 20+ AI Websites: From Image to Video
Course Description:
Welcome to the cutting edge of creative innovation! Dive into the world of artificial intelligence and harness its transformative power to revolutionize your visual content creation. In this comprehensive course, you'll embark on a hands-on journey, mastering over 20 AI-powered websites that seamlessly bridge the gap between static images and captivating videos.
What You'll Learn:
AI for Image Enhancement:
Explore AI tools that enhance and transform static images, turning ordinary visuals into extraordinary masterpieces.
Dynamic Video Creation with AI:
Learn how to leverage AI algorithms to generate dynamic and engaging video content from your enhanced images.
Hands-On Practice with 20+ AI Platforms:
Immerse yourself in practical exercises, guiding you through the functionalities of more than 20 AI websites, each offering unique capabilities.
Optimizing Workflow Efficiency:
Streamline your creative process as you discover tips and techniques for seamlessly integrating AI into your workflow.
AI Ethics and Considerations:
Delve into discussions about the ethical considerations surrounding AI in the creative process and how to use these tools responsibly.
Real-world Applications and Case Studies:
Witness real-world applications of AI-generated visuals and study case studies highlighting successful integration in various industries.
Troubleshooting and Best Practices:
Navigate potential challenges with confidence, armed with troubleshooting skills and industry best practices.
Who Is This Course For:
Content creators seeking to elevate their visuals with cutting-edge AI technology.
Marketers aiming to stay ahead by incorporating AI-generated content in their campaigns.
Video editors eager to explore the fusion of AI and video creation.
Students and educators looking to explore the intersection of AI and creative arts.
Small business owners and entrepreneurs seeking innovative branding solutions.
Requirements:
Basic computer skills and internet access.
A desire to explore the limitless possibilities of AI in creative endeavors.
Enthusiasm for hands-on learning and experimentation.
Unlock the door to a new era of creativity. Enroll now and join us on a transformative journey from static images to dynamic videos with the power of artificial intelligence!
Note: Lifetime access to course materials and updates included.
This comprehensive course is designed to equip you with the skills to effectively utilize Simulation By Deep Neural Operators. We will delve into the essential concepts of solving partial differential equations (PDEs) and demonstrate how to build a simulation code through the application of Deep Operator Network (DeepONet) using data generated by solving PDEs with the Finite Difference Method (FDM).
In this course, you will learn the following skills:
Understand the Math behind Finite Difference Method.
Write and build Algorithms from scratch to sole the Finite Difference Method.
Understand the Math behind partial differential equations (PDEs).
Write and build Machine Learning Algorithms to build Simulation code By Deep Neural Operators using Pytorch.
Write and build Machine Learning Algorithms to build Simulation code By Deep Neural Operators using DeepXDE.
Compare the results of Finite Difference Method (FDM) with the Deep Neural Operator using the Deep Operator Network (DeepONet).
We will cover:
Pytorch Matrix and Tensors Basics.
Finite Difference Method (FDM) Numerical Solution for 1D Heat Equation.
Deep Neural Operator to perform integration of an Ordinary Differential Equations(ODE).
Deep Neural Operator to perform simulation for 1D Heat Equation using Pytorch.
Deep Neural Operator to perform simulation for 1D Heat Equation using DeepXDE.
Deep Neural Operator to perform simulation for 2D Fluid Motion using DeepXDE.
If you lack prior experience in Machine Learning or Computational Engineering, please dont worry. as this course is comprehensive and course, providing a thorough understanding of Machine Learning and the essential aspects of partial differential equations PDEs and Simulation By Deep Neural Operators by applying Deep Operator Network (DeepONet) .
Let's enjoy Learning PINNs together
This comprehensive course is designed to equip you with the skills to effectively utilize Simulation By Deep Neural Operators. We will delve into the essential concepts of solving partial differential equations (PDEs) and demonstrate how to build a simulation code through the application of Deep Operator Network (DeepONet) using data generated by solving PDEs with the Finite Difference Method (FDM).
In this course, you will learn the following skills:
Understand the Math behind Finite Difference Method.
Write and build Algorithms from scratch to sole the Finite Difference Method.
Understand the Math behind partial differential equations (PDEs).
Write and build Machine Learning Algorithms to build Simulation code By Deep Neural Operators using Pytorch.
Write and build Machine Learning Algorithms to build Simulation code By Deep Neural Operators using DeepXDE.
Compare the results of Finite Difference Method (FDM) with the Deep Neural Operator using the Deep Operator Network (DeepONet).
We will cover:
Pytorch Matrix and Tensors Basics.
Finite Difference Method (FDM) Numerical Solution for 1D Heat Equation.
Deep Neural Operator to perform integration of an Ordinary Differential Equations(ODE).
Deep Neural Operator to perform simulation for 1D Heat Equation using Pytorch.
Deep Neural Operator to perform simulation for 1D Heat Equation using DeepXDE.
Deep Neural Operator to perform simulation for 2D Fluid Motion using DeepXDE.
If you lack prior experience in Machine Learning or Computational Engineering, please dont worry. as this course is comprehensive and course, providing a thorough understanding of Machine Learning and the essential aspects of partial differential equations PDEs and Simulation By Deep Neural Operators by applying Deep Operator Network (DeepONet) .
Let's enjoy Learning PINNs together
"Cypress 2024: The Ultimate Automation Testing Course from Scratch" is a compact, pragmatic learning experience tailored for both beginners and experienced testers. This course is focused on the latest in end-to-end, visual, and AI-powered test automation, using Cypress as the primary tool. Starting with Cypress fundamentals, you'll rapidly advance to more complex concepts, ensuring a deep understanding of automated testing.
!!! Please note that the course is a work in progress, with new lectures being added regularly to cover all topics thoroughly!!!
Throughout the course, students will delve into the essentials of a development environment, configuring Cypress with various IDEs, and mastering programming foundations crucial for testers. You will gain proficiency in HTML, JavaScript, and TypeScript, ensuring a solid foundation for advanced testing techniques.
The core of the course is dedicated to Cypress fundamentals, where you will learn to write your first test, understand Cypress's core features, interact with web elements, and implement effective assertions and validations. As the course progresses, you'll explore advanced Cypress configurations, TypeScript applications, session management, and complex tasks like handling pop-ups and frames, clock manipulation, and parallel testing.
A significant portion of the course is devoted to building a robust Cypress framework for end-to-end testing. This includes practical approaches to using fixtures, custom commands, page object design patterns, data management, and dynamic test parameterization.
API testing, a critical component of modern software testing, is covered extensively. You will learn the fundamentals of REST and GraphQL API testing, along with practical examples and advanced techniques. The course also covers database testing strategies and simulating network requests and responses.
The integration of Behavior-Driven Development (BDD) with Cypress, using Cucumber and Mocha, forms a crucial part of the curriculum. This is complemented by a detailed exploration of dashboard services and reporting tools, including Cypress Cloud Dashboard and various reporters like Mochawesome and Allure.
Visual testing, an increasingly important aspect of QA, is thoroughly addressed. You’ll explore various tools and techniques, including snapshot testing and implementations with Percy, Applitools, and Happo.
In a unique twist, the course incorporates AI-driven tools like ChatGPT and GitHub Copilot, teaching you how to optimize test automation with these cutting-edge technologies.
Cross-browser testing is also a significant focus, with practical sessions on using BrowserStack, Docker and setting up local environments for comprehensive test coverage.
A pivotal component of the course is continuous integration (CI) and continuous deployment (CD), where you'll learn about CI/CD fundamentals, and how to integrate Cypress with npm, Jenkins, GitHub Actions, GitLab CI, CircleCI, and Docker.
Finally, the course wraps up with best practices in Cypress testing and a section dedicated to interview preparation, offering tips, strategies, and insights for career advancement in the testing domain.
This course is ideal for anyone looking to deepen their understanding of test automation and stay ahead in the rapidly evolving field of automated testing. Whether you’re starting from scratch or looking to upgrade your skills, Cypress is the ultimate course to future-proof your testing career.
"Cypress 2024: The Ultimate Automation Testing Course from Scratch" is a compact, pragmatic learning experience tailored for both beginners and experienced testers. This course is focused on the latest in end-to-end, visual, and AI-powered test automation, using Cypress as the primary tool. Starting with Cypress fundamentals, you'll rapidly advance to more complex concepts, ensuring a deep understanding of automated testing.
!!! Please note that the course is a work in progress, with new lectures being added regularly to cover all topics thoroughly!!!
Throughout the course, students will delve into the essentials of a development environment, configuring Cypress with various IDEs, and mastering programming foundations crucial for testers. You will gain proficiency in HTML, JavaScript, and TypeScript, ensuring a solid foundation for advanced testing techniques.
The core of the course is dedicated to Cypress fundamentals, where you will learn to write your first test, understand Cypress's core features, interact with web elements, and implement effective assertions and validations. As the course progresses, you'll explore advanced Cypress configurations, TypeScript applications, session management, and complex tasks like handling pop-ups and frames, clock manipulation, and parallel testing.
A significant portion of the course is devoted to building a robust Cypress framework for end-to-end testing. This includes practical approaches to using fixtures, custom commands, page object design patterns, data management, and dynamic test parameterization.
API testing, a critical component of modern software testing, is covered extensively. You will learn the fundamentals of REST and GraphQL API testing, along with practical examples and advanced techniques. The course also covers database testing strategies and simulating network requests and responses.
The integration of Behavior-Driven Development (BDD) with Cypress, using Cucumber and Mocha, forms a crucial part of the curriculum. This is complemented by a detailed exploration of dashboard services and reporting tools, including Cypress Cloud Dashboard and various reporters like Mochawesome and Allure.
Visual testing, an increasingly important aspect of QA, is thoroughly addressed. You’ll explore various tools and techniques, including snapshot testing and implementations with Percy, Applitools, and Happo.
In a unique twist, the course incorporates AI-driven tools like ChatGPT and GitHub Copilot, teaching you how to optimize test automation with these cutting-edge technologies.
Cross-browser testing is also a significant focus, with practical sessions on using BrowserStack, Docker and setting up local environments for comprehensive test coverage.
A pivotal component of the course is continuous integration (CI) and continuous deployment (CD), where you'll learn about CI/CD fundamentals, and how to integrate Cypress with npm, Jenkins, GitHub Actions, GitLab CI, CircleCI, and Docker.
Finally, the course wraps up with best practices in Cypress testing and a section dedicated to interview preparation, offering tips, strategies, and insights for career advancement in the testing domain.
This course is ideal for anyone looking to deepen their understanding of test automation and stay ahead in the rapidly evolving field of automated testing. Whether you’re starting from scratch or looking to upgrade your skills, Cypress is the ultimate course to future-proof your testing career.
Embark on a transformative journey in the world of AI-driven art with 'Midjourney Mastery: Unleash Your Inner Artist', a course meticulously designed to usher you into the innovative realm of image generation using Midjourney. This comprehensive guide not only introduces you to the foundational aspects of AI models and their significance but also provides a deep dive into detecting AI-generated images, showcasing the intricacies of working with Midjourney, its benefits, challenges, and practical tips for optimal utilization.
Discover the synergy between Discord and Midjourney as we walk you through the setup, installation, and subscription processes, unraveling why Midjourney's integration with Discord is pivotal for your artistic journey. Delve into the world of Midjourney commands, learning how to create your own server, understand various prompts, commands, and explore the extensive range of variations available to tailor your artistic output.
The course doesn’t stop there; it arms you with pro tips, parameters adjustments, and the knowledge to generate images in Anime form, ensuring you have a holistic understanding of what AI art entails. We also broaden your horizon with insights into other AI tools, ensuring you are well-equipped in the wider AI landscape.
Photography enthusiasts and UI designers are not left out, as we cover categories of images, street photography, UI designs, product photography, and the use of modifiers, providing a rounded education to elevate your artistic capabilities.
Join us on this exciting journey, and transform from a novice to a seasoned artist, mastering the art of AI-driven image generation with Midjourney.