|Course or Certification Name||Category||Location||Mode of learning|
|Training Diploma in Mechanical Engineering||Engineering Design||Classroom|
|Big Data Engineering Training Course||Big Data||Online self study|
|Computer Networking||Routing & Network Support||Online self study|
|Vskills Certified Engineering Design Professional||Engineering Design||Online self study|
|Computer Hacking Forensic Investigator Certification||Ethical Hacking||Online self study|
|Big Data Engineering Perspectives||Big Data||Online self study|
|Virtualization Certification Training||Virtual Machine||Online self study|
|MSc Financial Engineering||MTech Full-time||Online self study|
|Piping Engineering||Engineering Design||Classroom|
|Python for Computer Vision with OpenCV and Deep Learning||Data Analysis||Online self study|
|Computer Hacking and Forensics||Ethical Hacking||Online self study|
|PG Diploma in System Software Development(PG-DSSD)||Emerging Web Technologies||Classroom|
|Master the Coding Interview: Data Structures + Algorithms||Relational Databases||Online self study|
|Post graduate Diploma in Financial Engineering and Risk ManagementÂ||Executive MBA||Classroom|
|Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)||Data Science||Online self study|
Big data, in simple terms, refer to the huge amount of data set that cannot be usually analysed using traditional methods. Big data is a growing field and many businesses are adopting it to improve their business functions; leading to a spurt in the demand for expert professionals in the field. | Big Data Engineering course is aimed at providing the best-in-the-industry training to the candidates who are looking to get success in big data field | The course has quality online learning modules which have been developed by subject matter experts | Providing the necessary skills, the course has a comprehensive coverage of all important topics related to big data engineering
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.
Engineering Design is the process of devising a system, component, or process to meet desired needs. The course, Engineering Design, is specially made to teach the decision making process (often iterative) in which the basic sciences, mathematics, and engineering sciences are applied to convert resources optimally to meet a stated objective. The course is very beneficial for engineering and management professionals or students pursuing post graduation studies. | The certification tests the candidates on various areas in product planning, product specifications, prototyping, design for quality and reliability.
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 todayâ€™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.
Big data is a term for data sets so large that traditional data processing applications can not be used to perform any sort of analysis. It is often semi structured or unstructured in form. There are a number of unique challenges that arise when companies begin to use big data. The least of which are the engineering concerns. This course will introduce some of those engineering challenges and describe how some companies have come up with solutions.
This Virtualization course is a course package of multiple courses and chapters on Virtualization and its related cloud computing techniques. It consists of multiple courses in the Virtualization course including the course completion certification. It also contains several other modules that contain Virtualization related concepts such as Server virtualization, VMWare center, vSphere training etc.
The program is designed for students with 1-2 years of experience as well as fresh graduates in Math, Statistics, Engineering, Technology, Business, Economics, Finance, Computer Science etc | The program provides students with a broad-based education in high technology finance, combining the technical and conceptual advances in Computer Science, Mathematics and Finance | Program integrates Quantitative and Qualitative Finance for practical use of advanced financial techniques in the industry prepares participants to meet the challenges and rigors of the new marketplace | The program is offered in collaboration with Carnegie Mellon University, USA | Prominent Recruiters from past batches - Singapore Exchange, PwC, Ernst & Young, Deutsch Bank, JP Morgan, Asian Development Bank, Goldman Sachs, Calyon Corporate and Investment Bank, Algorithmics and many more
Piping Engineering course is one-of-a-kind. This course is structured to raise the level of expertise in piping design and to improve the competitiveness in the global markets. This course provides various piping system designs, development skills and knowledge of current trends of plant layout. The students are given case studies to develop their professional approach
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
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.
C-DAC has taken up the challenge to address the need for trained system software development professionals by introducing an in-depth course Post Graduate Diploma in System Software Development (PG DSSD) giving emphasis to secure software design & implementation practices as per the Industry needs. Post Graduate Diploma in System Software Development (PG DSSD) is a 22 weeks fulltime course consisting of 9 modules including an industry relevant project and a seminar. C-DAC which is doing pioneering research work in providing system and network security solutions has the requisite expertise to conceive, design to develop and implement training program in system software development. The result of their efforts is the most successful career oriented course â€œPost Graduate Diploma in System Software Developmentâ€ (PG DSSD) for Engineers in Electronics, Computer Science and Information Technology and also for Computer Science Post Graduates.
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!
Post Graduate Diploma in Financial Engineering and Risk Management (PGDFERM) is a specific programme by National Institute of Securities Markets (NISM). The programme aims to equip the participants with skills in treasury and risk management functions. The course is a combination of basic and advanced theory and practical, and a combination of mathematics, statistics, financial economics, computational finance financial modelling and risk management. | The course will be offered in two different Formats - | Format A: Weekend programme at Vashi. | Format B: Residential programme at Vashi.
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)