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[100% OFF] The Complete Typescript for Beginners From Zero To Hero 2020 Free

Every other course online teaches you the basic syntax and features of Typescript, but only this course will show you how to apply Typescript on real projects, instructing you how to build large, successful projects through example. Typescript is a 'super-set' of Javascript. That means that if you already know Javascript, you are ready to take this course. Typescript adds in several important features to Javascript, including a type system. This type system is designed to help you catch errors during development, rather than when you are running your code. That means you'll be twice as productive by catching bugs earlier in development. But besides the type system, Typescript also provides several tools for structuring large codebases and writing truly reusable code. ES6 is the 6th edition, officially known as ECMAScript 2015, and was finalised in June 2015. ES6 adds significant new syntax for writing complex applications, including classes and modules, but defines them semantically in the same terms as ECMAScript 5 strict mode. Browser support for ES6 is still incomplete. However, ES6 code can be transpiled into ES5 code, which has more consistent support across browsers. Typescript is a superset of Javascript that compiles to plain Javascript. It is also the main language used for Angular 2. ES6 | ES2015 | Typescript | ES6 Tutorial | ES2015 Tutorial | Typescript Tutorial | ES6 Tutorial for Beginners | ES2015 Tutorial for Beginners | Typescript tutorial for Beginners

[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 :) 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] 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] Mastering CSS Grid 2020 - With 3 cool projects Free

CSS Grid is a relatively new and unused concept to... More CSS. It's very important these days that our layouts are simple to maintain, and easy to adjust based on the dimensions of our device. CSS grid simplifies this process over other existing strategies. In this course we take you deep into how to build a variety of different layouts in CSS Grid. We cover the following:- All the properties in CSS Grid, how they work, and any gotchas that you may not be aware of when using them. Alignment and how it works in CSS Grid, including the alignment of tracks and grid items at the grid container level. We also show you how to override alignment at the grid item level. The basics of responsive web design, such as media queries and how they work with mobile / tablet etc. Grid areas and how it helps simplify responsive web design The concept of implicit and explicit grids and what the differences are A deep look into the Autoplacement algorithm Animation at a high level and what works currently with CSS Grid How to convert some layouts in Flexbox to use CSS Grid instead When to use Flexbox over CSS Grid Once we cover all of these concepts, we then go about showing you some basic layout problems and how they can be solved. This includes:- Column based layout Basic Sidebar layout Vertical Text alignment Modal alignment Stick footer layout Formatting form fields And hopefully in future much more. We then look at some advance layout topics such as:- The Holygrail layout The Media Objects layout A Viewport Friendly Image Gallery A Responsive Image Gallery An Animated Sidebar A Monthly Calendar layout A Newspaper Cover layout A Responsive Twitter Clone Layout A Responsive Movie Gallery Then if you haven't had enough, we have 3 real life application examples that will give you the experience you need. They are:- A Chat UI interface An Uber Eats Clone Responsive Application A YouTube Clone Responsive Application Who this course is for: Web Developers Web Designers User Experience Designers Front End Developers Full Stack Developers 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] Learn Complete Python-3 GUI using Tkinter Free

Through this Course master in Python Tkinter &... More Create real world projects! Less
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[100% OFF] Data Visualization in Excel: All Excel Charts and Graphs Free

What are the chart types I will learn in this cour... Morese? Excel offers the following major chart types. All of these are covered in this course Column Chart Line Chart Pie Chart Doughnut Chart Bar Chart Area Chart XY (Scatter) Chart Bubble Chart Stock Chart Surface Chart Radar Chart Combo Chart Pivot Chart Sparklines And many other creative ones :) How are charts useful in Excel? A chart is a tool you can use in Excel to communicate data graphically. Charts allow your audience to see the meaning behind the numbers, and they make showing comparisons and trends much easier. What are the benefits of using charts in Excel? Excel charts allow spreadsheet administrators to create visualizations of data sets. By highlighting a set of data within an Excel spreadsheet and feeding it into the charting tool, users can easily create various types of charts in which the data is displayed in a graphical way. This course will answer all the questions that would pop up while you set to visualize your data using Excel charts such as: How do you make Excel charts look better? How do you format a chart in Excel? What are the different elements of charts? How do I make those awesome infographics that I see in fancy magazines and TV reports? How do I create a comparison chart in Excel? What is the best chart to use for comparison? And many more... How is this course different from other resources available online? Most courses cover only teach how to draw different types of charts in Excel. The main point is missed. The main point of creating a chart is that you want to convey a message or tell a story using the chart. In this course, once you have learnt all the charting tools, you will also learn how you should create a chart. How you can highlight your message and avoid clutter in the chart, so that when your audience looks at the chart, the message is clearly conveyed to them. Who this course is for: Anyone curious to master charts in excel from beginner to advanced in short span of time 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] 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] Java Parallel Computation on Hadoop Free

Build your essential knowledge with this hands-on,... More introductory course on the Java parallel computation using the popular Hadoop framework: - Getting Started with Hadoop - HDFS working mechanism - MapReduce working mecahnism - An anatomy of the Hadoop cluster - Hadoop VM in pseudo-distributed mode - Hadoop VM in distributed mode - Elaborated examples in using MapReduce Learn the Widely-Used Hadoop Framework Apache Hadoop is an open-source software framework for storage and large-scale processing of data-sets on clusters of commodity hardware. Hadoop is an Apache top-level project being built and used by a global community of contributors and users. It is licensed under the Apache License 2.0. All the modules in Hadoop are designed with a fundamental assumption that hardware failures (of individual machines, or racks of machines) are common and thus should be automatically handled in software by the framework. Apache Hadoop's MapReduce and HDFS components originally derived respectively from Google's MapReduce and Google File System (GFS) papers. Who are using Hadoop for data-driven applications? You will be surprised to know that many companies have adopted to use Hadoop already. Companies like Alibaba, Ebay, Facebook, LinkedIn, Yahoo! is using this proven technology to harvest its data, discover insights and empower their different applications! Contents and Overview As a software developer, you might have encountered the situation that your program takes too much time to run against large amount of data. If you are looking for a way to scale out your data processing, this is the course designed for you. This course is designed to build your knowledge and use of Hadoop framework through modules covering the following: - Background about parallel computation - Limitations of parallel computation before Hadoop - Problems solved by Hadoop - Core projects under Hadoop - HDFS and MapReduce - How HDFS works - How MapReduce works - How a cluster works - How to leverage the VM for Hadoop learning and testing - How the starter program works - How the data sorting works - How the pattern searching - How the word co-occurrence - How the inverted index works - How the data aggregation works - All the examples are blended with full source code and elaborations Come and join us! With this structured course, you can learn this prevalent technology in handling Big Data. Who this course is for: IT Practitioners Software Developers Software Architects Programmers Data Analysts Data Scientists Less
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[100% OFF] Oracle SQL : Practical Examples : Go from Beginner to Master Free

***SQL course which gained immediate popularity wi... Moreth the launch on UDEMY*** ============================================================================ ***Continuously being updated with new topics/videos every week*** ***Added lecture SQL vs NOSQL*** > 19 Dec 2019 (under Interview Section) ***Added Interview Section*** > 15 Dec 2019 *** Added lecture Most Important SQL Queries*** > 15 Dec 2019 ***Added lecture What is VIEW?*** > 15 Dec 2019 ============================================================================= You need to learn the most important and powerful language of the database world - SQL which makes your programming skills complete and enriched in just less than 20 hours of study! If you have already wasted your time and money in hunting for a complete yet concise course in SQL through random youtube videos or offered by inexperienced people - then you are at the right place here. This course brings step-by-step lessons in its logical series of videos to help you master the art and science of SQL. Moreover there is not even a basic knowledge of programming envisaged while designing this course. This course has been brought by an highly experienced faculty who have had 20+ years of experience in working as Oracle developer and DBA out of which 6 years onside in USA and UK. The faculty has been working in Oracle field ranging from Oracle version 6 to the latest 19C. This course is for everybody who likes to make career in database programming, front end programming, ERP, or in general succeed as an IT professional, management people and undergraduate students of any stream. This course is covered on Oracle's LiveSQL platform available on web hence does not require any local installation of Oracle, yet the students can practice on latest version, the current is Oracle 19C. Being on web, students can learn, take notes or do practice sitting anywhere as Oracle LiveSQL is accessible on all the devices - PC, Laptops or even Mobiles. Who this course is for: Students interested in database back end programming Programmers in any other front end language like Java or PHP or Python etc, must learn SQL Engineering students, Computer Science students, Science / Commerce students - All pursuing UG or PG or completed with degree Management people who are required to draw ad-hoc data as per requirement 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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58 used

[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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139 used

[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] 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] The Complete PHP 7 Guide for Web Developers Free

PHP levels up! The world’s favorite back-end pro... Moregramming language now gets a new version packed with new features and significant upgrades. PHP is touted as the de facto language for server-side scripting in app development and even websites. The popularity of the language has also made it extremely useful as a general-purpose programming language. The latest version gets a huge boost in terms of performance, speed, new scalar type declarations and even a new operator. The performance and speed boost comes from the new turbocharged Zend Engine 3, which also allows PHP7 to consume half as much as memory as PHP5 and support more component users at the same time. In addition the new engine, other changes to PHP7 include replacing fatal- or recoverable-level legacy PHP error mechanisms with object-oriented exceptions, inclusion of left-hand-side expressions, unmaintained or deprecated server application programming interfaces (SAPIs) were removed, list() operator now includes support for strings, new language features such as return type declarations for functions, and support for the scalar types in return type and parameter declarations. With so much power under the hood, it is no wonder a lot of developers are shifting to PHP7. With this course, you too can learn how to supercharge your apps and websites. Our complete PHP 7 guide is the perfect course to get you started with the amazing features included into the already powerful programming language. It comes loaded with everything you need to know to upgrade to the fancy new iteration. The course will cover not only the fundamentals of PHP 5, but will also familiarize you with the new features and changes in PHP 7. These new additions may not seem like much, but they will improve your coding by four fold, especially ones such as unserialise function (which will accept another optional parameter) and password hash function (that now automatically generates a secure salt, rather than accept a given salt). The PHP 7 tutorial also includes breaking down features such as the new spaceship operator, Throwable Interface, Handling Fatal Errors, Generator Delegation, Anonymous Classes, Fetching Data & Error Handling and so much more. That’s not all. Some sections even includes quizzes to help you test your understanding and a project that will allow you to become comfortable coding in PHP 7. In this course, you will learn: Introduction to PHP, its fundamentals and its environment What is new in PHP 7 and how it differs from PHP 5 New features such as spaceship operators, error handling, new declarations, new classes, new functions, etc. Fully design a GoodQuotes app project that will allow you to add, edit and remove data Less
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[100% OFF] Learn Next.js Free

SO, YOU’RE LOOKING FOR A COURSE THAT WILL TEACH ... MoreYOU NEXT.JS QUICKLY & IN A FUN MANNER? I’ve got just the course for you! Welcome, my name is Josh Werner with Learn Tech Plus and I’ve put this course together to help people just like you quickly master Next.js...Whether you’re a beginner or experienced with Next.js! If your goal is to become a master of Next.js, then this course is perfect for you. It will get you started on the right path and give you the knowledge and skills you need to master Next.js... Learning Next.js is Not only for Experienced users, but also everyone else. Because when you have mastered Next.js, you can get around Next.js quickly and increase your productivity! In short, a good understanding of Next.js is tremendously beneficial. Now, in this course, we'll go far beyond that. By the end of it, you'll have gained complete proficiency in Next.js even if you're currently a complete beginner! THAT’S RIGHT...NO PRIOR EXPERIENCE OR KNOWLEDGE IS REQUIRED! You don’t need any previous experience or knowledge to take this course. In fact, all you need is a desire to learn and master Next.js. This is not one of those courses that will throw too much at you at once and cause you to get overwhelmed. This is a course that you’ll not only learn so much from, but also enjoy the journey as you’re learning (which is a very important part of the learning process) The course will take you by the hand and teach you everything you need to know step by step and even put your knowledge to practice immediately by showing you how to setup an account with Next.js and How to use Next.js. On top of this, you will also get my continuous support as well to make sure you’re successful with my course. LEARN NEXT.JS BY DOING! (LEARN NEXT.JS FROM SCRATCH!) We will go step by step and cover Next.js. The goal here is to help you A) Setup a Free Account with Next.js B) Work with Next.js Here’s what we’ll cover in the course: 1. We’ll start from the very beginning and explain what Next.js is, why & how it’s used. 2. Introduce you to Next.js Less
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[100% OFF] Complete Machine Learning with R Studio - ML for 2020 Free

You're looking for a complete Machine Learning cou... Morerse that can help you launch a flourishing career in the field of Data Science & Machine Learning, right? You've found the right Machine Learning course! After completing this course you will be able to: · Confidently build predictive Machine Learning models to solve business problems and create business strategy · Answer Machine Learning related interview questions · Participate and perform in online Data Analytics competitions such as Kaggle competitions Check out the table of contents below to see what all Machine Learning models you are going to learn. How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics 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 the most popular techniques of machine learning. Why should you choose this course? This course covers all the steps that one should take while solving a business problem through linear regression. 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. Below is a list of popular FAQs of students who want to start their Machine learning journey- What is Machine Learning? Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. What are the steps I should follow to be able to build a Machine Learning model? You can divide your learning process into 3 parts: Statistics and Probability - Implementing Machine learning techniques require basic knowledge of Statistics and probability concepts. Second section of the course covers this part. Understanding of Machine learning - Fourth section helps you understand the terms and concepts associated with Machine learning and gives you the steps to be followed to build a machine learning model Programming Experience - A significant part of machine learning is programming. Python and R clearly stand out to be the leaders in the recent days. Third section will help you set up the Python environment and teach you some basic operations. In later sections there is a video on how to implement each concept taught in theory lecture in Python Understanding of models - Fifth and sixth section cover Classification models and with each theory lecture comes a corresponding practical lecture where we actually run each query with you. Why use R for Machine Learning? Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Machine 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 Data journey Statisticians needing more practical experience 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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