|Course or Certification Name||Category||Location||Mode of learning|
|Vskills Certified Data Entry Operator Government Certification||Data Entry||Offline self study|
|Python for Computer Vision with OpenCV and Deep Learning||Data Analysis||Online self study|
|Taming Big Data with Apache Spark 3 and Python - Hands On!||Data Science||Online self study|
|R for Data Analysis||Data Analysis||Online self study|
|Master the Coding Interview: Data Structures + Algorithms||Relational Databases||Online self study|
|Simplilearn Data Scientist Master's Program||Data Science||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|The Python Mega Course: Build 10 Real World Applications||Data Analysis||Online self study|
|Big Data Hadoop Expert Program - Online Classroom||Big Data||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)||Data Science||Online self study|
|The Complete Tableau Bootcamp for Data Visualization||Data Visualization||Online self study|
|Data Science and Machine Learning Bootcamp with R||Data Science||Online self study|
|Big Data Hadoop Solutions Architect Masters Program||Hadoop Administration||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Big Data and Machine Learning Prodegree||Big Data||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Data Science with R Professional||Data Science||Online self study|
|Big Data Fundamentals||Big Data||Online self study|
Data Entry Operators have good typing and numeric entry skills, and they help companies in updating data into a computer system database. Vskills Certified Data Entry Operator course assesses the candidateâ€™s ability to entry data as per the companyâ€™s requirements. This specially designed government-certified course helps the candidate to acquire the necessary technical skills for typing and entry through the usage of MS-Office software. It tests the candidateâ€™s ability to ensure correct and fast entry.
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
New! Updated for Spark 3 and with a hands-on structured streaming example. Big data" analysis is a hot and highly valuable skill and this course will teach you the hottest technology in big data: Apache Spark . Employers including Amazon , EBay , NASA JPL , and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Windows system right at home. It's easier than you might think. Learn and master the art of framing data analysis problems as Spark problems through over 15 hands-on examples, and then scale them up to run on cloud computing services in this course. You'll be learning from an ex-engineer and senior manager from Amazon and IMDb. Learn the concepts of Spark's Resilient Distributed Datastores Develop and run Spark jobs quickly using Python Translate complex analysis problems into iterative or multi-stage Spark scripts Scale up to larger data sets using Amazon's Elastic MapReduce service Understand how Hadoop YARN distributes Spark across computing clusters Learn about other Spark technologies, like Spark SQL, Spark Streaming, and GraphX By the end of this course, you'll be running code that analyzes gigabytes worth of information in the cloud in a matter of minutes. This course uses the familiar Python programming language ; if you'd rather use Scala to get the best performance out of Spark, see my "Apache Spark with Scala - Hands On with Big Data" course instead. We'll have some fun along the way. You'll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most popular" superhero is and develop a system to find degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to The Incredible Hulk? You'll find the answer. This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together both on your own system, and in the cloud using Amazon's Elastic MapReduce service. 5 hours of video content is included, with over 15 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX. Wrangling big data with Apache Spark is an important skill in today's technical world. Enroll now! " I studied "Taming Big Data with Apache Spark and Python" with Frank Kane, and helped me build a great platform for Big Data as a Service for my company. I recommend the course! " - Cleuton Sampaio De Melo Jr.
This free online R for Data Analysis course will get you started with the R computer programming language. In this course, you will learn how the data analysis tool, the R programming language, was developed in the early 90s by Ross Ihaka and Robert Gentleman at the University of Auckland, and has been improving ever since. You will also learn about how data analysis systematically evaluates data using analytical and logical reasoning, and more!
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 Master's Program provides training in the skills required to become a certified data scientist. You'll learn the most in-demand technologies such as Data Science on R, SAS, Python, Big Data on Hadoop and implement concepts such as data exploration, regression models, hypothesis testing, Hadoop, and Spark.
The Python Mega Course is the most practical course you will find on the web today. So far, over 140,000 students have used the course to learn Python programming and to build real-world applications in Python 3. You will learn how to build Python apps during this course, even if you know nothing about programming. You will start from scratch and progressively build up your skills by creating some awesome Python programs ranging from webcam object detection apps, to data collector web apps that query data from SQL databases, to data visualization dashboards on the browser. The course has it all to make you an all-round Python programmer that not only knows Python but also the technologies you need to know to create professional applications. The course follows a modern-teaching approach where students learn by doing . You will start Python from scratch by creating simple programs first. Once you learn the basics, you will then start with the fun part, which is building 10 real-world applications. You will code the apps, guided step-by-step by easy video explanations and continuous support from the course instructor. The applications you will build in the course consist of database apps , web apps , desktop apps , web scraping scripts , webcam object detectors , web maps , data visualization dashboards , and more. These programs are not only great examples to help master Python, but you can also use them for your portfolio. By buying the course you will gain lifetime access to all of its videos, coding exercises, quizzes, code notebooks, cheat sheets, and the Q&A inside the course, where you can ask your questions and get an answer on the same day. On top of that, you are covered by the Udemy 30-day money-back guarantee , so you can easily return the course if you don't like it. If you don't know anything about Python, do not worry! In the first 12 sections, you will learn Python basics such as functions, loops, and conditionals and learn how to apply the basics by doing some examples. If you already know the basics, then the first 12 sections can serve as a refresher. The other 20 sections focus entirely on building real-world applications. The applications you will build cover a wide range of interesting topics: Web applications Desktop applications Database applications Web scraping Web mapping Data analysis Data visualization Computer vision Object-Oriented Programming Specifically, the 10 Python applications you will build are: A program that returns English-word definitions A program that blocks access to distracting websites A web map visualizing volcanoes and population data A portfolio website A desktop-graphical program with a database backend A webcam motion detector A web scraper of real estate data An interactive web graph A database web application A web service that converts addresses to geographic coordinates To consider yourself a professional programmer you need to know how to write professional programs and there's no other course that teaches you that, so join thousands of other students who have successfully applied their Python skills in the real world. Sign up and start learning the amazing Python programming language today! Frequently Asked Questions Will I be able to learn Python and find a job after completing this course? I have heard of quite a few success stories where students have rigorously followed the course and have found a job afterwards. However, whether you will be able to learn Python and be job-ready, heavily depends on you. If you merely watch the videos, without trying anything on your own, you will hardly learn anything. Instead, you have to try the code you see in the videos on your computer, change the code, run it, improve it further, run it again, fix the possible errors, try making a similar app, repeat, ask questions in the Q&A when you get stuck, and try to solve all the exercises in the course. That way you will certainly learn how to program with Python and be able to find a job. How much time will I need to complete the course? That depends on two factors: (1) Your background: Someone coming from a math or computer science background may be able to complete the course in a shorter time compared to someone coming from a social science background for example. (2) The effort you put in: If you just watch the videos, you may finish the course in two days. However, simply watching the videos is not enough. You need to experiment with the code you see in the videos. The more you experiment with it the better you become. Depending on the two factors I mentioned above, students spend from one week to three months to complete the course, most spending one month. I don't know anything about programming. Will I still be able to learn Python? This course assumes you have no previous knowledge of programming. Whenever a programming term is mentioned (e. G. a variable) the meaning of the term is explained thoroughly so you not only understand how to use that particular term in Python, you also understand what that term means in programming. Will I get support if I get stuck? Yes. Feel free to drop a question in the Q&A, and me, or my teaching assistant, will answer your questions within the same day. Does this course cover Python 2 or Python 3? Python 3 What IDE/editor is used in the course? Visual Studio Code is used in the course. It is very new and probably the best IDE that exists today. However, you can use your favorite IDE. The code will work the same, no matter the IDE. Does the course expire? No. Once you buy the course it's yours. I update the content regularly and all the updates are also included for free in the one-time purchase you make.
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. | Mastering Hadoop and related tools: The course provides you with an in-depth understanding of the Hadoop framework including HDFS, YARN, and MapReduce. | Mastering real-time data processing using Spark: You will learn to do functional programming in Spark, implement Spark applications, understand parallel processing in Spark, and use Spark RDD optimization techniques. | The â€˜Impala-an Open Source SQL Engine for Hadoopâ€™ is an ideal course package for individuals who want to understand the basic concepts of Massively Parallel Processing or MPP SQL query engine that runs on Apache Hadoop. On completing this course, learners will be able to interpret the role of Impala in the Big Data Ecosystem. | MongoDB Developer and Administrator certification from Simplilearn would equip you to master the skills to become MongoDB experienced professional. By going through this MongoDB training you would become job ready by mastering data modelling, ingestion, query and Sharding, Data Replication with MongoDB along with installing, updating and maintaining MongoDB environment. | Apache Kafka is an open source Apache project. It is a high-performance real-time messaging system that can process millions of messages per second. It provides a distributed and partitioned messaging system and is highly fault tolerant.
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)
Welcome to the best online resource for learning about Tableau 10! This course will teach you everything you need to know to create amazing data visualizations and dashboards with Tableau! Every module of this course is carefully designed to teach you what you need to know to create amazing data visualizations and dashboards with Tableau. We start with the basics and gradually build up your Tableau skill set by leveraging awesome real world data sets to create visualizations for your portfolio of projects. Upon completing this course you will be ready to tackle your own data projects with real world data sets and create Tableau dashboards to show off to your colleagues or even potential employers. Completion of this course also includes a certification you can post to your LinkedIn profile! Inside the course we'll cover: Installing and setting up Tableau Public on your computer Visual Analytics with Tableau Tableau Mapping for Geographical Data Basic Calculations Table Calculations Level of Detail (LOD) Expressions Joins and Unions Interactive Worksheets with Set Actions and Parameter Control Spatial Mapping Understanding Color Vision Deficiency Build Sophisticated Dashboards and Unique, Engaging Stories through the Power of Data Visualization and much, much more! Not only do you get great technical content, but you will also get access to our Question and Answer Forums, where you and other students can get help on the course material and content. All of this comes with a 30-day money back guarantee so you can enroll today completely risk free! We'll see you inside the course!
Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems! This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science! This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy! We'll teach you how to program with R, how to create amazing data visualizations, and how to use Machine Learning with R! Here a just a few of the topics we will be learning: Programming with RAdvanced R FeaturesUsing R Data Frames to solve complex tasksUse R to handle Excel FilesWeb scraping with RConnect R to SQLUse ggplot2 for data visualizationsUse plotly for interactive visualizationsMachine Learning with R, including:Linear RegressionK Nearest NeighborsK Means ClusteringDecision TreesRandom ForestsData Mining TwitterNeural Nets and Deep LearningSupport Vectore Machinesand much, much more! Enroll in the course and become a data scientist today!
Designed to make certain that you change into a Hadoop Architect master, Big Data Hadoop Masters Program is a structured learning program recommended by famous industry experts. This certification includes real life projects that let you work through technical challenges connected with Hadoop Administration. When you complete the requirement of the course, you will get master certificate from Naukri learning certifying that you have gained the knowledge of Big Data Hadoop Solutions Architect. You will get knowledge in designing, maintaining and deploying Hadoop clusters and Nosql database technologies.
The Big Data and Machine Learning Prodegree, in association with IBM as the EdTech Partner, is a first-of-its-kind 160-hour certification course providing in-depth exposure to Data Science, Big Data, Machine Learning and Deep Learning. The rigorous industry-aligned curriculum offers a comprehensive understanding of Python, Spark and Hadoop for careers in Machine Learning and Big Data. The program also features seven industry projects and periodic interaction with industry leaders in the Machine Learning Ecosystem.
Data Science is an inter-disciplinary filed that uses scientific methods, processes and systems to extract useful insights from data. R is an open-source programming language used in data science for statistical computing and graphics. | This Certified Data Science with R Professional course has been specifically designed for candidates to get the requisite skills and knowledge to work as data scientists | It also provides the necessary training to the candidates to have working experience in R as per the requirements for data analysis and statistical computing | The course has been developed by expert professionals and has quality online learning modules | It offers candidates a course-completion certification, accepted globally
The course covers the way team works in big data companies, some challenges and opportunities that big data offers. You will also learn how big data is driving organizational change and the main challenges companies face when trying to analyze massive data sets. Besides, some fundamental techniques like big data stack, data mining and stream processing. In this training program, you will come across a number of tools for working with big data. It also lets you learn the technique of storing, processing and deploying in an enterprise scenario. You will gain a deep knowledge of what insights big data can offer through hands-on experience with the tools used by big data experts. At the end of the course, you will have a better understanding of the different applications of big data in industry.