|Course or Certification Name||Category||Location||Mode of learning|
|Python for Computer Vision with OpenCV and Deep Learning||Online self study|
|Computer Hacking Forensic Investigator Certification||Ethical Hacking||Online self study|
|Computer Hacking and Forensics||Ethical Hacking||Online self study|
|Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)||Online self study|
|Vskills Certified Computer Fundamentals Professional||MS Office||Offline self study|
|Computer Networking||Routing & Network Support||Online self study|
|Intro to Theoretical Computer Science||Web Technologies||Online self study|
|Become a Computer Vision Expert||Machine Learning||Online self study|
|Proactive Computer Security||Online self study|
|Complete IT Support Specialist Course: IT Foundations||IT Support||Online self study|
|Master the Coding Interview: Data Structures + Algorithms||Online self study|
|Human-Computer Interaction||Web Technologies||Online self study|
|Computer Forensics||Cyber Security||Online self study|
|Vskills Certified Software Security Professional||Information Security||Online self study|
|Tensorflow 2.0: Deep Learning and Artificial Intelligence||Online self study|
Welcome to the ultimate online course on Python for Computer Vision! This course is your best resource for learning how to use the Python programming language for Computer Vision. We'll be exploring how to use Python and the OpenCV (Open Computer Vision) library to analyze images and video data. The most popular platforms in the world are generating never before seen amounts of image and video data. Every 60 seconds users upload more than 300 hours of video to Youtube, Netflix subscribers stream over 80,000 hours of video, and Instagram users like over 2 million photos! Now more than ever its necessary for developers to gain the necessary skills to work with image and video data using computer vision. Computer vision allows us to analyze and leverage image and video data, with applications in a variety of industries, including self-driving cars, social network apps, medical diagnostics, and many more. As the fastest growing language in popularity, Python is well suited to leverage the power of existing computer vision libraries to learn from all this image and video data. In this course we'll teach you everything you need to know to become an expert in computer vision! This $20 billion dollar industry will be one of the most important job markets in the years to come. We'll start the course by learning about numerical processing with the NumPy library and how to open and manipulate images with NumPy. Then will move on to using the OpenCV library to open and work with image basics. Then we'll start to understand how to process images and apply a variety of effects, including color mappings, blending, thresholds, gradients, and more. Then we'll move on to understanding video basics with OpenCV, including working with streaming video from a webcam. Afterwards we'll learn about direct video topics, such as optical flow and object detection. Including face detection and object tracking. Then we'll move on to an entire section of the course devoted to the latest deep learning topics, including image recognition and custom image classifications. We'll even cover the latest deep learning networks, including the YOLO (you only look once) deep learning network. This course covers all this and more, including the following topics: NumPy Images with NumPy Image and Video Basics with NumPy Color Mappings Blending and Pasting Images Image Thresholding Blurring and Smoothing Morphological Operators Gradients Histograms Streaming video with OpenCV Object Detection Template Matching Corner, Edge, and Grid Detection Contour Detection Feature Matching WaterShed Algorithm Face Detection Object Tracking Optical Flow Deep Learning with Keras Keras and Convolutional Networks Customized Deep Learning Networks State of the Art YOLO Networks and much more! Feel free to message me on Udemy if you have any questions about the course! Thanks for checking out the course page, and I hope to see you inside! Jose
Computer hacking forensic investigation is the process of detecting hacking attacks and properly extracting evidence to report the crime and conduct audits to prevent future attacks. | Computer crime in today’s cyber world is on the rise. Computer Investigation techniques are being used by police, government and corporate entities globally and many of them turn to EC-Council for our Computer Hacking Forensic Investigator CHFI Certification Program.
Love the idea of digital forensics investigation? That is what computer forensics is all about. You will learn how to; determine potential online criminal activity at its inception, legally gather evidence, search and investigate wireless attacks.
This is one of the most exciting courses I've done and it really shows how fast and how far deep learning has come over the years. When I first started my deep learning series, I didn't ever consider that I'd make two courses on convolutional neural networks . I think what You'll find is that, this course is so entirely different from the previous one, you will be impressed at just how much material we have to cover. Let me give you a quick rundown of what this course is all about: We're going to bridge the gap between the basic CNN architecture you already know and love, to modern, novel architectures such as VGG , ResNet , and Inception (named after the movie which by the way, is also great!) We're going to apply these to images of blood cells, and create a system that is a better medical expert than either you or I. This brings up a fascinating idea: that the doctors of the future are not humans, but robots. In this course, You'll see how we can turn a CNN into an object detection system, that not only classifies images but can locate each object in an image and predict its label. You can imagine that such a task is a basic prerequisite for self-driving vehicles . (It must be able to detect cars, pedestrians, bicycles, traffic lights, etc. in real-time) We'll be looking at a state-of-the-art algorithm called SSD which is both faster and more accurate than its predecessors. Another very popular computer vision task that makes use of CNNs is called neural style transfer . This is where you take one image called the content image, and another image called the style image, and you combine these to make an entirely new image, that is as if you hired a painter to paint the content of the first image with the style of the other. Unlike a human painter, this can be done in a matter of seconds. I will also introduce you to the now-famous GAN architecture ( Generative Adversarial Networks ), where you will learn some of the technology behind how neural networks are used to generate state-of-the-art, photo-realistic images. Currently, we also implement object localization , which is an essential first step toward implementing a full object detection system. I hope you're excited to learn about these advanced applications of CNNs, I'll see you in class! AWESOME FACTS: One of the major themes of this course is that we're moving away from the CNN itself, to systems involving CNNs. Instead of focusing on the detailed inner workings of CNNs (which we've already done), we'll focus on high-level building blocks. The result? Almost zero math . Another result? No complicated low-level code such as that written in Tensorflow , Theano , or PyTorch (although some optional exercises may contain them for the very advanced students). Most of the course will be in Keras which means a lot of the tedious, repetitive stuff is written for you. Suggested Prerequisites: Know how to build, train, and use a CNN using some library (preferably in Python) Understand basic theoretical concepts behind convolution and neural networks Decent Python coding skills, preferably in data science and the Numpy Stack TIPS (for getting through the course): Watch it at 2x. Take handwritten notes. This will drastically increase your ability to retain the information. Write down the equations. If you don't, I guarantee it will just look like gibberish. Ask lots of questions on the discussion board. The more the better! Realize that most exercises will take you days or weeks to complete. Write code yourself, don't just sit there and look at my code. WHAT ORDER SHOULD I TAKE YOUR COURSES IN?: Check out the lecture "What order should I take your courses in?" (available in the Appendix of any of my courses, including the free Numpy course)
MS Office suite is one of the most versatile software application suites used in the day-to-day operations to support and connect different business systems. This Vskills Certified Computer Fundamental MS Office Professional is an essential course for both beginners and professional which provide the essential skills required to show their competencies in MS Office. With this government certification, it will be easy for candidates to get employment opportunities in various offices using MS Office in their daily operations.
This course covers advanced topics in Computer Networking such as Software-Defined Networking (SDN), Data Center Networking and Content Distribution. The course is divided into three parts: | Part 1 is about the implementation, design principles and goals of a Computer Network and touches upon the various routing algorithms used in CN (such as link-state and distance vector). | Part 2 talks about resource control and content distribution in Networking Applications. It covers Congestion Control and Traffic Shaping. | Part 3 deals with the operations and management of computer networks encompassing SDN's (Software Defined Networks), Traffic Engineering and Network Security.
This class teaches you about basic concepts in theoretical computer science -- such as NP-completeness -- and what they imply for solving tough algorithmic problems.
Learn cutting-edge computer vision and deep learning techniques—from basic image processing, to building and customizing convolutional neural networks. Apply these concepts to vision tasks such as automatic image captioning and object tracking, and build a robust portfolio of computer vision projects.
In this course, you’ll learn how to proactively test what you have put in place to protect your data. In the first week you’ll be able to discuss the basics of deterrents and how to “trick” attackers into believing they’ve hit a goldmine of data away from your real systems. In week 2, you’ll be able to understand and discuss the steps of penetration testing methodology. In week 3, you will be able to understand and apply what you have learned on your own systems to test whether your systems are secure or not. In week 4, we’ll discuss planning for your own methodology that you can apply to your own systems. And finally in week 5, we’ll finish up with a project that will allow you to test your skills in a safe environment.
This is part one of a five part course that’s designed to provide a comprehensive education on all the major aspects of an IT Support Specialist. By the end of this series you’ll have all the skills required to qualify for an entry level position. In this course you will learn a skill set that you can build on throughout this series of courses or continue your education in a more traditional setting. Either way, this course will provide you with a rock solid foundation for building up your mastery of IT Support.|We’ll be covering the basic skills of Binary, System Administration, Operating Systems, Networking, and Security. In subsequent courses, we’ll be going in depth in all of these major aspects. We’ll be focusing specifically on an IT help desk, but the knowledge and skills learned here have a broad scope of application within the field.|By the end of this first course, you'll be able to understand how a computer thinks and communicates using binary, what abstraction is and how to apply it to your work, troubleshooting skills and techniques and how to best apply them. We'll break down the hardware part by part and learn how they all function and work together to create a operational machine. We'll also be doing breakdowns on Software, Operating Systems, and how to troubleshoot issues. How to install software, how to install Operating Systems, like Windows, and how to build a desktop from scratch. You'll also gain the skills for strong documentation, how to manage computers, what a network is and how it functions and a whole lot more!|In addition, you'll learn How to properly interact with customers, and coworkers in an IT environment and be able to utilize powerful problem solving skills and how to implement effective solutions. These core concepts will be the foundation for everything and provide you with the understanding that you’ll need to learn more complicated aspects of IT Support.
Join a live online community of over 140,000+ developers and a course taught by an industry expert that has actually worked both in Silicon Valley and Toronto as a senior developer. Graduates of this course are now working at Google, Amazon, Apple, IBM, JP Morgan, Facebook + other top tech companies. Want to land a job at a great tech company like Google, Microsoft, Facebook, Netflix, Amazon, or other companies but you are intimidated by the interview process and the coding questions? Do you find yourself feeling like you get "stuck" every time you get asked a coding question? This course is your answer. Using the strategies, lessons, and exercises in this course, you will learn how to land offers from all sorts of companies. Many developers who are "self taught", feel that one of the main disadvantages they face compared to college educated graduates in computer science is the fact that they don't have knowledge about algorithms, data structures and the notorious Big-O Notation. Get on the same level as someone with computer science degree by learning the fundamental building blocks of computer science which will give you a big boost during interviews. You will also get access to our private online chat community with thousands of developers online to help you get through the course. Here is what you will learn in this course: Technical: 1. Big O notation 2. Data structures: * Arrays * Hash Tables * Singly Linked Lists * Doubly Linked Lists * Queues * Stacks * Trees (BST, AVL Trees, Red Black Trees, Binary Heaps) * Tries * Graphs 3. Algorithms: * Recursion * Sorting * Searching * Tree Traversal * Breadth First Search * Depth First Search * Dynamic Programming Non Technical: - How to get more interviews - What to do during interviews - What do do after the interview - How to answer interview questions - How to handle offers - How to negotiate your salary - How to get a raise Unlike most instructors, I am not a marketer or a salesperson. I am a senior developer and programmer who has worked and managed teams of engineers and have been in these interviews both as an interviewee as well as the interviewer. My job as an instructor will be successful if I am able to help you become better at interviewing and land more jobs. This one skill can really change the course of your career and I hope you sign up today to see what it can do for your career! Taught by: Andrei is the instructor of the highest rated Web Development course on Udemy as well as one of the fastest growing. His graduates have moved on to work for some of the biggest tech companies around the world like Apple, Google, JP Morgan, IBM, etc... He has been working as a senior software developer in Silicon Valley and Toronto for many years, and is now taking all that he has learned, to teach programming skills and to help you discover the amazing career opportunities that being a developer allows in life. Having been a self taught programmer, he understands that there is an overwhelming number of online courses, tutorials and books that are overly verbose and inadequate at teaching proper skills. Most people feel paralyzed and don't know where to start when learning a complex subject matter, or even worse, most people don't have $20,000 to spend on a coding bootcamp. Programming skills should be affordable and open to all. An education material should teach real life skills that are current and they should not waste a student's valuable time. Having learned important lessons from working for Fortune 500 companies, tech startups, to even founding his own business, he is now dedicating 100% of his time to teaching others valuable software development skills in order to take control of their life and work in an exciting industry with infinite possibilities. Andrei promises you that there are no other courses out there as comprehensive and as well explained. He believes that in order to learn anything of value, you need to start with the foundation and develop the roots of the tree. Only from there will you be able to learn concepts and specific skills(leaves) that connect to the foundation. Learning becomes exponential when structured in this way. Taking his experience in educational psychology and coding, Andrei's courses will take you on an understanding of complex subjects that you never thought would be possible. See you inside the courses!
This course is an introductory course on human-computer interaction, covering the principles, techniques, and open areas of development in HCI.
The advanced course in Digital Forensics offered by edX includes principles and techniques for digital forensics investigation and the spectrum of available computer forensics tools. The course aims at educating the professionals about forensics procedures to ensure court admissibility of evidence, as well as the legal and ethical implications. The course also focuses on teaching how to perform a forensic investigation on both Unix/Linux and Windows systems with different file systems. The program is designed for candidates seeking an advanced career in the field of computing security.
Vskills certification for Software Security Professional assesses the candidate for a company’s secured software development needs. The certification tests the candidates on various areas in software security which includes knowledge of various types of security attacks and countermeasures on programming language (C/C++, Java and .Net), web applications, web services, SOA-based application, and mobile applications and tools used.
Welcome to Tensorflow 2.0! What an exciting time. It's been nearly 4 years since Tensorflow was released, and the library has evolved to its official second version. Tensorflow is Google's library for deep learning and artificial intelligence . Deep Learning has been responsible for some amazing achievements recently, such as: Generating beautiful, photo-realistic images of people and things that never existed (GANs) Beating world champions in the strategy game Go, and complex video games like CS:GO and Dota 2 (Deep Reinforcement Learning) Self-driving cars (Computer Vision) Speech recognition (e. G. Siri) and machine translation (Natural Language Processing) Even creating videos of people doing and saying things they never did (DeepFakes - a potentially nefarious application of deep learning) Tensorflow is the world's most popular library for deep learning, and it's built by Google, whose parent Alphabet recently became the most cash-rich company in the world (just a few days before I wrote this). It is the library of choice for many companies doing AI and machine learning. In other words, if you want to do deep learning, you gotta know Tensorflow. This course is for beginner-level students all the way up to expert-level students. How can this be? If you've just taken my free Numpy prerequisite, then you know everything you need to jump right in. We will start with some very basic machine learning models and advance to state of the art concepts. Along the way, you will learn about all of the major deep learning architectures, such as Deep Neural Networks, Convolutional Neural Networks (image processing), and Recurrent Neural Networks (sequence data). Current projects include: Natural Language Processing (NLP) Recommender Systems Transfer Learning for Computer Vision Generative Adversarial Networks (GANs) Deep Reinforcement Learning Stock Trading Bot Even if you've taken all of my previous courses already, you will still learn about how to convert your previous code so that it uses Tensorflow 2.0, and there are all-new and never-before-seen projects in this course such as time series forecasting and how to do stock predictions. This course is designed for students who want to learn fast, but there are also "in-depth" sections in case you want to dig a little deeper into the theory (like what is a loss function, and what are the different types of gradient descent approaches). Advanced Tensorflow topics include: Deploying a model with Tensorflow Serving (Tensorflow in the cloud) Deploying a model with Tensorflow Lite (mobile and embedded applications) Distributed Tensorflow training with Distribution Strategies Writing your own custom Tensorflow model Converting Tensorflow 1.x code to Tensorflow 2.0 Constants, Variables, and Tensors Eager execution Gradient tape Instructor's Note: This course focuses on breadth rather than depth, with less theory in favor of building more cool stuff. If you are looking for a more theory-dense course, this is not it. Generally, for each of these topics (recommender systems, natural language processing, reinforcement learning, computer vision, GANs, etc.) I already have courses singularly focused on those topics. Thanks for reading, and I'll see you in class!