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[100% OFF] The Self-Taught Programmer

The Definitive Guide to Programming Professionally

[100% OFF] Python for Beginners - Learn Python Programming in Hindi Free

Head into the world of Python Programming, easy an... Mored detailed. Build your own applications, right from the basics! Less
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[100% OFF] Mastering Agile Scrum Workshop Free

UPDATE FOR 2020 with Tanmay's latest knowledge on ... MoreAgile Scrum Certification! This course is about learning the latest Agile Scrum methodology for the Software development field. In this course, you will learn all other Agile methodologies along with detailed information on Scrum. By this course, experienced project managers can grow in their careers and get the next level of opportunity as an Agile Scrum Master and the junior team members can learn the process of the Agile Scrum methodology. The biggest target audience is at any experience level who wants to learn Agile Scrum in detail and apply in the career!!! Who this course is for: Project Managers who would like to be an Agile Scrum Master Qualifying Agile Scrum Master Certification Exam People who want to learn about Agile Scrum Developers, BAs, Architects, Analysts, Designers, Managers, etc Less
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[100% OFF] Practical Django With Python | Launch Your Startup Today Free

Hi ! i'm a freelancer from India you might have... More subscribed to online courses earlier which mess up with lot of boring theory explanations, and this course is completely different.we will learn the amazing framework(django) practically, it just turns your idea into a startup django is a kind of framework, where we can do the same thing in different ways, so as per my freelancing experience i will choose only one way to do a particular task. so in this course i will be explaining you my best practices that i do instead of explaining all the possible ways .this is the reason i reduced this course from 24 hours to nearly 4 hours removing all unnecessary stuff, this is just to make you learn quicker. everything is explained in simple English, instead of using Hi-Fi vocabulary and technical terms. so that it will be completely beginner friendly. Less
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[100% OFF] The Complete IP Subnetting Course: Beginner to Advanced! Free

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

Firebase ML Kit for Android Developer's Make yo... Moreur Android Applications smart, use trained model or train your own models explore the power of AI and Machine Learning. This course was recorded using Android Studio 3.6.1 (which is a great introduction to the development environment!) For a smooth experience I'd recommend you use the same, but students can still use the latest Android Studio version available if they prefer! Wish you’d thought of Object Recognition/Face Detection/Text Recognition? Me too. But until I work out how to build a time machine. Here’s the next best thing. Firebase ML Kit for Android Developer's Why choose me? My name’s Hamza Asif, Udemy’s coding instructor. It's not my first on mobile Machine Leaning. I have a course named "Machine Learning for Android Developer using Tensorflow lite" on udemy. So which course you should take? It's recommended taking "Machine Learning for Android Developer using Tensorflow lite" first so that you can understand the working of Machine Learning. If you want to learn a practical implementation and use of Machine Learning in Android then that course is for you. This is my 2nd course on Android Machine Learning and I am the only udemy instructor with more than one course on that topic. My goal is to promote the use of Machine Learning in Android and I am excited to share my knowledge with you. Android Version we will use? Android Pie, Android Q All the Android Application we will develop in this course we will use Android Pie and Q to test them. So we are\ So join my Firebase ML Kit for Android Developer's course today and here’s what you’ll get Learn practical implementation of Text Recognition, Language Identification, Face and expression detection, Barcode scanning, Landmark Recognition, Text Translation, and Object detection and recognition. With Auto ML learn how to train the model on your own dataset and use those models in Android Application Learn about both on-device and Cloud Machine Learning Why take this course? Machine Learning use is at its peak so is the mobile tech but people having skills to implement both are rare. This course will enable you to empower your Android Application with the practical implementation of Machine Learning, Computer Vision and AI. Having a little knowledge of Android Development, this course will differentiate you from other developers because you will have something that is currently in demand. This course will make provide you a smooth path to become a pro in using Machine Learning in your Applications. This course will not just enable you to apply machine learning in limited scenarios but It will enable you to Prepare or download your own dataset Train machine learning model Develop Android Application So if you have very basic knowledge of Android Development and want to apply Machine Learning in Android Applications without knowing background knowledge of Machine Learning this course is or you. Is this course for you? This is a one-size-fits-all course for beginners to experts. So, this course is for you if you are: A total beginner, with a curious mind and a drive to make and create awesome stuff using App development and ML A fledgling developer, want to add Machine Learning implementation in his skillset A pro app developer-heavyweight, with an itch to build your dream app An entrepreneur with big ideas Benefits to you Risk-free! 30-day money-back guarantee Freedom to work from anywhere (beach, coffee shop, airport – anywhere with Wi-Fi) Potential to work with forward-thinking companies (from cool start-ups to pioneering tech firms) Rocket-fuelled job opportunities and powered-up career prospects A sense of accomplishment as you build amazing things Make any Android app you like (your imagination is your only limit) Submit your apps to Google Play and potentially start selling within hours Thanks for getting this far. I appreciate your time! I also hope you’re as excited to get started as I am to share the latest use of ML in Android development with you. All that remains to be said, is this… Don’t wait another moment. The world is moving fast. And I know you’ve got ideas worth sharing. Coding really can help you achieve your dreams. So click the button to sign up today – completely risk-free. And join me on this trailblazing adventure, today. Who this course is for: Anyone who wants to learn the practical implementation of Machine Learning and Computer Vision in their Android Applications. Anyone who wants to make their Application smart. Anyone who wants to train and deploy Machine Learning models on his own data without background knowledge of Machine Learning. Less
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[100% OFF] Search Engine Optimization for Websites - SEO Basics Free

This course will teach students every thing about ... MoreSEO in 40 minutes and make them perform SEO by using the best practices. What's more this SEO course is built to stand the test of time...keep reading to find out why! "Short and essential" "Really engaging, like the way you explain all the little things, good for us beginners!" "Struggled with these concepts before this course. Thank you for explaining it so simply" "Great course by a great instructor." Who this course is for: Students desiring to learn SEO People who want to perform on their websites to increase traffic 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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[100% OFF ] HANDS ON DOCKER for JAVA Developers Free

This course is a 100% HANDS ON course for Java Ent... Morehusiasts who want to use DOCKER To Build->Ship->Run Java Apps using Docker and want to learn thru 10+ real world hands on use cases. This course is optimized for the busy professional with real world use cases examples and problem solving. The student registering for the course should be able to dedicate time towards Hands on labs to get a clearer understanding on how to use docker. Docker Version: 18.03.1-ce, JDK 8 Learn to build real world apps using Java and Docker with Microservices using the Spring framework, JQuery, Bootstrap and much more.... T Apart from the theoretical aspect here are the HANDS ON LAB Exercises which will be covered MICROSERVICES using Docker . Build a Spring MVC and MYSQL RESTFUL MICROSERVICE, Scale a micro service with multiple containers Build a Proxy Servlet, a filter with a Spring MVC app backed by MYSQL to load balance the requests between containers. Learn what the real world problems are and how Docker attempts to solve real world use cases. Learn to Run WEB Apps on Apache HTTP and NGINX Web servers in Docker as containers. Learn to run Simple Java Programs developed using JDK8 using Docker Create a sample Spring MVC Web App running with a bootstrap and JQUERY UI and run it using Docker Learn about Docker machines and Docker compose Upload your code to DOCKER HUB and share your Docker images for deployments with peers Less
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53 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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46 used

[100% OFF] A Guide To Learn Angular From Scratch Free

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

Take your react js skills to next level by buildin... Moreg Native Android and IOS Apps using React Native Less
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136 used, 100% success rate

[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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81 used

[100% OFF] CISSP Master Class: Become A CISSP Today Free

In this CISSP Master Class: Become a CISSP Today .... More I will help you with all the knowledge you need to pass the CISSP Certification. Hi, I am Sagar Bansal, . I have helped hundreds of students to pass CISSP Exam within their first attempt. For me, It is a simple exam in English, you need to answer the Questions from (ISC)²'s point of view, in their perfect world. Understand and answer every question from a Manager or a Risk Advisers point of view, NOT from an executive or as a techie. Most hands-on techies that fail the CISSP exams do so because they answer from a point of being reactive, not being proactive. The CISSP exam is using the Computerized Adaptive Testing (CAT) format, and is 3 hour long and will have 100-150 questions. Most people studying for the CISSP certification will use multiple books, video courses, and 3-5000 practice questions before taking the exam, this really is the path to success. Who is the target audience? Anyone wanting lean more about the CISSP certification! People wanting to grow their IT Security and Cyber Security knowledge New and experienced IT Security professionals Anyone wanting to break into IT Security Basic knowledge Wanting to pass the Information Systems Security Professional (CISSP) Certification Exam Wanting to learn about management level IT Security and Cyber Security What will you learn Prepare for the latest version of the Information Systems Security Professional (CISSP) Certification Exam Learn why you want to get your CISSP certification, what it can give you Where to start on your CISSP certification journey Learn why you want to get your CISSP certification, what it can give you Understand IT Security and Cyber Security from a management level perspective Less
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[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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[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] The Complete 2020 PHP Full Stack Web Developer Bootcamp Free

Do you want to be a Certified Web Developer? or... More Are you are a student and want to get a Job as Web Developer? or Do you want be Freelancer to earn an extra part time income? or You want to improve your Web Development Skills at Work? If these are your goals then this course is exactly made for you to Become PHP Full Stack Web Developer! 48+ hours of course content with Exercises, Quiz, Assignments and Projects. If you give your valuable time to this course and I will promise to help you achieve your goal. RIGHT AFTER THIS COURSE, YOU WILL BE: Able to Build websites. Get a job as a junior web developer. Start your own online business with WordPress. Become Freelancer Web developer on Fiverr or UpWork. Be proficient with databases and server-side languages with PHP and MySQL. Become a front-end and Back-end developer - Complete Full Stack Developer. In less than 30 days, you'll be ready for an entry-level job as a Full Stack Web Developer. This course will give you the following Skills: Front End Web Development: HTML. CSS. JAVASCRIPT. BOOTSTRAP. Back End Web Development: PHP. MYSQL. WORDPRESS. PHP OOP. BASICS: WEB BASICS. INTRODUCTION TO XML. COMPLETE UNDERSTANDING OF JSON. INTRODUCTION TO REST AND API. SOFT SKILLS: INTERVIEW QUESTIONS. PHP RESUME. STUDENT MENTORSHIP. PROJECTS: PHPKart - Complete Shopping Cart Website using HTML, CSS, JAVASCRIPT, PHP and MySQL. LearnWP.xyz - Blogging Website with WordPress. (Buy Domain, Web Hosting, Installing Themes and etc...) CERTIFICATION PROVIDED: Get your PHP Full Stack Developer Certification. VALUABLE RESOURCES: You will become PHP Full Stack Web Developer: 48+ hours of course. - Worth $199 You will be Certified PHP Full Stack Web Developer - Worth $399 Complete Source Code and Projects: PHPKart & LearnWP.xyz - Worth $299 Student Mentorship via Private Facebook Group. - Worth $219 PHP Projects Downloads. - Worth $129 Resume and Interview Questions. - Worth $79 Lifetime Documentation Site Access - Worth $29.90 30 Days Money Back Policy. Total Worth: $1353 FEEDBACK FROM STUDENTS: -> Amazing, above expectations! - Adeel Nazim -> I think , someone who wants to learn php , should start with this course.Great content , so much valuable info in this course , thank you!! - Andreas -> good course with lot of examples. this is the best course in PHP - Murali Krishna Nistala -> This course is very good introduction to PHP. Many examples and every lection has a test and a quiz. - Milan Švarc -> Very easy to understand, lots of examples. Repeats important points in different ways making difficult concepts easier to grasp. - Laura Long -> A well organized course, explained each and every concept in very easy way, now feeling confident while using PHP oop.- Wasim Tamboli -> This course is a easy to learn. and your teaching way is awesome. - Bharat Kumar -> He is explaining the concepts crystal clear . Very thankfull to the teacher - Ponmurali Jeyaprakasam -> Very easy to understand and the best part is there are too many assignments for working which makes u perfect - Gokul Singh Do not miss the Premium Contents with this course: 48+ hours of Full Stack Web Development Course. One Course Covers - 12 Courses: HTML, CSS, JAVASCRIPT, BOOTSTRAP, PHP, MYSQL, PHP OOP, WORDPRESS, XML, API, JSON and REST. 6 Web Development Books for FREE. (1200+ pages long) - Selling for $20 on Amazon Lifetime FREE Access to Premium Bootcamp Documentation Website. - Sold monthly membership PHPKart and LearnWP Website Source Code. - Sold my source code for each $299 Interview Questions (1000+ questions) - Selling for $20 on Amazon 30 days Money Back Guarantee (0% Risk) 100% FREE for Lifetime Access. IF YOU ARE REALLY SERIOUS TO LEARN WEB DEVELOPMENT AND LOOKING FOR THE RIGHT COURSE... THEN THIS IS THE BEST COURSE THAT CAN HELP YOU ACHIEVE YOUR GOAL.. BELIEVE ME, YOU ARE JUST ONE COURSE AWAY FROM BECOMING BRILLIANT WEB DEVELOPER.... Who this course is for: Anyone who wants to learn to code Anyone who wants to generate new income streams Anyone who wants to build websites Anyone who wants to become financially independent Anyone who wants to start their own business or become freelance Less
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177 used

[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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168 used

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

Every other course online teaches you the basic sy... Morentax 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 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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