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[100% OFF] React Native and Redux Course using hooks

Take your react js skills to next level by building Native Android and IOS Apps using React Native
100% success rate

[100% OFF] Home Business Basic Sales & Marketing Tools

Learn About Some Of The Basic Sales & Marketin... Moreg Tools For A Home Business Less
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[100% OFF] MERN Stack Master Course - Building your own Instagram Free

MERN stands for MongoDB, Express.js, React.js and ... MoreNode.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 Less
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[100% OFF] The IOS Development MasterClass: Learn The Skills To Master Swift And Xcode Free

This course is a skills based journey into app dev... Moreelopment. Throughout this course students will learn the skills necessary to build apps for iOS using Xcode and the Swift Programming Language Less
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[100% OFF] Linux Shell Scripting: Bashing, Automating Commands, Updated Free

Welcome to this Comprehensive Linux Shell Scriptin... Moreg Laser Targeted Course "Updated”. In short, this is the one stop shop for everything you need to become a Master in Shell Scripting. With 70+ Long, but Laser Targeted Videos, over 21 packed hours, we will leave no stone unturned. Are you ready to start your path to becoming a Master in Shell Scripting and learn one of employer's most demanded skills for 2020 and beyond? This is by far the most comprehensive, yet condensed and straight-forward, course bundle for Linux Shell Scripting on Udemy! Whether you have never had any knowledge on Shell Scripting before, already know some basic skills, or want to learn about the advanced features of Shell Scripting, this is the course you are looking for! Don’t miss this Limited Time Offer. ACT NOW! You will Learn by Practice: By the end of this Unique Course, you will go from #Newbie to #Advanced as a #Shell_Scripting_Expert. Here is what you’ll learn: Chapter 01 - Introduction 0101 - About this Course 0102 - Course Structure 0103 - What is the UNIX Shell 0104 - Which Shell 0105 - What is a Shell Script Chapter 02 - Your First Shell Script 0201 - A Basic Script 0202 - The echo Command 0203 - The read Command 0204 - Shell Basics Revisited 0205 - Special Characters 0206 - Comments 0207 - Chapter Exercises 0208 - Exercise Solutions Chapter 03 - Running a Shell Script 0301 - Running a Script on the Command-line 0302 - Running a Script from within vi 0303 - Your PATH and bin 0304 - Script Interpreters 0305 - CGI Scripts Chapter 04 - Shell Programming Features 0401 - Shell Variables 0402 - Environment Variables 0403 - The Trouble with Quotes 1 0404 - The Trouble with Quotes 2 0405 - Grouping Commands 0406 - Line Control 0407 - Chapter Exercises 0408 - Exercise Solutions 0409 - Introducing the Course Project 0410 - Course Project Solution Chapter 05 - Conditional Code 0501 - True and False 0502 - Conditional Command Execution 0503 - The if Statement 0504 - The else Clause 0505 - The elif Clause 0506 - Using test 1 0507 - Using test 2 0508 - Using test 3 0509 - The case Statement 0510 - Chapter Exercises 0511 - Exercise Solutions Chapter 06 – Loops 0601 - The while Loop 0602 - break and continue 0603 - Numerical Calculations 0604 - The for Loop 0605 - Chapter Exercises 0606 - Exercise Solutions Chapter 07 - Text Processing 0701 - About Filters 0702 – grep 0703 - Regular Expressions 0704 – sort 0705 – sed 0706 - awk 1 0707 - awk 2 0708 - Chapter Exercises 0709 - Exercise Solutions Chapter 08 – Functions 0801 - Program Structure 0802 - Defining and Calling a Function 0803 - Function Parameters 0804 - Function Return Values 0805 - Functions in Other Files 0806 - Case Study- The yesno Function 0807 - Chapter Exercises 0808 - Exercise Solutions Chapter 09 - Command-line Parameters 0901 - Using Command-line Parameters 0902 - Using shift 0903 - Using set - - Command 0904 - Using IFS 0905 - Usage Messages 0906 - Chapter Exercises 0907 - Exercise Solutions Chapter 10 - Advanced Scripting 1001 – Debugging 1002 - Default Values for Variables 1003 - Temporary Files 1004 - Preventing Abnormal Termination 1005 - Chapter Exercises 1006 - Exercise Solutions 1007 - The End Chapter 11 - Additional Content Part 1: Exercises and More 1101 – Please download the attached Exercises Files 1102 – Learn EMACS 1103 – Learn VI and Vim 1104 – Very Valuable Documentation Additional Content Part 2: Grand Finale Bonus Lectures. Enjoy the Benefits You could also end up using these skills in your work for Your #Clients, and much more. You'll Also Get: ✔ Lifetime Access to course updates ✔ Udemy Certificate of Completion Ready for Download ✔ A responsive instructor in the Q&A Section ✔ This courses’ bundle comes with a 30 day money back guarantee! If you are not satisfied in any way, you'll get your money back. So wait no more! Learn Linux Shell Scripting, increase your knowledge, become a Shell Scripting Expert and advance your career all in a fun and practical way! I really hope you found this course valuable, but either way, please leave a review and share your experience... Less
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[100% OFF] JavaScript + ES6 + ES7 + ES8 + ES9 -> The Complete Guide Free

Welcome to my new course: 'JavaScript + ES6 + ES7 ... More+ ES8 + ES9 -> The Complete Guide'. This course starts from scratch, you neither need to know any pre-requisite programming knowledge nor any language expertise. From the environment Setup to Development, this course covers almost each and every concept required to become an expert JavaScript developer. Having a deep-dive of the concepts in this course, you'll learn all about: JavaScript: Development Environment Setup Fundamentals Operators Control Flow Arrays Functions Objects Prototypes Patterns To Create Objects Error Handling Miscellaneous Objects Debugging in Chrome Shopping Cart Project: Putting All Together ES6: Features with their Syntax Modules Class Symbols Iterators & Generators Promises Maps & Sets Extensions of Built-in Objects Reflect API Proxy API ES7: New Features ES8: New Features ES9: New Features World Weather Project: Putting All Together Course Roundup and many more... This course will assist: In becoming an proficient 'JavaScript Developer' and Inclining towards the learning/ understanding of any client/ server side programming language. Why JavaScript? JavaScript (JS) is a lightweight, interpreted or JIT compiled programming language with first-class functions. Most well-known as the scripting language for Web pages, many non-browser environments also use it, such as Node.js and Apache CouchDB. JS is a prototype-based, multi-paradigm, dynamic scripting language, supporting object-oriented, imperative, and declarative (e.g. functional programming) styles. The standard for JavaScript is ECMAScript. As of 2012, all modern browsers fully support ECMAScript 5.1. Older browsers support at least ECMAScript 3. On June 17, 2015, ECMA International published the 6th major version of ECMAScript, ECMAScript 2015. Since then, ECMAScript standards are on yearly release cycles. This course covers up to the latest version of JavaScript, which is currently ECMAScript 2019. Why we should learn JavaScript & the reasons are: Open Source Language: Freely Available. Much more than Scripting programming language. Scalability and Performance Features. Evolving steadily & ES6 represents the BEST !!! Much JavaScript-related innovation in the Market. Base of most of the frameworks like Angular. Supported by a broad coalition of companies. Who this course is for: Be a JS Ninja by understanding the most popular programming language in the world viz. JavaScript. Newcomer as well as experienced having the experience with JavaScript (ES5/ ES6) and know the basics of the language. Understanding the new Features and Additions, brought by ES6 (including ES5) to JavaScript. Understand the basics to move head with the popular libraries/frameworks like jQuery, React, Angular or NodeJS. Understand how JavaScript actually works internally. 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] 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] Complete Python Bootcamp for Data Science& Machine Learning Free

This comprehensive course will be your guide to le... Morearning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! 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 beginners with some 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! Enroll in the course and become a data scientist today! Less
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[100% OFF] Web Development Masterclass - Complete Certificate Course Free

This course offers a comprehensive look into the e... Morentire web development process - from local server configuration using WAMP and MAMP (Apache, MySQL, PHP) to production deployment using the latest web technologies including: LAMP Stack (Linux, Apache, PHP and MySQL) for Ubuntu, HTML5, CSS, Bootstrap, JavaScript, jQuery, XML, and AJAX. The content is ideal for those interested in working as a web developer, launching a web application, or devoted enthusiasts. The concepts explored in this course are suitable for individuals of all skill levels. Each module starts with the fundamental concepts and gradually transitions into more advanced material. What makes this course unique? This course is specifically intended to teach students to develop web applications using the most efficient methods and the latest web technologies. Through live demonstrations we teach the importance of using scalable cloud hosting infrastructures during the development process. This includes small informational websites of only a few pages to advanced 'big data' style, dynamic web applications. We go through several live examples of web development and Linux based server configurations on popular Cloud hosting providers such as Linode. Section 1 & 2 (Introduction, How the Internet Works) The course begins with with an overview of learning objectives. We then explore how the internet works, including the composition and transmission of data packets over both local and wide-area Networks. Next we take a look at the HTTP and HTTPS protocols as applicable to client and server side communications - including DNS Lookups. This section will also teach students how email exchange works over SMTP and IMAP. The role of Network Ports and Firewalls are also introduced. Section 3, 4: (The Web Development Process, Planning a Website) Students will gain an understanding of all the steps involved in the web development process. Section 5: Web Hosting and System Requirements We conduct an in-depth case analysis of web hosting solutions including: Shared, Virtual Private, Dedicated and Cloud Hosting. We provide an overview of various packages offered by different web hosting companies and weigh the pros and cons of each one. Students are also introduced to the importance of web server scalability and the advantages of cloud hosting over traditional hosting services. We also examine the infrastructure requirements of popular, resource intensive applications such as Netflix and Facebook to emphasize the importance of avoiding costly mistakes in the initial stages of development. Section 6: Domain Names We provide an overview of the domain name registration process. This includes the role of registrars and TLD (Top Level Domain) administration by ICANN. ccTLD's (Country Code Top Level Domains) are also explored. Students gain hands-on experience with the registration process using popular domain registrars. We provide a comparison of different registrars and register a sample domain name using GoDaddy. Other topics of discussion include: domain name privacy and administration, auto-renewal, domain forwarding, and name server assignment. Section 7: Testing Environment Students are introduced to configuring a local testing server on a PC or MAC system using WAMP (Windows) or MAMP (MAC). The lessons provide a detailed guide on installation of the packages and an overview of the interface. Section 8: Production Environment Students acquire the skills needed to optimally configure a live production environment for securely hosting web applications on a cloud server (Linode). The section starts with an overview of different cloud hosting providers such as Amazon Web Services, Microsoft Azure, Linode and Digital Ocean. We then provide a live demonstration of server setup using Linode. This includes deployment of Ubuntu and installation of LAMP Stack (Linux) on the Linode Server using remote access consoles such as Terminal (MAC) and PuTTY for Windows. Students gain an in-depth knowledge of server maintenance, file and directory commands. We also explore SSH Authentication for multiple users and file permissions to reduce security vulnerabilities. Remote Desktop connections for server administration are taught, using Tight VNC (Windows) and RealVNC (MAC). A thorough overview of the Linode server management console is conducted, to show students how to scale servers, change root passwords, manage the DNS Zone file and create back-ups. Section 9: FTP Setup Students learn the role of an FTP (File Transfer Protocol) client to connect to a remote server, through a local machine. We provide a live demonstration on file upload using FileZilla and explore the FileZilla Interface for connection management. Section 10: HTML Development This section explores HTML. HTML is a key fundamental building block when learning to develop websites. Students initially learn the basics of HTML page structure and gradually transition into working with spacing, text formatting, lists, images, videos, links, anchors, tables, forms and much more. We include several projects, where students are shown first-hand, how to develop and code html web pages from scratch. Section 11: CSS Development Students learn to use CSS to create stylish, responsive web page layouts. We start by discussing the parts and types of CSS rules, followed by CSS classes, DIVS, and ID's. Students gain significant exposure to various formatting options, including margins, padding, font properties, backgrounds, transparency, positioning, link styling and CSS tables. This section includes a hands-on web development project where students utilize the concepts explored in the lesson. Section 12: Document Object Model (DOM) As a precursor to JavaScript, we explore the DOM (Document Object Model). We explain its usage and application in manipulating HTML and CSS elements. Section 13: JavaScript Development We introduce students to JavaScript coding to add interactivity to static HTML and CSS pages. The section starts with discussing JavaScript placement, using both internal and external scripts. We then take a look at JavaScript output, variable declarations, arithmetic operators, objects, strings, math functions, arrays, conditional statements, loops, functions and events. Students also go through two hands-on projects that will further solidify their knowledge of the concepts explored in the lessons. Section 14: JQuery Library We explore the jQuery library and many of its unique features, used to create stunning, animated web pages. We start with the basics, from embedding jQuery into web pages to working with Selectors. Students then explore working with events, toggling, fading, sliding, and other forms of animation. The lessons also teach students how to work with callbacks, chaining, dragables, accordion menus and many other functions. Section 15: Bootstrap Framework Students are taught to use the Bootstrap framework for responsive, mobile-first - front-end development. As one of the leading open-source development libraries, Bootstrap is an essential part of the developers coding arsenal. The section begins with teaching students how to include essential Bootstrap files into web pages. It then explores the Bootstrap Grid system and popular layout strategies for optimal cross-device and cross-browser compatibility. Students gain exposure to just about every Bootstrap component, from typography, tables and images, to jumbotrons, wells, alerts, buttons, glyphicons and progress bars. The section includes several hands-on exercises that will walk students through the process of creating stunning layouts, complete with modals, carousels, popovers, drop-down menus, forms and much more. Section 16: PHP Development Students gain exposure to creating dynamic web applications and functionality using PHP. We start with the basics, including variable declaration and data output. The lessons then transition into working with objects, conditional statements, loops, functions, arrays and form validation. Section 17: MySQL Database Integration Students learn to unleash the true power of web application development with MySQL database integration. We start with the basics from database and table creation, to user management. Next we explore the execution of commonly used SQL statements for database modification and administration. Students are also taught how to create database connections and execute SQL statements from PHP scripts. Section 18, 19 (XML, AJAX, & Development) We explore XML and AJAX integration to create dynamic content, without page refresh. The lessons cover several hands-on training exercises that will encompass many of the exciting functions AJAX offers. Students will build a website complete with database integration, registration forms with server-side validation, user authentication, and a SMTP-based contact submit form. Section 20: Google Apps for Work Students learn to create a customized business email address using Google Apps for Work. Email administration is also explored, along with alias creation. Less
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[100% OFF] Learn Modern Javascript by Coding a Snake Game Free

Ever wanted to learn Javascript, Node.js & Exp... Moreress.js but found traditional courses a little boring & long? Jump straight in by coding a snake game and learn the fun way! You will get experience using: Javascript ES6 Classes Arrays Functions Objects Phaser 3 Node.js Express.js Phaser 3 Snake is a nice, simple game that includes many fundamental elements that you will find in many games. It is the ideal first game to code. The game includes: Movement Input handling Power ups Randomisation Collision detection Game over handling I hope you enjoy the course! Who this course is for: Beginner Javascript students interested in game development Less
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[100% OFF] The Complete Full-Stack JavaScript Course! Free

If you would like to master JavaScript and get sta... Morerted as a full-stack web developer, you are going to LOVE this course! Learn full-stack JavaScript development working on coding projects using ReactJS, NodeJS, LoopbackJS, Redux, Material-UI and socket programming. We will work on the following 3 coding projects in this course: Calculator Application - We will go over the basics of what React is, how to create components and how to work within the React life-cycle. Weblog - We will build a feature rich blog app using React and LoopbackJS. We will begin to explore the full-stack elements of JavaScript by coding our own REST API, and how the front and back-end can communicate with each other. Chat Application - We will explore socket programming. With a web socket you can keep clients connected on the server side. We will program a chat app where you can create a user account, add other users and then message back and forth with them. This course was designed for students who have a basic understanding of front-end web development. It will be helpful if you know how to use HTML and CSS. A basic understanding of JavaScript is not required, but it will help you get up to speed with the tutorials. All of the lectures are downloadable for offline viewing. English captions are available within the course. Thank you for taking the time to read this and we hope to see you in the course! Less
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[100% OFF] Learn Python Web Development With Flask Zero To Hero Free

Flask is a micro web framework written in Python. ... MoreIt is micro framework because it does not require dozens of tools and library. you can customize flask as you want with the help of flask and get creative with it. What will you learn? You will Learn about Back End Web Developed Flask Models Sqlalchemy Sqllite Python Advanced Databases Flask Login Login System Full CRUD functioning db Why Flask? Flask Make it easy to use and good for python beginners. it is best if you want to make project light weight Why this Course we will be making 2 different projects and 1 to work as assignment to do list app full blogging web app with login Project: Library Management System Who this course is for: Web Developers Beginners curious for python Beginners curious for python web development Beginners curious for python flask Beginners curious for python web frameworks 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] Data Science: Supervised Machine Learning Bootcamp in Python Free

This course focuses on one of the main branches of... More Machine Learning that is Supervised Learning in Python. If you are not familiar with Python, there is nothing to worry about because the Lectures comprising the Python Libraries will train you enough and will make you comfortable with the programming language. The course is divided into two sections, in the first section, you will be having lectures about Python and the fundamental libraries like Numpy, Pandas, Seaborn, Scikit-Learn and Tensorflow that are necessary for one to be familiar with before putting his hands-on Supervised Machine Learning. Then is the Supervised Learning part, which basically comprises three main chapters Regression, Classification, and Deep Learning, each chapter is thoroughly explained, both theoretically and experimentally. During all of these lectures, we’ll be learning how to use the different machine learning algorithms to create some mind-blowing modules of Machine Learning, and at the end of the course, you’ll be trained enough that you would be able to develop you own Recognitions Systems and Prediction Models and many more. Let's get started! Who this course is for: Those who are interested in AI and Machine Learning Those who have basic knowledge of any programming language Those who want to be create awesome Machine Learning and AI modules And those who want to earn some handsome amount of money from Machine Learning Field in Future Less
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162 used

[100% OFF] Logo Design - Design a Logo in Photoshop for beginners Free

Do you want to learn how to create your very first... More logo? In this course you'll find the key elements that will make you a designer ready for the market. With step-by-step lessons guiding you through this wonderful journey, you'll learn the fundamentals of logo design, why it's so important to write down your ideas and needs and the most important part: You'll have fun doing what is one of the most important parts of a brand image: A logo! We'll sketch in paper our ideas, then we'll take them into the digital canvas and create our very first logo! Who this course is for: Anybody who wants to design a logo for its own or a client Less
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84 used

[100% OFF] Core Java Interview Bootcamp To Handle Interviews With Confidence. Free

Hi everyone :) Having you stop here simply mean... Mores you are either preparing for a core java interview or want to know the most widely asked questions in the room. This course is intended for you folks, perfectly. The course basically aims at providing an in-depth explanation to most continuously asked questions through very engaging animated PPTs. Whether it's string, or exceptions, or multi-threading, I have got your back on most asked questions from these topics. The much important thing is the clear and concise clarity in explanations that you will get from this course. Note: 1. The course is not intended for complete beginners! You need to have at least basic to intermediate knowledge of core java. 2. I will keep on adding brand new most asked questions regularly. So, this course is not just limited to a fixed number of questions! Rest assured, you will enjoy this awesome Bootcamp with me. See you in the course... Over n Out :) Less
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124 used

[100% OFF] Agile Project Management 200+ Tools with Kanban Scrum Devops

Learn 200+ Tools of Agile + Scrum + Kanban + Lean ... More& more. Only Agile Course that includes DevOps & iCAN Certification Less
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115 used, 100% success rate

[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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58 used

[100% OFF] Digital Marketing (SEO, Google Ads, Google Analytics etc) Free

Although this course is for beginners, the knowled... Morege it provides is really advanced. It is full of tips and tricks as well as tested methods that will make you an expert in digital marketing and online advertising. Its curiculim includes: Blogging Social Media Google Ads SEO Google Analytics E-commerce Optimization Conversion Optimization Each section of the course is a step by step guide that not only gives you usefull instructions about the topic it addresses but also tried methods that you can easily use to bring profits to your business and to be a successful digital marketing professional. Less
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127 used

[100% OFF] Develop and Publish a Google Chrome Extension! Free

Hello and welcome to our course on how to develop ... Moreand publish a Google Chrome Extension! This web development course was designed for all levels of programmers, and will provide you with practical JavaScript programming experience. In this course we will build two Chrome extensions and cover the following topics: Introduction and Manifest Content Scripts Messaging Different Parts of the Extension Creating Share Popup Icons Building an Image Downloader Interacting with the DOM Uploading to the Google Chrome Web Store Project source code is available on GitHub. All of the videos in this course are downloadable for offline viewing. English subtitles/captions are available within the course. Thank you for taking the time to read this and we hope to see you in the course! Who this course is for: Web developers interested in publishing a Google Chrome Extension. New JavaScript programmers looking for practical projects. Less
Expired
86 used