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[100% OFF] MERN Stack Master Course - Building your own Instagram Free

MERN stands for MongoDB, Express.js, React.js and Node.js - and combined, these four technologies allow you to build amazing web applications In this course we will be building FULL FLEDGED INSTAGRAM website and it will be a lots of fun as we building this together. This course covers - Building an backend API with Node.js & Express Testing API using Postman JWT based authentication Image upload Context API for state management React Hooks React Router hooks Protecting routes or endpoints Sending Emails Forgot & Reset Password This course is NOT an introduction course to React & Node js. It is fully hands on course for building full stacks websites using MERN

[100% OFF] The Complete Guide Angular 8 for Java Developers 2020 Free

Angular is a TypeScript-based open-source front-en... Mored web application platform led by the Angular Team at Google and by a community of individuals and corporations to address all of the parts of the developer's workflow while building complex web applications. Angular is a complete rewrite from the same team that built AngularJS. Angular is a framework for building client applications in HTML and either JavaScript or a language like TypeScript that compiles to JavaScript. Angular combines declarative templates, dependency injection, end to end tooling, and integrated best practices to solve development challenges. Angular empowers developers to build applications that live on the web, mobile, or the desktop. This course is for existing Java developers who want to learn the popular Angular framework for developing front-end Web interfaces. In the course we cover all of the main principles of building websites in Angular, including the Typescript Language. This is taught with reference to Java and Java web technology examples, making it a very quick and easy way for Java developers to upgrade their skills to Angular. No prior knowledge of Javascript or Typescript is needed, although some basic HTML is useful. Who this course is for: web developers, .net developers, java developers, python developers Less
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[100% OFF] SVM for Beginners: Support Vector Machines in R Studio Free

You're looking for a complete Support Vector Machi... Morenes course that teaches you everything you need to create a SVM model in R, right? You've found the right Support Vector Machines techniques course! How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course. If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the advanced technique of machine learning, which are Support Vector Machines. Why should you choose this course? This course covers all the steps that one should take while solving a business problem through SVM. Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business. What makes us qualified to teach you? The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones: This is very good, i love the fact the all explanation given can be understood by a layman - Joshua Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. Download Practice files, take Quizzes, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning. Go ahead and click the enroll button, and I'll see you in lesson 1! Cheers Start-Tech Academy Who this course is for: People pursuing a career in data science Working Professionals beginning their Data journey Statisticians needing more practical experience Anyone curious to master SVM technique from Beginner to Advanced in short span of time Less
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[100% OFF] The Complete IP Subnetting Course: Beginner to Advanced! Free

This course dives deep into IPv4 addressing and IP... Morev4 subnetting. Starting with binary math and ending with difficult IPv4 subnetting problems this course will prepare you for the subnetting questions on the CCNA, MCSA and CompTIA Network+ exams. Full of shortcuts and useful insights you will gain the clearest understanding of IPv4 addressing and IPv4 subnetting you have every had. This course divides the material up into small increments and then conquers each with multiple examples, practice questions and video explanations. You will never just get stuck on IPv4 subnetting again. We actively monitor the Q&A forum and will respond to every relevant question with a helpful answer. We are committed to helping every student achieve their learning goals and will listen to all comments and suggestions. Less
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[100% OFF] CYBER SECURITY SPECIALIZATION : Part 1 Free

The growth in the technological field is exponenti... Moreal. Day by day, the IT sector is flourishing to a greater extent. With such rapid growth, the need for security is also increasing. People have started becoming concerned about their privacy. Cybersecurity issues are becoming a day-to-day struggle for businesses. Recent trends and cyber security statistics reveal a huge increase in hacked and breached data from sources that are common in the workplace. With these growing trends, every individual must be aware of security and that is why you should go for this course! Most of the people are often confused when they are asked - “WHAT IS CYBER SECURITY?” The most common reply is - “UM, HACKING. ” Well, hacking is part of cyber security but it really doesn’t mean that hacking is the synonym of cyber security. Many courses out there are only focusing on the practical approach of cyber security - HACKING. Well, hacking is not the only domain of cyber security. There are other domains also, for example Incident Response Team, Blue team, Security Audits, IT Security Management, Security laws and many more. In order to start practicing hacking, you should first know the concepts! You should understand how the world is dealing with cyber threats. HACKING is not the only “coolest” thing here. There are other security topics as well. !!!! Hackers attack every 39 seconds, on average 2,244 times a day. !!!! So are you sure that your data is well protected from these hackers? Have you even configured your network to maintain your privacy? Do you know how hackers can gain access to your devices without you even getting notified? Well, don’t worry! We are here to answer these questions. There might be many questions in your mind regarding this course. We will surely address all of them once you enroll for this course, but for the time being, we’ll focus on the following questions: WHY SHOULD I LEARN CYBER SECURITY? Let’s face it. We live in a digital world. Our work lives, personal lives, and finances have all begun gravitating toward the world of the internet, mobile computing, and electronic media. Unfortunately, this widespread phenomenon makes us more vulnerable than ever to malicious attacks, invasions of privacy, fraud, and other such frightening cases. That’s why cyber security is such a vital part of a secure and well-ordered digital world. Cybersecurity keeps us safe from hackers, cyber criminals, and other agents of fraud. But let me ask you a question, HOW GOOD IS YOUR KNOWLEDGE ABOUT CYBER SECURITY? Here are some facts that would blow up your mind! According to Varonis, Worldwide spending on cyber security is forecasted to reach $133.7 billion in 2022. Data breaches exposed 4.1 billion records in the first half of 2019. Symantec says, the top malicious email attachment types are .doc and .dot which make up 37%, the next highest is .exe at 19.5% These are not just facts but they are warnings! Everyone who is accessing a device should be aware of their security and that is why we have designed this course. Okay, here comes the next question. UM, OKAY! BUT WHY SHOULD I ENROLL FOR THIS COURSE? The perfect answer to this question would be - Have a look at our curriculum. THE FUNDAMENTALS OF CYBER SECURITY, is the first part of our CYBER SECURITY SPECIALIZATION. In this course, we have covered right from the basics of computer networking to the advance concepts such as cryptography, security auditing, incident management. Yes, we have actually started from the definition of a Computer Network. Our course is broadly divided into seven sections. In the first section we have covered the basics of networking. We have discussed different protocols and their usage. We have talked about IP addresses and their classes and a lot of things which are important from the point of view of cyber security. Bonus Material - We have included practicals also! From the second section we are actually talking about cyber security. Right from the history of cyber security to different terminologies have been discussed in this section. We have designed the curriculum in such a way that even a novice can understand cyber security and we are so sure that this course would actually give a better idea of cyber security. You will learn about critical thinking and its importance to pursue a career in Cyber security. You will also learn about organizations and resources to further research cyber security issues in the Modern era. This course is intended for anyone who wants to gain a basic understanding of Cyber security or as the first course in a series of courses to acquire the skills to work in the Cybersecurity field as a Jr Cybersecurity Analyst. We recommend you to watch our introductory video where we have discussed the entire syllabus :) Have a look at few highlights from our course. Handpicked curriculum, specially designed for all levels of learners. Continuous assessment through challenging quizzes Get your questions answered within 48 hours A variety of resources such as useful links, books, PDFs are also provided Regular updates related to cyber security Exploration of different aspects of Cybersecurity Practicals are also included along with theory You will understand how cryptography works in real life Concepts such as firewalls, antivirus, cyber attacks are also discussed and Many more. We encourage suggestions WHO CAN ENROLL FOR THIS COURSE? This course is not intended for a specific group of people. Anyone who wants to learn about cyber security can enroll for this course. If you already know about security, you can always revisit the ideas and clear your doubts if you have any. We have not only covered the technical topics but also included all the statistics as well. For example we have discussed the scope of cyber security along with the career insights and also the salaries of different job roles in this field. This course will help you to decide whether you want to become a Penetration tester or security auditor or Red Team Specialist. In short, this is the perfect course if you want to kick start your career in cyber security! BOTTOM LINE - Once you move ahead in this course, you will get a clear idea about cyber sec. The way we have put all the things together helps the learner in creating an interest in this field. We would like to assure one thing to you - THIS COURSE WILL LITERALLY TELL YOU EVERYTHING ABOUT CYBER SECURITY. Happy Learning! Less
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[100% OFF] The Complete Python 3 Course: Beginner to Advanced! Free

If you want to get started programming in Python, ... Moreyou are going to LOVE this course! This course is designed to fully immerse you in the Python language, so it is great for both beginners and veteran programmers! Learn Python as Nick takes you through the basics of programming, advanced Python concepts, coding a calculator, essential modules, creating a "Final Fantasy-esque" RPG battle script, web scraping, PyMongo, WebPy development, Django web framework, GUI programming, data visualization, machine learning, and much more! We are grateful for the great feedback we have received! "This course it great. Easy to follow and the examples show how powerful python can be for the beginner all the way to the advanced. Even if the RPG may not be your cup of tea it shows you the power of classes, for loops, and others!" "Good course even for non-programmers too." "It's really well explained, clear. Not too slow, not too fast." "Very thorough, quick pace. I'm learning A TON! Thank you :)" "Good explanation, nice and easy to understand. Great audio and video quality. I have been trying to get into Python programming for some time; still a long way to go, but so far so good!" The following topics are covered in this course: Programming Basics Python Fundamentals JavaScript Object Notation (JSON) Web Scraping PyMongo (MongoDB) Web Development Django Web Framework Graphical User Interface (GUI) Programming (PyQt) Data Visualization Machine Learning This course is fully subtitled in English! Thank you for taking the time to read this and we hope to see you in the course! Who this course is for: This course was designed for students with little to no programming experience Developers familiar with Python can take their knowledge to the next level! Students who go through the course can expect to walk away with a comprehensive understanding of Python Less
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[100% OFF] Java For Everyone - Zero to Hero free

Core Java, OOPS, Collection, Exception Handling, D... Moreesign Pattern. Core concepts of Java including Variables, datatypes, operators, control statements, arrays, packages, classpath, user-input and debugging Object Oriented Programming concepts with read life examples String with memory mapping Exception handling Java collections Design patterns And also you will learn how to debug code in eclipse. Less
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[100% OFF] Data Structures And Algorithms In The C Programming Language Free

Have you already got some experience in the C prog... Moreramming language but want to take it further? Then this course is for you. This course will teach you all about creating internal data structures in C. This course will teach you how to create the following: Linked List Implementation Double Linked List Implementation Array List Implementation Queue Implementation Stack Implementation Binary Tree Implementation All of the implementations described above will be created on video from scratch! You will learn how all of these work internally and when they should be used. This course is a "must have" for someone who has learned the fundamentals of the C Programming Language Who this course is for: C programmers who want to learn how to develop data structures in their applications Less
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[100% OFF] Learn Creational Design Patterns in Java Free

Design patterns provide a template for writing qua... Morelity code. Knowing which design pattern to use in which scenario can be challenging but will make you a master Java programmer. In this course you will take a deep dive into creational patterns, which can help you create more flexible, reusable objects. I will be covering the six most popular creational patterns— Builder, Telescoping Constructor, Singleton, Prototype, Factory and Abstract Factory as well as concepts such as multithreading, mutability, inheritance and Java Heap and Stack workings. I will provide example use cases, complete with implementation instructions and tips for avoiding the unique challenges posed by each pattern also explain how do design patterns work inside Java Heap and Stack Memory. By the end of this course, you'll be equipped with the knowledge and skills necessary to implement each design patterns in your Java projects. Learning Objectives: What are creational design patterns? How to avoid complex constructors? Implementing the Builder pattern Implementing the Telescoping pattern Understanding similarity between Builder and Telescoping pattern Best interview answers for Singleton pattern Questions. Also get a practical idea about the advance concepts such as serialization, cloning, multi-threading and reflection Problem and Solution of Multi-threading with the Singleton pattern Implementing the Prototype pattern Best interview answers for Prototype pattern Questions. Implementing simple Factory pattern Implementing Abstract Factory pattern Who this course is for: Java Developer Java Developer curious about design patterns Java Architect Nail your Java Interviews Web Application Developers Industrial experts API Developers Tech Architects Less
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[100% OFF] CSS Flexbox Quick introduction to using FlexBox CSS style Free

Explore more about using Flexbox with examples and... More sample code to get you coding. Flexbox is a one-dimensional layout method for laying out items in rows or columns. Items flex to fill additional space and shrink to fit into smaller spaces Please note that the scope of this course using CSS Flexbox. If you are looking for a more detailed CSS course this course is not for you. Simple course with limited scope designed to be topic specific. Taught by an instructor with over 20 years of Web Development experience. If you've been looking to get started with CSS Flexbox - THIS COURSE IS FOR YOU!!!! Nothing to lose - Fast friendly support is always available to help if you need it. Please note that the SCOPE OF THIS COURSE IS Creating and using CSS flexbox and will not cover complex commands and everything about CSS, HOW TO GET STARTED COURSE - if you are looking at more detailed node or JavaScript content this is not for you. Who this course is for: Web developers Web designers Anyone who is building a website Webmasters and web coders creating web content Less
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[100% OFF] Python for beginners - Learn all the basics of python Free

Have you always wanted to learn programming but di... Moredn't know where to start ? Well now you are at the right place ! I created this python course to help everyone learn all the basics of this programming language. This course is really straight to the point and will give you all the notion about python. Also, the course is not that long so and the way the material is presented is very easy to assimilate. So if python is something that you are interested about, then you will definitely like this course. Enjoy your learning :) Who this course is for: People interested to learn how to program in python people curious about programming Less
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[100% OFF] The Complete AngularJS Authentication 2020 | Certified Free

Authentication for traditional web applications is... More fairly straight-forward: we send our credentials to the server, a session is created, and a cookie is returned to be saved in the browser. This method works well for round-trip applications, but it isn't a good way to do authentication in modern single page apps, like those built with AngularJS. In this course we are going to learn about the challenges associated with traditional authentication and how to use what is arguably the best alternative: the JSON Web Token. Using that knowledge, we'll implement authentication in an AngularJS app that makes calls to an Express API. We'll cover how to address all the challenges associated with keeping a single page application in check when it comes to stateless authentication. This can be a tricky matter since the front end and backend apps are effectively separated, but we'll find out how to leverage our user's JWT to address the challenges. We'll use Auth0 as an identity and authentication server so that we don't have to roll our own. Who this course is for: Anyone that wants to learn AngularJS Less
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[100% OFF] A Guide To Learn Angular From Scratch Free

Learn the essentials you'll need to get started wi... Moreth AngularJS, a popular open-source web application framework maintained by Google. During this two-hour introductory course, your instructor will introduce you to the basics of AngularJS.The course is designed for individuals and web development professionals that need to understand the fundamentals of AngularJS.Learn about data binding, controllers and creating simple apps, along with additional ways to control the data of AngularJS applications with multiple rows of data and scope binding. Who this course is for: This course is for people who are new to Angular Less
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[100% OFF] Deep Learning for Beginners: Neural Networks in R Studio Free

You're looking for a complete Artificial Neural Ne... Moretwork (ANN) course that teaches you everything you need to create a Neural Network model in R, right? You've found the right Neural Networks course! After completing this course you will be able to: Identify the business problem which can be solved using Neural network Models. Have a clear understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc. Create Neural network models in R using Keras and Tensorflow libraries and analyze their results. Confidently practice, discuss and understand Deep Learning concepts How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Neural networks course. If you are a business Analyst or an executive, or a student who wants to learn and apply Deep learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the most advanced concepts of Neural networks and their implementation in R Studio without getting too Mathematical. Why should you choose this course? This course covers all the steps that one should take to create a predictive model using Neural Networks. Most courses only focus on teaching how to run the analysis but we believe that having a strong theoretical understanding of the concepts enables us to create a good model . And after running the analysis, one should be able to judge how good the model is and interpret the results to actually be able to help the business. What makes us qualified to teach you? The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Deep learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 250,000 enrollments and thousands of 5-star reviews like these ones: This is very good, i love the fact the all explanation given can be understood by a layman - Joshua Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. Download Practice files, take Practice test, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take practice test to check your understanding of concepts. There is a final practical assignment for you to practically implement your learning. What is covered in this course? This course teaches you all the steps of creating a Neural network based model i.e. a Deep Learning model, to solve business problems. Below are the course contents of this course on ANN: Part 1 - Setting up R studio and R Crash course This part gets you started with R. This section will help you set up the R and R studio on your system and it'll teach you how to perform some basic operations in R. Part 2 - Theoretical Concepts This part will give you a solid understanding of concepts involved in Neural Networks. In this section you will learn about the single cells or Perceptrons and how Perceptrons are stacked to create a network architecture. Once architecture is set, we understand the Gradient descent algorithm to find the minima of a function and learn how this is used to optimize our network model. Part 3 - Creating Regression and Classification ANN model in R In this part you will learn how to create ANN models in R Studio. We will start this section by creating an ANN model using Sequential API to solve a classification problem. We learn how to define network architecture, configure the model and train the model. Then we evaluate the performance of our trained model and use it to predict on new data. We also solve a regression problem in which we try to predict house prices in a location. We will also cover how to create complex ANN architectures using functional API. Lastly we learn how to save and restore models. We also understand the importance of libraries such as Keras and TensorFlow in this part. Part 4 - Data Preprocessing In this part you will learn what actions you need to take to prepare Data for the analysis, these steps are very important for creating a meaningful. In this section, we will start with the basic theory of decision tree then we cover data pre-processing topics like missing value imputation, variable transformation and Test-Train split. Part 5 - Classic ML technique - Linear Regression This section starts with simple linear regression and then covers multiple linear regression. We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don't understand it, it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures. We also look at how to quantify models accuracy, what is the meaning of F statistic, how categorical variables in the independent variables dataset are interpreted in the results and how do we finally interpret the result to find out the answer to a business problem. By the end of this course, your confidence in creating a Neural Network model in R will soar. You'll have a thorough understanding of how to use ANN to create predictive models and solve business problems. Go ahead and click the enroll button, and I'll see you in lesson 1! Cheers Start-Tech Academy ------------ Below are some popular FAQs of students who want to start their Deep learning journey- Why use R for Deep Learning? Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Deep learning in R 1. It’s a popular language for Machine Learning at top tech firms. Almost all of them hire data scientists who use R. Facebook, for example, uses R to do behavioral analysis with user post data. Google uses R to assess ad effectiveness and make economic forecasts. And by the way, it’s not just tech firms: R is in use at analysis and consulting firms, banks and other financial institutions, academic institutions and research labs, and pretty much everywhere else data needs analyzing and visualizing. 2. Learning the data science basics is arguably easier in R. R has a big advantage: it was designed specifically with data manipulation and analysis in mind. 3. Amazing packages that make your life easier. Because R was designed with statistical analysis in mind, it has a fantastic ecosystem of packages and other resources that are great for data science. 4. Robust, growing community of data scientists and statisticians. As the field of data science has exploded, R has exploded with it, becoming one of the fastest-growing languages in the world (as measured by StackOverflow). That means it’s easy to find answers to questions and community guidance as you work your way through projects in R. 5. Put another tool in your toolkit. No one language is going to be the right tool for every job. Adding R to your repertoire will make some projects easier – and of course, it’ll also make you a more flexible and marketable employee when you’re looking for jobs in data science. What is the difference between Data Mining, Machine Learning, and Deep Learning? Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions. Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Who this course is for: People pursuing a career in data science Working Professionals beginning their Neural Network journey Statisticians needing more practical experience Anyone curious to master ANN from Beginner level in short span of time Less
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[100% Off] Learn SQL for Beginners: The Comprehensive Hands-on Bootcamp Free

Learning databases and database theory can be easy... More if you have the right teacher. This university level course will give you a solid understanding of how databases work and how to use them. In the course, we will be using PostgreSQL which is one of the top two databases most demanded in industry. This course will advance your skills as a developer. This course is very practical and applicable. It focuses on teaching you skills you can use. Presented with high-quality video lectures, this course will visually show you many great things about relational databases and PostgreSQL. This course is taught by two teachers. One of your teachers is a tenured professor in California. Your other teacher is a Professional Developer. Both of these teachers will be on screen, sharing their wisdom and knowledge with you. This is just some of what you will learn in this course: Learn to succeed as a student Master database fundamentals Build a database for tracking movie rentals Understand schema, data hierarchy, and normalization Learn validation, data integrity, and ACID transactions Master using key fields and ensuring referential integrity Learn how to do SQL commands at the terminal and in code editors Solidify concepts with abundant hands on exercises which also have video solutions provided Acquire the ability to read PostgreSQL database documentation Learn how to install PostgreSQL on Windows, Linux, and Mac Master building databases, tables, and relationships between tables Master creating, reading, updating, inserting, and deleting records Gain the ability to do subqueries and aggregate functions Master using grouping, having, limit, fetch, and offset Learn how to use JSON inside SQL using PostgreSQL Master joins to query multiple sets Master filtering records in queries MASTER SQL & PostgreSQL! This is an amazing course! This course will change your life. Being skilled at using relational databases and SQL will serve you and your career well. This course will increase your proficiency, productivity, and power as a programmer. You are going to love this course and it will forever change your life. Your satisfaction is guaranteed with this course. Join us now and enroll! Who this course is for: This is a first semester university level SQL database course. This course is ideal for beginners wanting to learn databases & SQL programming. Less
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[100% OFF] The Complete Front-End Web Development Course! Free

If you would like to get started as a front-end we... Moreb developer, you are going to LOVE this course! Work on projects ranging from a simple HTML page to a complete JavaScript based Google Chrome extension. We will cover the following technologies in this course: Web development basics with HTML Cascading Style Sheets (CSS) JavaScript programming jQuery JavaScript library Bootstrap framework We will work on 3 class projects throughout this course: Simple text site - We will use what we learned in the HTML sections to create a simple text site. This project will help you learn HTML structure and the essential elements. Fallout inspired Pip-Boy - We will take what we learned in the CSS and Bootstrap sections of the course to code a Pip-Boy from the game Fallout. This project will help you learn the design elements of modern web development. Google Chrome extension - We will finish the course by programming a JavaScript based Google Chrome extension. This project will help you understand the logical parts of web development. This course covers the most popular web development frameworks, and will get you started on your path towards becoming a full-stack web developer! Still not sold? Check out a few of the awesome reviews this course has received! "Excellent Course! Highly Recommend It! Such a great hands on experience with this course." "Very nice course, covers all the stuff you need, good voice and good explanation makes it perfect for people that are new to HTML. Also there's some best practices recommendations which are useful even for advanced developers." "Excellence in giving the optimal set of tools for web development beginners seeking a well-rounded start for professional web development." Thank you for taking the time to read this, and we hope to see you in the course! Who this course is for: Anyone who would like to learn front-end web development Less
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[100% OFF] Projects in R: Learn R Creating Data Science Projects Free

R Programming Language is not an easy language to ... Morelearn, and requires extensive practice in addition to the theory. Simply understanding in theory, how R Programming language works and everything that you can do with R is just not enough – you require a complete breakdown of how to go about doing it. This is why we have designed this comprehensive project-based course! In this course, we attempt to break down this complex programming language and environment into an easy to follow structured tutorial that will help you not only understand this statistical language, but also become more familiar with how you can go about using it. R is a programming language and environment for statistical computing and graphics. It allows developers to work with a range of statistical and graphical techniques including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, etc. Our course will help you go through a step by process of understanding how R can help you become a more efficient data miner, analyst and statistician. However, it won’t just list or show you how to do that. The instructor will lead you through real world projects that will show you exactly how you can do them, while urging you to follow all the projects along with the instructor. This project based course a great way for you to understand the fundamentals using a hands-on approach. No more confusing resources or boring theories, but rather you would actually get a hands on with the R Programming Language and environment. In this course, you would learn the fundamentals of R programming language, including the basic concepts such as lists, functions, arrays, vectors, matrices, strings, etc. There are five major aspects that you will learn in this course. 1. Practical approach to the R Programming – If you already have some background in R programming, or even have the knowledge, then this will help you gain a practical approach to R programming. 2. Learn Different Forms of Data Visualization – Visualizations of data has become a popular trend, as it makes the data more prominent and easier to understand. These include different types of visualizations such as bar graph, charts, heat map, etc. 3. Learn efficient ways to visualize data – Data should be efficient, especially if you are working with partial data. If the data is not efficient, the analysis would not be faulty and can be misunderstood. 4. Learn ways to manipulate data – Data isn’t always constant and it is often used to analyze past data and make future predictions. For this data is required to be manipulated to create predictions for multiple scenarios. 5. Learn to generate reports using R – Now we come to the most important stage of data mining and analysis. Here you will learn to generate effective reports that will help you put out a clean set of data analysis for consumption. Less
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[100% OFF] GraphQL from Scratch - Realtime MERN Stack with React Node Free

Learn GraphQL from Scratch with MERN Stack (Mongo ... MoreExpress React Node) and Firebase to build Truly Realtime Web Apps. So if you are looking to Build Lightning Fast Realtime Web Apps using GraphQL with MERN Stack, don't waste your valuable time wandering around and trying to learn it from 10 different resources. I have packed everything into this course for you to fully understand all the practical GraphQL concepts... from basic to advance. Ready to go FullStack GraphQL with Node React MongoDB Firebase Authentication CRUD Realtime Subscriptions Deployment and more Join me :) Less
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[100% OFF] Image Recognition using CNN: Keras & TensorFlow in R Studio Free

You're looking for a complete Convolutional Neural... More Network (CNN) course that teaches you everything you need to create a Image Recognition model in R, right? You've found the right Convolutional Neural Networks course! After completing this course you will be able to: Identify the Image Recognition problems which can be solved using CNN Models. Create CNN models in R using Keras and Tensorflow libraries and analyze their results. Confidently practice, discuss and understand Deep Learning concepts Have a clear understanding of Advanced Image Recognition models such as LeNet, GoogleNet, VGG16 etc. How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Convolutional Neural networks course. If you are an Analyst or an ML scientist, or a student who wants to learn and apply Deep learning in Real world image recognition problems, this course will give you a solid base for that by teaching you some of the most advanced concepts of Deep Learning and their implementation in R without getting too Mathematical. Why should you choose this course? This course covers all the steps that one should take to create an image recognition model using Convolutional Neural Networks. Most courses only focus on teaching how to run the analysis but we believe that having a strong theoretical understanding of the concepts enables us to create a good model . And after running the analysis, one should be able to judge how good the model is and interpret the results to actually be able to help the business. What makes us qualified to teach you? The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Deep learning techniques and we have used our experience to include the practical aspects of data analysis in this course We are also the creators of some of the most popular online courses - with over 300,000 enrollments and thousands of 5-star reviews like these ones: This is very good, i love the fact the all explanation given can be understood by a layman - Joshua Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. Download Practice files, take Practice test, and complete Assignments With each lecture, there are class notes attached for you to follow along. You can also take practice test to check your understanding of concepts. There is a final practical assignment for you to practically implement your learning. What is covered in this course? This course teaches you all the steps of creating a Neural network based model i.e. a Deep Learning model, to solve business problems. Below are the course contents of this course on ANN: Part 1 (Section 2)- Setting up R and R Studio with R crash course This part gets you started with R. This section will help you set up the R and R studio on your system and it'll teach you how to perform some basic operations in R. Part 2 (Section 3-6) - ANN Theoretical Concepts This part will give you a solid understanding of concepts involved in Neural Networks. In this section you will learn about the single cells or Perceptrons and how Perceptrons are stacked to create a network architecture. Once architecture is set, we understand the Gradient descent algorithm to find the minima of a function and learn how this is used to optimize our network model. Part 3 (Section 7-11) - Creating ANN model in R In this part you will learn how to create ANN models in R. We will start this section by creating an ANN model using Sequential API to solve a classification problem. We learn how to define network architecture, configure the model and train the model. Then we evaluate the performance of our trained model and use it to predict on new data. Lastly we learn how to save and restore models. We also understand the importance of libraries such as Keras and TensorFlow in this part. Part 4 (Section 12) - CNN Theoretical Concepts In this part you will learn about convolutional and pooling layers which are the building blocks of CNN models. In this section, we will start with the basic theory of convolutional layer, stride, filters and feature maps. We also explain how gray-scale images are different from colored images. Lastly we discuss pooling layer which bring computational efficiency in our model. Part 5 (Section 13-14) - Creating CNN model in R In this part you will learn how to create CNN models in R. We will take the same problem of recognizing fashion objects and apply CNN model to it. We will compare the performance of our CNN model with our ANN model and notice that the accuracy increases by 9-10% when we use CNN. However, this is not the end of it. We can further improve accuracy by using certain techniques which we explore in the next part. Part 6 (Section 15-18) - End-to-End Image Recognition project in R In this section we build a complete image recognition project on colored images. We take a Kaggle image recognition competition and build CNN model to solve it. With a simple model we achieve nearly 70% accuracy on test set. Then we learn concepts like Data Augmentation and Transfer Learning which help us improve accuracy level from 70% to nearly 97% (as good as the winners of that competition). By the end of this course, your confidence in creating a Convolutional Neural Network model in R will soar. You'll have a thorough understanding of how to use CNN to create predictive models and solve image recognition problems. Go ahead and click the enroll button, and I'll see you in lesson 1! Cheers Start-Tech Academy ------------ Below are some popular FAQs of students who want to start their Deep learning journey- Why use R for Deep Learning? Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Deep learning in R 1. It’s a popular language for Machine Learning at top tech firms. Almost all of them hire data scientists who use R. Facebook, for example, uses R to do behavioral analysis with user post data. Google uses R to assess ad effectiveness and make economic forecasts. And by the way, it’s not just tech firms: R is in use at analysis and consulting firms, banks and other financial institutions, academic institutions and research labs, and pretty much everywhere else data needs analyzing and visualizing. 2. Learning the data science basics is arguably easier in R. R has a big advantage: it was designed specifically with data manipulation and analysis in mind. 3. Amazing packages that make your life easier. Because R was designed with statistical analysis in mind, it has a fantastic ecosystem of packages and other resources that are great for data science. 4. Robust, growing community of data scientists and statisticians. As the field of data science has exploded, R has exploded with it, becoming one of the fastest-growing languages in the world (as measured by StackOverflow). That means it’s easy to find answers to questions and community guidance as you work your way through projects in R. 5. Put another tool in your toolkit. No one language is going to be the right tool for every job. Adding R to your repertoire will make some projects easier – and of course, it’ll also make you a more flexible and marketable employee when you’re looking for jobs in data science. What is the difference between Data Mining, Machine Learning, and Deep Learning? Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions. Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning. Who this course is for: People pursuing a career in data science Working Professionals beginning their Deep Learning journey Anyone curious to master image recognition from Beginner level in short span of time Less
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