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Videos uploaded by user “intrigano”
Firewall Stateful versus Stateless
 
05:29
Real-Time Cyber Threat Detection and Mitigation Module 1 Basic Network Security This module introduces the basics of TCP/IP for security, including firewall design and use. Learning Objectives • Explain the pros and cons of security through obscurity • Summarize the basics of TCP/IP for cyber security • Examine basic TCP/IP hacks including spoofs and floods • Define firewall and basic operation • Differentiate between stateful and stateless firewall operation About this course: This course introduces real-time cyber security techniques and methods in the context of the TCP/IP protocol suites. Explanation of some basic TCP/IP security hacks is used to introduce the need for network security solutions such as stateless and stateful firewalls. Learners will be introduced to the techniques used to design and configure firewall solutions such as packet filters and proxies to protect enterprise assets. Perimeter solutions such as firewalls and intrusion prevention systems are shown to have significant drawbacks in common enterprise environments. The result of such weakness is shown to often exist as advanced persistent threats (APTs) from nation-state actors. Such attacks, as well as DDOS and third-party attacks, are shown to have potential solutions for modern enterprise. Subscribe at: https://www.coursera.org/learn/intro-cyber-attacks/home/welcome https://www.coursera.org
Views: 12838 intrigano
Introduction to IT Support - What does an IT Support Specialist do
 
02:32
Google IT Support Professional Certificate https://www.coursera.org/specializations/google-it-support This six-course certificate, developed exclusively by Google, includes innovative curriculum designed to prepare you for an entry-level role in IT support. A job in IT can mean in-person or remote help desk work, either in a small business or at a global company, like Google. Whether you’ve been tinkering with IT or are completely new to the field, you’ve come to the right place. If you’re looking for a job, upon completion of the certificate, you can share your information with top employers, like Bank of America, Walmart, Sprint, GE Digital, PNC Bank, Infosys, TEKsystems, UPMC, and, of course, Google. Through a dynamic mix of video lectures, quizzes, and hand-on labs and widgets, this program will introduce you to troubleshooting and customer service, networking, operating systems, system administration, automation, and security. Along the way, you’ll hear from Googlers with unique backgrounds and perspectives, whose own foundation in IT support served as a jumping off point for their careers. They’re excited to go on this journey with you, as you invest in your future by achieving an end-of-program certificate. Course 1 - IT Technical Support Fundamentals In this course, you’ll be introduced to the world of Information Technology, or IT. This course is the first of a series that aims to prepare you for a role as an entry-level IT Support Specialist. You’ll learn about the different facets of Information Technology, like computer hardware, the Internet, computer software, and job-related skills. You’ll also learn about the history of computers, and the pioneers who shaped the world of computing that we know today. This course covers a wide variety of topics in IT that are designed to give you an overview of what’s to come in this IT Support Professional Certificate. By the end of this course, you’ll be able to: - understand how the binary system works. - assemble a computer from scratch. - choose and install an operating system on a computer. - understand what the Internet is, how it works, and the impact it has in the modern world. - learn how applications are created and how they work under the hood of our computer. - utilize common problem-solving methodologies and soft skills in an Information Technology setting. Who is this class for: This program is intended for beginners who are interested in developing the skills necessary to perform entry-level IT support. No pre-requisite knowledge is required. However, if you do have some familiarity with IT, you can skip through
Views: 10032 intrigano
Software security - Return Oriented Programming -  ROP
 
11:14
software security - Return Oriented Programming - ROP To get certificate subscribe at: https://www.coursera.org/learn/software-security ================================== Software Security playlist: https://www.youtube.com/playlist?list=PL2jykFOD1AWY1E3MB38_uOfpvEf4gnW80 ================================== About this course: This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a "build security in" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems. Successful learners in this course typically have completed sophomore/junior-level undergraduate work in a technical field, have some familiarity with programming, ideally in C/C++ and one other "managed" program language (like ML or Java), and have prior exposure to algorithms. Students not familiar with these languages but with others can improve their skills through online web tutorials.
Views: 14093 intrigano
Neural Networks - Networks in Networks and 1x1 Convolutions
 
06:40
Convolutional Neural Networks About this course: This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization. Who is this class for: - Learners that took the first two courses of the specialization. The third course is recommended. - Anyone that already has a solid understanding of densely connected neural networks, and wants to learn convolutional neural networks or work with image data. Deep convolutional models: case studies Learn about the practical tricks and methods used in deep CNNs straight from the research papers. Learning Objectives • Understand multiple foundational papers of convolutional neural networks • Analyze the dimensionality reduction of a volume in a very deep network • Understand and Implement a Residual network • Build a deep neural network using Keras • Implement a skip-connection in your network • Clone a repository from github and use transfer learning Subscribe at: https://www.coursera.org Upcoming events/projects: Cyber Security Summer Camp in Georgia Bakuriani for school students; 11-18 years old; as the trainers and counselors are involved leading cyber security experts and professors. Working language is English. https://scsa.ge/en/international-cyber-camp-2/ ---------------------------------------- We offer you website development, penetration testing and cryptanalysis; Our team consists of professionals. To work with us is always comfortable and easy because our job is our pleasure. https://utoweb.com/en/main/ https://scsa.ge/en/ ----------------------------------------- We invite you to publish your articles in our peer-review International Scientific Cyber Security Journal; publication is free. www.journal.scsa.ge ----------------------------------------- If you like our channel and would like to support our work please donate. We are working for you! https://www.paypal.me/cyberassociatio
Views: 17872 intrigano
Networking -  The TCPIP Five Layer Network Model
 
05:15
Google IT Support Professional Certificate https://www.coursera.org/specializations/google-it-support https://www.facebook.com/cyberassociation/ This six-course certificate, developed exclusively by Google, includes innovative curriculum designed to prepare you for an entry-level role in IT support. A job in IT can mean in-person or remote help desk work, either in a small business or at a global company, like Google. Whether you’ve been tinkering with IT or are completely new to the field, you’ve come to the right place. If you’re looking for a job, upon completion of the certificate, you can share your information with top employers, like Bank of America, Walmart, Sprint, GE Digital, PNC Bank, Infosys, TEKsystems, UPMC, and, of course, Google. Course 2 - The Bits and Bytes of Computer Networking (Module 1 Introduction to Networking) About the Course This course is designed to provide a full overview of computer networking. In this course, we’ll cover everything from the fundamentals of modern networking technologies and protocols to practical applications and network troubleshooting. By the end of this course, you’ll be able to: - describe computer networks in terms of a five-layer model. - understand all of the standard protocols involved with TCP/IP communications. - grasp powerful network troubleshooting tools and techniques. - learn network services like DNS and DHCP that help make computer networks run. Except as otherwise noted. Who is this class for: This program is intended for beginners who are interested in developing the skills necessary to perform entry-level IT support. No pre-requisite knowledge is required. However, if you do have some familiarity with IT, you can skip through any content that you might already know. Course 2 consists of 6 modules Module 1 Introduction to Networking Module 2 The Network Layer Module 3 The Transport and Application Layers Module 4 Networking Services Module 5 Connecting to the Internet Module 6 Troubleshooting and the Future of Networking In the first module of this course, we will cover the basics of computer networking. We will learn about the TCP/IP and OSI networking models and how the network layers work together. We'll also cover the basics of networking devices such as cables, hubs and switches, routers, servers and clients. We'll also explore the physical layer and data link layer of our networking model in more detail. By the end of this module, you will know how all the different layers of the network model fit together to create a network. Learning Objectives • Describe how the TCP/IP five layer network model works. • Identify basic networking devices. • Label each of the five layers in the TCP/IP network model. • Describe how the physical layer works. • Describe how the data link layer works.
Views: 5473 intrigano
Bitcoin - Proof of Stake Virtual Mining
 
08:07
Proof of Stake Virtual Mining - Bitcoin and Cryptocurrency Technologies Part 8 - Alternative Mining Puzzles Not everyone is happy about how Bitcoin mining works: its energy consumption and the fact that it requires specialized hardware are major sticking points. This week we'll look at how mining can be re-designed in alternative cryptocurrencies. Upcoming events/projects: Cyber Security Summer Camp in Georgia Bakuriani for school students; 11-18 years old; as the trainers and counselors are involved leading cyber security experts and professors. Working language is English. https://scsa.ge/en/international-cyber-camp-2/ ---------------------------------------- We offer you website development, penetration testing and cryptanalysis; Our team consists of professionals. To work with us is always comfortable and easy because our job is our pleasure. https://utoweb.com/en/main/ https://scsa.ge/en/ ----------------------------------------- We invite you to publish your articles in our peer-review International Scientific Cyber Security Journal; publication is free. www.journal.scsa.ge ----------------------------------------- If you like our channel and would like to support our work please donate. We are working for you! https://www.paypal.me/cyberassociatio
Views: 31100 intrigano
43 Quantum Mechanics - Quantum factoring   Period finding
 
19:28
Quantum Mechanics and Quantum Computation - Quantum factoring Period finding
Views: 9627 intrigano
Linear Algebra – What are eigenvalues and eigenvectors
 
04:25
Mathematics for Machine Learning: Linear Algebra, Module 5 Eigenvalues and Eigenvectors Application to Data Problems To get certificate subscribe at: https://www.coursera.org/learn/linear-algebra-machine-learning/home/welcome ============================ Mathematics for Machine Learning: Linear Algebra: https://www.youtube.com/playlist?list=PL2jykFOD1AWazz20_QRfESiJ2rthDF9-Z ============================ Youtube channel: https://www.youtube.com/user/intrigano ============================ https://scsa.ge/en/online-courses/ https://www.facebook.com/cyberassociation/ About this course: In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works. Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before. At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning. Who is this class for: This course is for people who want to refresh their maths skills in linear algebra, particularly for the purposes of doing data science and machine learning, or learning about data science and machine learning. We look at vectors, matrices and how to apply these to solve linear systems of equations, and how to apply these to computational problems. ________________________________________ Created by: Imperial College London Module 5 Eigenvalues and Eigenvectors Application to Data Problems Eigenvectors are particular vectors that are unrotated by a transformation matrix, and eigenvalues are the amount by which the eigenvectors are stretched. These special 'eigen-things' are very useful in linear algebra and will let us examine Google's famous PageRank algorithm for presenting web search results. Then we'll apply this in code, which will wrap up the course. Learning Objectives • Identify geometrically what an eigenvector/value is • Apply mathematical formulation in simple cases • Build an intuition of larger dimention eigensystems • Write code to solve a large dimentional eigen problem
Views: 1862 intrigano
Multivariate Calculus – The Hessian
 
05:40
Course 2 - Mathematics for Machine Learning Multivariate Calculus, Module 2 Multivariate calculus To get certificate subscribe at: https://www.coursera.org/learn/multivariate-calculus-machine-learning ============================ Mathematics for Machine Learning: Multivariate Calculus https://www.youtube.com/playlist?list=PL2jykFOD1AWaL4_-bdidPfIWe765jOgfL ============================ Youtube channel: https://www.youtube.com/user/intrigano ============================ https://scsa.ge/en/online-courses/ https://www.facebook.com/cyberassociation/ About this course: This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster. Next, we learn how to calculate vectors that point up hill on multidimensional surfaces and even put this into action using an interactive game. We take a look at how we can use calculus to build approximations to functions, as well as helping us to quantify how accurate we should expect those approximations to be. We also spend some time talking about where calculus comes up in the training of neural networks, before finally showing you how it is applied in linear regression models. This course is intended to offer an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck. Hopefully, without going into too much detail, you’ll still come away with the confidence to dive into some more focused machine learning courses in future. Who is this class for: This class is for people who would like to learn more about machine learning techniques, but don’t currently have the fundamental mathematics in place to go into much detail. This course will include some exercises that require you to work with code. If you've not had much experience with code before DON'T PANIC, we will give you lots of guidance as you go. Module 2 Multivariate calculus Building on the foundations of the previous module, we now generalise our calculus tools to handle multivariable systems. This means we can take a function with multiple inputs and determine the influence of each of them separately. It would not be unusual for a machine learning method to require the analysis of a function with thousands of inputs, so we will also introduce the linear algebra structures necessary for storing the results of our multivariate calculus analysis in an orderly fashion. Learning Objectives • Recognize that differentiation can be applied to multiple variables in an equation • Use multivariate calculus tools on example equations • Recognise the utility of vector/matrix structures in multivariate calculus • Examine two dimensional problems using the Jacobian
Views: 3525 intrigano
Neural Networks - Bounding Box Predictions
 
14:32
Convolutional Neural Networks About this course: This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization. Who is this class for: - Learners that took the first two courses of the specialization. The third course is recommended. - Anyone that already has a solid understanding of densely connected neural networks, and wants to learn convolutional neural networks or work with image data. Object detection Learn how to apply your knowledge of CNNs to one of the toughest but hottest field of computer vision: Object detection. Learning Objectives • Understand the challenges of Object Localization, Object Detection and Landmark Finding • Understand and implement non-max suppression • Understand and implement intersection over union • Understand how we label a dataset for an object detection application • Remember the vocabulary of object detection (landmark, anchor, bounding box, grid, ...) Subscribe at: https://www.coursera.org
Views: 13973 intrigano
The objectivity of Swiss Design
 
06:09
history of design Module 4 - Graphic Design Radicalism - Swiss Design Design practice in the late 1950s to early 1970s was new, radical and divergent. To show you just how varied it was, we’ll look at the work of four key players/movements. To get certificate subscribe at: https://www.coursera.org/specializations/graphic-design ============================ history of design https://www.youtube.com/playlist?list=PL2jykFOD1AWb7hNucP2fj491MQ594G3Rk ============================ Youtube channel: https://www.youtube.com/user/intrigano ============================ https://scsa.ge/en/online-courses/ https://www.facebook.com/cyberassociation/ Ideas from the History of Graphic Design About this course: This condensed survey course focuses on four key periods or themes from the history of design. Together we’ll trace the emergence of design as a recognized practice, why things look the way they do, and how designers approached specific design problems in their work. This is an essential course for emerging designers entering the field, or for students interested in learning more about visual culture and analysis. No previous experience is required.
Views: 2727 intrigano
python - Parsing XML in Python
 
12:21
Programming for Everybody - Parsing XML in Python Upcoming events/projects: Cyber Security Summer Camp in Georgia Bakuriani for school students; 11-18 years old; as the trainers and counselors are involved leading cyber security experts and professors. Working language is English. https://scsa.ge/en/international-cyber-camp-2/ ---------------------------------------- We offer you website development, penetration testing and cryptanalysis; Our team consists of professionals. To work with us is always comfortable and easy because our job is our pleasure. https://utoweb.com/en/main/ https://scsa.ge/en/ ----------------------------------------- We invite you to publish your articles in our peer-review International Scientific Cyber Security Journal; publication is free. www.journal.scsa.ge ----------------------------------------- If you like our channel and would like to support our work please donate. We are working for you! https://www.paypal.me/cyberassociatio
Views: 25378 intrigano
cryptography - Padding Oracle Attacks
 
17:06
Cryptography To get certificate subscribe: https://www.coursera.org/learn/cryptography ======================== Playlist URL: https://www.youtube.com/playlist?list=PL2jykFOD1AWb07OLBdFI2QIHvPo3aTTeu ============================ Youtube channel: https://www.youtube.com/user/intrigano ============================ https://scsa.ge/en/online-courses/ https://www.facebook.com/cyberassociation/
Views: 9704 intrigano
44 Quantum Mechanics - Quantum factoring   Shor's factoring algorithm
 
25:43
Quantum Mechanics and Quantum Computation - Quantum factoring Shor's factoring algorithm
Views: 14497 intrigano
Neural Networks - One Shot Learning
 
04:45
Convolutional Neural Networks About this course: This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization. Who is this class for: - Learners that took the first two courses of the specialization. The third course is recommended. - Anyone that already has a solid understanding of densely connected neural networks, and wants to learn convolutional neural networks or work with image data. Special applications: Face recognition & Neural style transfer Discover how CNNs can be applied to multiple fields, including art generation and face recognition. Implement your own algorithm to generate art and recognize faces! Subscribe at: https://www.coursera.org
Views: 2910 intrigano
Quantum Optics - introduction to the course
 
11:43
This course gives you access to basic tools and concepts to understand research articles and books on modern quantum optics. You will learn about quantization of light, formalism to describe quantum states of light without any classical analogue, and observables allowing one to demonstrate typical quantum properties of these states. These tools will be applied to the emblematic case of a one-photon wave packet, which behaves both as a particle and a wave. Wave-particle duality is a great quantum mystery in the words of Richard Feynman. You will be able to fully appreciate real experiments demonstrating wave-particle duality for a single photon, and applications to quantum technologies based on single photon sources, which are now commercially available. The tools presented in this course will be widely used in our second quantum optics course, which will present more advanced topics such as entanglement, interaction of quantized light with matter, squeezed light, etc... So if you have a good knowledge in basic quantum mechanics and classical electromagnetism, but always wanted to know: • how to go from classical electromagnetism to quantized radiation, • how the concept of photon emerges, • how a unified formalism is able to describe apparently contradictory behaviors observed in quantum optics labs, • how creative physicists and engineers have invented totally new technologies based on quantum properties of light, then this course is for you. Who is this class for: This course is primarily intended for university students who have a good knowledge of basic quantum mechanics and classical electromagnetism, and who want to enter in the field of quantum optics. It is also intended for engineers who want to catch up with the rapidly developing quantum technologies derived from the second quantum revolution, in which the observation and control of single quantum objects, such as single photons, is a key ingredient. Subscribe at: https://www.coursera.org
Views: 8724 intrigano
Linear Algebra - Solving data science challenges with mathematics
 
05:55
Mathematics for Machine Learning: Linear Algebra, Module 1 - Introduction to Linear Algebra and to Mathematics for Machine Learning To get certificate subscribe at: https://www.coursera.org/learn/linear-algebra-machine-learning/home/welcome ============================ Mathematics for Machine Learning: Linear Algebra: https://www.youtube.com/playlist?list=PL2jykFOD1AWazz20_QRfESiJ2rthDF9-Z ============================ Youtube channel: https://www.youtube.com/user/intrigano ============================ https://scsa.ge/en/online-courses/ https://www.facebook.com/cyberassociation/ About this course: In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works. Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before. At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning. Who is this class for: This course is for people who want to refresh their maths skills in linear algebra, particularly for the purposes of doing data science and machine learning, or learning about data science and machine learning. We look at vectors, matrices and how to apply these to solve linear systems of equations, and how to apply these to computational problems. ________________________________________ Created by: Imperial College London Module 1 Introduction to Linear Algebra and to Mathematics for Machine Learning In this first module we look at how linear algebra is relevant to machine learning and data science. Then we'll wind up the module with an initial introduction to vectors. Throughout, we're focussing on developing your mathematical intuition, not of crunching through algebra or doing long pen-and-paper examples. For many of these operations, there are callable functions in Python that can do the adding up - the point is to appreciate what they do and how they work so that, when things go wrong or there are special cases, you can understand why and what to do. Less Learning Objectives • Recall how machine learning and vectors and matrices are related • Interpret how changes in the model parameters affect the quality of the fit to the training data • Recognize that variations in the model parameters are vectors on the response surface - that vectors are a generic concept not limited to a physical real space • Use substitution / elimination to solve a fairly easy linear algebra problem • Understand how to add vectors and multiply by a scalar number
Views: 13001 intrigano
Software security - Session Hijacking
 
06:57
software security - Session Hijacking To get certificate subscribe at: https://www.coursera.org/learn/software-security ================================== Software Security playlist: https://www.youtube.com/playlist?list=PL2jykFOD1AWY1E3MB38_uOfpvEf4gnW80 ================================== About this course: This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a "build security in" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems. Successful learners in this course typically have completed sophomore/junior-level undergraduate work in a technical field, have some familiarity with programming, ideally in C/C++ and one other "managed" program language (like ML or Java), and have prior exposure to algorithms. Students not familiar with these languages but with others can improve their skills through online web tutorials.
Views: 3508 intrigano
IT Technical Support Fundamentals – Introduction
 
05:18
Google IT Support Professional Certificate https://www.coursera.org/specializations/google-it-support This six-course certificate, developed exclusively by Google, includes innovative curriculum designed to prepare you for an entry-level role in IT support. A job in IT can mean in-person or remote help desk work, either in a small business or at a global company, like Google. Whether you’ve been tinkering with IT or are completely new to the field, you’ve come to the right place. If you’re looking for a job, upon completion of the certificate, you can share your information with top employers, like Bank of America, Walmart, Sprint, GE Digital, PNC Bank, Infosys, TEKsystems, UPMC, and, of course, Google. Through a dynamic mix of video lectures, quizzes, and hand-on labs and widgets, this program will introduce you to troubleshooting and customer service, networking, operating systems, system administration, automation, and security. Along the way, you’ll hear from Googlers with unique backgrounds and perspectives, whose own foundation in IT support served as a jumping off point for their careers. They’re excited to go on this journey with you, as you invest in your future by achieving an end-of-program certificate. Course 1 - IT Technical Support Fundamentals In this course, you’ll be introduced to the world of Information Technology, or IT. This course is the first of a series that aims to prepare you for a role as an entry-level IT Support Specialist. You’ll learn about the different facets of Information Technology, like computer hardware, the Internet, computer software, and job-related skills. You’ll also learn about the history of computers, and the pioneers who shaped the world of computing that we know today. This course covers a wide variety of topics in IT that are designed to give you an overview of what’s to come in this IT Support Professional Certificate. By the end of this course, you’ll be able to: - understand how the binary system works. - assemble a computer from scratch. - choose and install an operating system on a computer. - understand what the Internet is, how it works, and the impact it has in the modern world. - learn how applications are created and how they work under the hood of our computer. - utilize common problem-solving methodologies and soft skills in an Information Technology setting. Who is this class for: This program is intended for beginners who are interested in developing the skills necessary to perform entry-level IT support. No pre-requisite knowledge is required. However, if you do have some familiarity with IT, you can skip through
Views: 10116 intrigano
Hardware security - Physical Unclonable Functions PUF Basics
 
16:24
hardware security - Physical Unclonable Functions PUF Basics To get certificate subscribe at: https://www.coursera.org/learn/hardware-security ================================== Hardware security playlist: https://www.youtube.com/playlist?list=PL2jykFOD1AWZRNhehPCsDLhfRkM1abYHd ================================== About this course: In this course, we will study security and trust from the hardware perspective. Upon completing the course, students will understand the vulnerabilities in current digital system design flow and the physical attacks to these systems. They will learn that security starts from hardware design and be familiar with the tools and skills to build secure and trusted hardware.
Views: 6246 intrigano
Neural Networks - Triplet Loss
 
15:31
Convolutional Neural Networks About this course: This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization. Who is this class for: - Learners that took the first two courses of the specialization. The third course is recommended. - Anyone that already has a solid understanding of densely connected neural networks, and wants to learn convolutional neural networks or work with image data. Special applications: Face recognition & Neural style transfer Discover how CNNs can be applied to multiple fields, including art generation and face recognition. Implement your own algorithm to generate art and recognize faces! Subscribe at: https://www.coursera.org
Views: 4914 intrigano
Linux SetUID, SetGID, Sticky Bit
 
05:53
Google IT Support Professional Certificate Course 3 - Operating Systems and You: Becoming a Power User, Module 2 - Users and Permissions (File Permissions) To get certificate subscribe at: https://www.coursera.org/specializations/google-it-support ================= The whole course playlist: Google IT Support Professional Certificate https://www.youtube.com/playlist?list=PL2jykFOD1AWZlfwMPcVKwaFrRXbqObI3U ================= Playlist Operating Systems: https://www.youtube.com/playlist?list=PL2jykFOD1AWY3Ot3HResh50JwdBdjilsq ================= https://www.facebook.com/cyberassociation/ https://scsa.ge/en/online-courses/ This six-course certificate, developed exclusively by Google, includes innovative curriculum designed to prepare you for an entry-level role in IT support. A job in IT can mean in-person or remote help desk work, either in a small business or at a global company, like Google. Whether you’ve been tinkering with IT or are completely new to the field, you’ve come to the right place. If you’re looking for a job, upon completion of the certificate, you can share your information with top employers, like Bank of America, Walmart, Sprint, GE Digital, PNC Bank, Infosys, TEKsystems, UPMC, and, of course, Google. Course 3 - Operating Systems and You: Becoming a Power User About the Course In this course, you’ll learn how to use the major operating systems, Windows and Linux, which are a core component of IT. Through a combination of video lectures, demonstrations, and hands-on practice, you’ll learn about the main components of an operating system and how to perform critical tasks like managing software and users, and configuring hardware. By the end of this course you’ll be able to: - navigate the Windows and Linux filesystems using a graphical user interface and command line interpreter. - set up users, groups, and permissions for account access. - install, configure, and remove software on the Windows and Linux operating systems. - configure disk partitions and filesystems. - understand how system processes work and how to manage them. - work with system logs and remote connection tools. - utilize operating system knowledge to troubleshoot common issues in an IT Support Specialist role. Module 2 - Users and Permissions In the second week of this course, we'll learn about configuring users and permissions in Windows and Linux OS. As an IT Support Specialist, it's important to know how to grant the appropriate permissions to users and groups for both Windows and Linux OS. By the end of this module, you will know how to add, modify, and remove users for a computer and for specific files and folders by using the Windows GUI, Windows CLI, and Linux shell. Learning Objectives • Grant the appropriate permissions to users and groups. • Add, modify and remove users on a computer. • Add, modify and remove permissions on files and folders.
Views: 6797 intrigano
Software security - Memory Layout
 
10:58
software security - Memory Layout To get certificate subscribe at: https://www.coursera.org/learn/software-security ================================== Software Security playlist: https://www.youtube.com/playlist?list=PL2jykFOD1AWY1E3MB38_uOfpvEf4gnW80 ================================== About this course: This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a "build security in" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems. Successful learners in this course typically have completed sophomore/junior-level undergraduate work in a technical field, have some familiarity with programming, ideally in C/C++ and one other "managed" program language (like ML or Java), and have prior exposure to algorithms. Students not familiar with these languages but with others can improve their skills through online web tutorials.
Views: 1808 intrigano
47 Quantum Mechanics - Quantum search   Grover's algorithm
 
12:04
Quantum Mechanics and Quantum Computation - Quantum search Grover's algorithm
Views: 4741 intrigano
IDS Versus IPS
 
06:53
Real-Time Cyber Threat Detection and Mitigation Module Module 3 Network Security Architectures This module introduces the foundations firewall architectures, intrusion detection, and SOC design. Learning Objectives • Describe firewall architectural options • Critique firewall architectural designs that are not recommended • Explain the basics of intrusion detection and intrusion prevention • Compare signature-based and profile-based security analysis • Describe how audit records, alarms, and flow information are processed • Identify trends in SOC design for the enterprise About this course: This course introduces real-time cyber security techniques and methods in the context of the TCP/IP protocol suites. Explanation of some basic TCP/IP security hacks is used to introduce the need for network security solutions such as stateless and stateful firewalls. Learners will be introduced to the techniques used to design and configure firewall solutions such as packet filters and proxies to protect enterprise assets. Perimeter solutions such as firewalls and intrusion prevention systems are shown to have significant drawbacks in common enterprise environments. The result of such weakness is shown to often exist as advanced persistent threats (APTs) from nation-state actors. Such attacks, as well as DDOS and third-party attacks, are shown to have potential solutions for modern enterprise. To get certificate subscribe at: https://www.coursera.org/learn/intro-cyber-attacks/home/welcome https://www.coursera.org
Views: 2339 intrigano
Quantum Optics - Introduction to Quantization of light
 
05:03
This course gives you access to basic tools and concepts to understand research articles and books on modern quantum optics. You will learn about quantization of light, formalism to describe quantum states of light without any classical analogue, and observables allowing one to demonstrate typical quantum properties of these states. These tools will be applied to the emblematic case of a one-photon wave packet, which behaves both as a particle and a wave. Wave-particle duality is a great quantum mystery in the words of Richard Feynman. You will be able to fully appreciate real experiments demonstrating wave-particle duality for a single photon, and applications to quantum technologies based on single photon sources, which are now commercially available. The tools presented in this course will be widely used in our second quantum optics course, which will present more advanced topics such as entanglement, interaction of quantized light with matter, squeezed light, etc... So if you have a good knowledge in basic quantum mechanics and classical electromagnetism, but always wanted to know: • how to go from classical electromagnetism to quantized radiation, • how the concept of photon emerges, • how a unified formalism is able to describe apparently contradictory behaviors observed in quantum optics labs, • how creative physicists and engineers have invented totally new technologies based on quantum properties of light, then this course is for you. Who is this class for: This course is primarily intended for university students who have a good knowledge of basic quantum mechanics and classical electromagnetism, and who want to enter in the field of quantum optics. It is also intended for engineers who want to catch up with the rapidly developing quantum technologies derived from the second quantum revolution, in which the observation and control of single quantum objects, such as single photons, is a key ingredient. Subscribe at: https://www.coursera.org
Views: 2345 intrigano
Quantum Optics - Canonical quantization
 
10:29
Quantum Optics - Quantization of light one mode - Canonical quantization This course gives you access to basic tools and concepts to understand research articles and books on modern quantum optics. You will learn about quantization of light, formalism to describe quantum states of light without any classical analogue, and observables allowing one to demonstrate typical quantum properties of these states. These tools will be applied to the emblematic case of a one-photon wave packet, which behaves both as a particle and a wave. Wave-particle duality is a great quantum mystery in the words of Richard Feynman. You will be able to fully appreciate real experiments demonstrating wave-particle duality for a single photon, and applications to quantum technologies based on single photon sources, which are now commercially available. The tools presented in this course will be widely used in our second quantum optics course, which will present more advanced topics such as entanglement, interaction of quantized light with matter, squeezed light, etc... So if you have a good knowledge in basic quantum mechanics and classical electromagnetism, but always wanted to know: • how to go from classical electromagnetism to quantized radiation, • how the concept of photon emerges, • how a unified formalism is able to describe apparently contradictory behaviors observed in quantum optics labs, • how creative physicists and engineers have invented totally new technologies based on quantum properties of light, then this course is for you. Who is this class for: This course is primarily intended for university students who have a good knowledge of basic quantum mechanics and classical electromagnetism, and who want to enter in the field of quantum optics. It is also intended for engineers who want to catch up with the rapidly developing quantum technologies derived from the second quantum revolution, in which the observation and control of single quantum objects, such as single photons, is a key ingredient. Subscribe at: https://www.coursera.org
Views: 2809 intrigano
Neural Networks - YOLO Algorithm
 
07:02
Convolutional Neural Networks About this course: This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization. Who is this class for: - Learners that took the first two courses of the specialization. The third course is recommended. - Anyone that already has a solid understanding of densely connected neural networks, and wants to learn convolutional neural networks or work with image data. Object detection Learn how to apply your knowledge of CNNs to one of the toughest but hottest field of computer vision: Object detection. Learning Objectives • Understand the challenges of Object Localization, Object Detection and Landmark Finding • Understand and implement non-max suppression • Understand and implement intersection over union • Understand how we label a dataset for an object detection application • Remember the vocabulary of object detection (landmark, anchor, bounding box, grid, ...) Subscribe at: https://www.coursera.org
Views: 7805 intrigano
Multivariate Calculus – The Jacobian
 
05:50
Course 2 - Mathematics for Machine Learning Multivariate Calculus, Module 2 Multivariate calculus To get certificate subscribe at: https://www.coursera.org/learn/multivariate-calculus-machine-learning ============================ Mathematics for Machine Learning: Multivariate Calculus https://www.youtube.com/playlist?list=PL2jykFOD1AWaL4_-bdidPfIWe765jOgfL ============================ Youtube channel: https://www.youtube.com/user/intrigano ============================ https://scsa.ge/en/online-courses/ https://www.facebook.com/cyberassociation/ About this course: This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster. Next, we learn how to calculate vectors that point up hill on multidimensional surfaces and even put this into action using an interactive game. We take a look at how we can use calculus to build approximations to functions, as well as helping us to quantify how accurate we should expect those approximations to be. We also spend some time talking about where calculus comes up in the training of neural networks, before finally showing you how it is applied in linear regression models. This course is intended to offer an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck. Hopefully, without going into too much detail, you’ll still come away with the confidence to dive into some more focused machine learning courses in future. Who is this class for: This class is for people who would like to learn more about machine learning techniques, but don’t currently have the fundamental mathematics in place to go into much detail. This course will include some exercises that require you to work with code. If you've not had much experience with code before DON'T PANIC, we will give you lots of guidance as you go. Module 2 Multivariate calculus Building on the foundations of the previous module, we now generalise our calculus tools to handle multivariable systems. This means we can take a function with multiple inputs and determine the influence of each of them separately. It would not be unusual for a machine learning method to require the analysis of a function with thousands of inputs, so we will also introduce the linear algebra structures necessary for storing the results of our multivariate calculus analysis in an orderly fashion. Learning Objectives • Recognize that differentiation can be applied to multiple variables in an equation • Use multivariate calculus tools on example equations • Recognise the utility of vector/matrix structures in multivariate calculus • Examine two dimensional problems using the Jacobian
Views: 1477 intrigano
Neural Networks - Normalizing inputs
 
05:31
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization About this course: This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. Who is this class for: This class is for: - Learners that took the first course of the specialization: "Neural Networks and Deep Learning" - Anyone that already understands fully-connected neural networks, and wants to learn the practical aspects of making them work well. Practical aspects of Deep Learning Learning Objectives • Recall that different types of initializations lead to different results • Recognize the importance of initialization in complex neural networks. • Recognize the difference between train/dev/test sets • Diagnose the bias and variance issues in your model • Learn when and how to use regularization methods such as dropout or L2 regularization. • Understand experimental issues in deep learning such as Vanishing or Exploding gradients and learn how to deal with them • Use gradient checking to verify the correctness of your backpropagation implementation Subscribe at: https://www.coursera.org
Views: 2736 intrigano
cryptography - CBC MAC
 
07:09
Cryptography To get certificate subscribe: https://www.coursera.org/learn/cryptography ======================== Playlist URL: https://www.youtube.com/playlist?list=PL2jykFOD1AWb07OLBdFI2QIHvPo3aTTeu ============================ Youtube channel: https://www.youtube.com/user/intrigano ============================ https://scsa.ge/en/online-courses/ https://www.facebook.com/cyberassociation/
Views: 4617 intrigano
Cyber-Physical Systems: Modeling and Simulation - Introduction
 
05:40
Cyber-Physical Systems: Modeling and Simulation About this course: Cyber-physical systems (CPS for short) combine digital and analog devices, interfaces, networks, computer systems, and the like, with the natural and man-made physical world. The inherent interconnected and heterogeneous combination of behaviors in these systems makes their analysis and design an exciting and challenging task. CPS: Modeling and Simulation provides you with an introduction to modeling and simulation of cyber-physical systems. The main focus is on models of physical process, finite state machines, computation, converters between physical and cyber variables, and digital networks. The instructor of this course is Ricardo Sanfelice (https://hybrid.soe.ucsc.edu), Associate Professor in the Department of Computer Engineering at the University of California Santa Cruz. Module 1 Basic Modeling Concepts: Discrete-time and Continuous-Time Systems Learning Objectives • Model physical components in a CPS • Model cyber components in a CPS • Understand the components of a CPS To get certificate subscribe at: https://www.coursera.org/learn/intro-cyber-attacks/home/welcome https://www.coursera.org
Views: 2657 intrigano
24 Quantum Mechanics - Bell state circuit
 
05:59
Bell state circuit
Views: 2252 intrigano
38 Quantum Mechanics - Quantum Fourier transform overview
 
10:12
Quantum Mechanics and Quantum Computation - Quantum Fourier transform overview
Views: 6084 intrigano
Forward and Reverse Proxies
 
04:58
Real-Time Cyber Threat Detection and Mitigation Module 2 More Advanced Network Security Technologies This module introduces packet filters, firewall rule sets, proxies, and additional network security methods. Learning Objectives • Describe the basics of packet filtering for network security • Compare application proxies in forward and reverse modes • Review firewall rule design and administration • Develop firewall policies for HTTP and other services • Analyze the security issues with FTP for packet filters About this course: This course introduces real-time cyber security techniques and methods in the context of the TCP/IP protocol suites. Explanation of some basic TCP/IP security hacks is used to introduce the need for network security solutions such as stateless and stateful firewalls. Learners will be introduced to the techniques used to design and configure firewall solutions such as packet filters and proxies to protect enterprise assets. Perimeter solutions such as firewalls and intrusion prevention systems are shown to have significant drawbacks in common enterprise environments. The result of such weakness is shown to often exist as advanced persistent threats (APTs) from nation-state actors. Such attacks, as well as DDOS and third-party attacks, are shown to have potential solutions for modern enterprise. To get certificate subscribe at: https://www.coursera.org/learn/intro-cyber-attacks/home/welcome https://www.coursera.org
Views: 1303 intrigano
Quantum Optics – Quantum cryptography the BB84 QKD scheme
 
15:14
One-photon based quantum technologies In this lesson, you will discover two quantum technologies based on one photon sources. Quantum technologies allow one to achieve a goal in a way qualitatively different from a classical technology aiming at the same goal. For instance, quantum cryptography is immune to progress in computers power, while many classical cryptography methods can in principle be broken when we have more powerful computers. Similarly, quantum random number generators yield true random numbers, while classical random number generators only produce pseudo-random numbers, which might be guessed by somebody else than the user. This lesson is also an opportunity to learn two important concepts in quantum information: (i) qubits based on photon polarization; (ii) the celebrated no-cloning theorem, at the root of the security of quantum cryptography. Learning Objectives • Apply your knowledge about the behavior of a single photon on a beam splitter to quantum random number generators. • Understand the no-cloning theorem • Understand and remember the properties of q qubit This course gives you access to basic tools and concepts to understand research articles and books on modern quantum optics. You will learn about quantization of light, formalism to describe quantum states of light without any classical analogue, and observables allowing one to demonstrate typical quantum properties of these states. These tools will be applied to the emblematic case of a one-photon wave packet, which behaves both as a particle and a wave. Wave-particle duality is a great quantum mystery in the words of Richard Feynman. You will be able to fully appreciate real experiments demonstrating wave-particle duality for a single photon, and applications to quantum technologies based on single photon sources, which are now commercially available. The tools presented in this course will be widely used in our second quantum optics course, which will present more advanced topics such as entanglement, interaction of quantized light with matter, squeezed light, etc... So if you have a good knowledge in basic quantum mechanics and classical electromagnetism, but always wanted to know: • how to go from classical electromagnetism to quantized radiation, • how the concept of photon emerges, • how a unified formalism is able to describe apparently contradictory behaviors observed in quantum optics labs, • how creative physicists and engineers have invented totally new technologies based on quantum properties of light, then this course is for you. Subscribe at: https://www.coursera.org
Views: 6273 intrigano
Automation Monitoring by Example - Prometheus Black Box Monitoring
 
05:10
Google IT Support Professional Certificate Course 5 - IT Automation, Module 6 - Monitoring To get certificate subscribe at: https://www.coursera.org/specializations/google-it-support ================= The whole course playlist: Google IT Support Professional Certificate https://www.youtube.com/playlist?list=PL2jykFOD1AWZlfwMPcVKwaFrRXbqObI3U ================= System Administration and IT Infrastructure Services: https://www.youtube.com/playlist?list=PL2jykFOD1AWYUKiWILvy1MtkboqifMEJ0 ================= https://www.facebook.com/cyberassociation/ https://scsa.ge/en/online-courses/ This six-course certificate, developed exclusively by Google, includes innovative curriculum designed to prepare you for an entry-level role in IT support. A job in IT can mean in-person or remote help desk work, either in a small business or at a global company, like Google. Whether you’ve been tinkering with IT or are completely new to the field, you’ve come to the right place. If you’re looking for a job, upon completion of the certificate, you can share your information with top employers, like Bank of America, Walmart, Sprint, GE Digital, PNC Bank, Infosys, TEKsystems, UPMC, and, of course, Google. Course 5 - IT Automation: It’s not that scary! About the Course This course is designed to give you an introduction to concepts related to the automatic management of infrastructure in the IT industry. Using tools like scripting languages, version control, configuration management systems, and monitoring solutions, this course will give you an introduction to automation in IT. It will have an emphasis on creating automation that’s both scalable and manageable. By the end of this course, you’ll be able to: - cite the fundamentals of programming using the Ruby language. - create basic automation scripts to perform system administration tasks. - use regular expressions to extract meaning from raw text. - manage code by using the version control system, Git. - develop and understand the benefits of tests for the scripts and automation they create. - deploy software using the Chef configuration management software and understand the principles of configuration management in the IT context. - track the health of technology systems through monitoring and become familiar with common monitoring concepts and practices Before taking this course, it's advised (but not required) that you complete the earlier courses in this program. It’s helpful to be familiar with the following concepts: - installation of software on a computer platform - basic computer network terminology and concepts - common system administrator tasks and responsibilities This course has been designed to be completed completely in-browser. You don’t have to install any software on your computer. Module 6 - Monitoring In the sixth module of the course, we'll learn about system monitoring. Monitoring helps IT Support Specialists analyzes the IT infrastructure so you can identify any problems or risks in the system. We'll learn how to use one monitoring system called Prometheus and use metric visualizations to help us troubleshoot and send alerts. By the end of this module, you will set up a monitoring and alerting system, which you will need to use for your final project of the course. Learning Objectives • Understand what monitoring is and why it’s important • Create an alerting system using Prometheus • Create an monitoring system using Prometheus • Understand what monitoring is and why it's important for IT infrastructure • Examine monitoring systems as a form of automation
Views: 1384 intrigano
Software security - Code Injection
 
06:34
software security - Code Injection To get certificate subscribe at: https://www.coursera.org/learn/software-security ================================== Software Security playlist: https://www.youtube.com/playlist?list=PL2jykFOD1AWY1E3MB38_uOfpvEf4gnW80 ================================== About this course: This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a "build security in" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems. Successful learners in this course typically have completed sophomore/junior-level undergraduate work in a technical field, have some familiarity with programming, ideally in C/C++ and one other "managed" program language (like ML or Java), and have prior exposure to algorithms. Students not familiar with these languages but with others can improve their skills through online web tutorials.
Views: 2568 intrigano
Neural Networks - ResNets
 
07:08
Convolutional Neural Networks About this course: This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization. Who is this class for: - Learners that took the first two courses of the specialization. The third course is recommended. - Anyone that already has a solid understanding of densely connected neural networks, and wants to learn convolutional neural networks or work with image data. Deep convolutional models: case studies Learn about the practical tricks and methods used in deep CNNs straight from the research papers. Learning Objectives • Understand multiple foundational papers of convolutional neural networks • Analyze the dimensionality reduction of a volume in a very deep network • Understand and Implement a Residual network • Build a deep neural network using Keras • Implement a skip-connection in your network • Clone a repository from github and use transfer learning Subscribe at: https://www.coursera.org
Views: 2689 intrigano
Linear Algebra - Motivations for linear algebra
 
03:31
Mathematics for Machine Learning: Linear Algebra, Module 1 - Introduction to Linear Algebra and to Mathematics for Machine Learning To get certificate subscribe at: https://www.coursera.org/learn/linear-algebra-machine-learning/home/welcome ============================ Mathematics for Machine Learning: Linear Algebra: https://www.youtube.com/playlist?list=PL2jykFOD1AWazz20_QRfESiJ2rthDF9-Z ============================ Youtube channel: https://www.youtube.com/user/intrigano ============================ https://scsa.ge/en/online-courses/ https://www.facebook.com/cyberassociation/ About this course: In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works. Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before. At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning. Who is this class for: This course is for people who want to refresh their maths skills in linear algebra, particularly for the purposes of doing data science and machine learning, or learning about data science and machine learning. We look at vectors, matrices and how to apply these to solve linear systems of equations, and how to apply these to computational problems. ________________________________________ Created by: Imperial College London Module 1 Introduction to Linear Algebra and to Mathematics for Machine Learning In this first module we look at how linear algebra is relevant to machine learning and data science. Then we'll wind up the module with an initial introduction to vectors. Throughout, we're focussing on developing your mathematical intuition, not of crunching through algebra or doing long pen-and-paper examples. For many of these operations, there are callable functions in Python that can do the adding up - the point is to appreciate what they do and how they work so that, when things go wrong or there are special cases, you can understand why and what to do. Less Learning Objectives • Recall how machine learning and vectors and matrices are related • Interpret how changes in the model parameters affect the quality of the fit to the training data • Recognize that variations in the model parameters are vectors on the response surface - that vectors are a generic concept not limited to a physical real space • Use substitution / elimination to solve a fairly easy linear algebra problem • Understand how to add vectors and multiply by a scalar number
Views: 4294 intrigano
Software security - Format String Vulnerabilities
 
06:42
software security - Format String Vulnerabilities To get certificate subscribe at: https://www.coursera.org/learn/software-security ================================== Software Security playlist: https://www.youtube.com/playlist?list=PL2jykFOD1AWY1E3MB38_uOfpvEf4gnW80 ================================== About this course: This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a "build security in" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems. Successful learners in this course typically have completed sophomore/junior-level undergraduate work in a technical field, have some familiarity with programming, ideally in C/C++ and one other "managed" program language (like ML or Java), and have prior exposure to algorithms. Students not familiar with these languages but with others can improve their skills through online web tutorials.
Views: 6859 intrigano
cryptography - Hex and ASCII
 
10:58
cryptography To get certificate subscribe: https://www.coursera.org/learn/cryptography ======================== Playlist URL: https://www.youtube.com/playlist?list=PL2jykFOD1AWb07OLBdFI2QIHvPo3aTTeu ============================ Youtube channel: https://www.youtube.com/user/intrigano ============================ https://scsa.ge/en/online-courses/ https://www.facebook.com/cyberassociation/
Views: 13220 intrigano
25 Quantum Mechanics - Teleportation part 1
 
11:38
Teleportation part 1
Views: 2006 intrigano
Quantum Optics – Mach Zehnder interferometer in classical optics
 
09:56
One photon interference: Wave-Particle duality In this lesson, you will address the fascinating question of a single photon interfering with itself, by calculating the interference pattern for a single photon launched into a Mach-Zehnder interferometer. In order to do it you will first learn how to treat a beam-splitter in quantum optics, a very important tool that you need to know. You will also learn that when you want to describe an optical instrument in quantum optics, it is very useful to master its classical optics description. This lesson is an opportunity to think about the mysterious concept of wave-particle duality, and about the power of the quantum formalism, which can deal consistently with two behaviours apparently contradictory . Learning Objectives • Employ quantum optics formalism to calculate interference • Memorize the quantum optics formalism for a beam splitter • Discover how the quantum optics formalism deals consistently with the mysterious wave-particle duality About this course: This course gives you access to basic tools and concepts to understand research articles and books on modern quantum optics. You will learn about quantization of light, formalism to describe quantum states of light without any classical analogue, and observables allowing one to demonstrate typical quantum properties of these states. These tools will be applied to the emblematic case of a one-photon wave packet, which behaves both as a particle and a wave. Wave-particle duality is a great quantum mystery in the words of Richard Feynman. You will be able to fully appreciate real experiments demonstrating wave-particle duality for a single photon, and applications to quantum technologies based on single photon sources, which are now commercially available. The tools presented in this course will be widely used in our second quantum optics course, which will present more advanced topics such as entanglement, interaction of quantized light with matter, squeezed light, etc... So if you have a good knowledge in basic quantum mechanics and classical electromagnetism, but always wanted to know: • how to go from classical electromagnetism to quantized radiation, • how the concept of photon emerges, • how a unified formalism is able to describe apparently contradictory behaviors observed in quantum optics labs, • how creative physicists and engineers have invented totally new technologies based on quantum properties of light, then this course is for you.
Views: 8223 intrigano
Application Proxy Filtering
 
06:29
Real-Time Cyber Threat Detection and Mitigation Module 2 More Advanced Network Security Technologies This module introduces packet filters, firewall rule sets, proxies, and additional network security methods. Learning Objectives • Describe the basics of packet filtering for network security • Compare application proxies in forward and reverse modes • Review firewall rule design and administration • Develop firewall policies for HTTP and other services • Analyze the security issues with FTP for packet filters About this course: This course introduces real-time cyber security techniques and methods in the context of the TCP/IP protocol suites. Explanation of some basic TCP/IP security hacks is used to introduce the need for network security solutions such as stateless and stateful firewalls. Learners will be introduced to the techniques used to design and configure firewall solutions such as packet filters and proxies to protect enterprise assets. Perimeter solutions such as firewalls and intrusion prevention systems are shown to have significant drawbacks in common enterprise environments. The result of such weakness is shown to often exist as advanced persistent threats (APTs) from nation-state actors. Such attacks, as well as DDOS and third-party attacks, are shown to have potential solutions for modern enterprise. To get certificate subscribe at: https://www.coursera.org/learn/intro-cyber-attacks/home/welcome https://www.coursera.org
Views: 1391 intrigano
Quantum Optics - Number states; Photon
 
07:09
Quantum Optics - Quantization of light one mode - Number states; Photon This course gives you access to basic tools and concepts to understand research articles and books on modern quantum optics. You will learn about quantization of light, formalism to describe quantum states of light without any classical analogue, and observables allowing one to demonstrate typical quantum properties of these states. These tools will be applied to the emblematic case of a one-photon wave packet, which behaves both as a particle and a wave. Wave-particle duality is a great quantum mystery in the words of Richard Feynman. You will be able to fully appreciate real experiments demonstrating wave-particle duality for a single photon, and applications to quantum technologies based on single photon sources, which are now commercially available. The tools presented in this course will be widely used in our second quantum optics course, which will present more advanced topics such as entanglement, interaction of quantized light with matter, squeezed light, etc... So if you have a good knowledge in basic quantum mechanics and classical electromagnetism, but always wanted to know: • how to go from classical electromagnetism to quantized radiation, • how the concept of photon emerges, • how a unified formalism is able to describe apparently contradictory behaviors observed in quantum optics labs, • how creative physicists and engineers have invented totally new technologies based on quantum properties of light, then this course is for you. Who is this class for: This course is primarily intended for university students who have a good knowledge of basic quantum mechanics and classical electromagnetism, and who want to enter in the field of quantum optics. It is also intended for engineers who want to catch up with the rapidly developing quantum technologies derived from the second quantum revolution, in which the observation and control of single quantum objects, such as single photons, is a key ingredient. Subscribe at: https://www.coursera.org
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Bitcoin - Zerocoin and Zerocash
 
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Zerocoin and Zerocash - Bitcoin and Cryptocurrency Technologies Part 6 - Bitcoin and Anonymity Is Bitcoin anonymous? What does that statement even mean—can we define it rigorously? We'll learn about the various ways to improve Bitcoin's anonymity and privacy and learn about Bitcoin's role in Silk Road and other hidden marketplaces.
Views: 1742 intrigano
Software security - Control Flow Integrity
 
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software security - Control Flow Integrity To get certificate subscribe at: https://www.coursera.org/learn/software-security ================================== Software Security playlist: https://www.youtube.com/playlist?list=PL2jykFOD1AWY1E3MB38_uOfpvEf4gnW80 ================================== About this course: This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a "build security in" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems. Successful learners in this course typically have completed sophomore/junior-level undergraduate work in a technical field, have some familiarity with programming, ideally in C/C++ and one other "managed" program language (like ML or Java), and have prior exposure to algorithms. Students not familiar with these languages but with others can improve their skills through online web tutorials.
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41 QFTn part 2
 
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Quantum Mechanics and Quantum Computation - QFTn part 2
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Neural Networks - Anchor Boxes
 
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Convolutional Neural Networks About this course: This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization. Who is this class for: - Learners that took the first two courses of the specialization. The third course is recommended. - Anyone that already has a solid understanding of densely connected neural networks, and wants to learn convolutional neural networks or work with image data. Object detection Learn how to apply your knowledge of CNNs to one of the toughest but hottest field of computer vision: Object detection. Learning Objectives • Understand the challenges of Object Localization, Object Detection and Landmark Finding • Understand and implement non-max suppression • Understand and implement intersection over union • Understand how we label a dataset for an object detection application • Remember the vocabulary of object detection (landmark, anchor, bounding box, grid, ...) Subscribe at: https://www.coursera.org
Views: 2321 intrigano