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[100% OFF] The Complete Full-Stack JavaScript Course! Free

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

[100% OFF] The Self-Taught Programmer

The Definitive Guide to Programming Professionally
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[100% OFF] Deep Learning Course with Flutter & Python - Build 6 AI Apps Free

Join the most comprehensive Flutter & Deep Lea... Morerning course on Udemy and learn how to build amazing state-of-the-art Deep Learning applications! Do you want to learn about State-of-the-art Deep Learning algorithms and how to apply them to IOS/Android apps? Then this course is exactly for you! You will learn how to apply various State-of-the-art Deep Learning algorithms such as GAN's, CNN's, & Natural Language Processing. In this course, we will build 6 Deep Learning apps that will demonstrate the tools and skills used in order to build scalable, State-of-the-Art Deep Learning Flutter applications! After completing this course you will be able to: Learn the tools and skills to develop any AI idea you have onto a mobile phone. Have a clear understanding of different types of Neural Networks and how you can use them to your advantage. Build any Neural Networks in Python and then export them into your Flutter application. Use different strategies to get neural networks with 90%+ accuracy. Why should you choose this course? This course covers all the steps that one should take to create a Flutter application that uses State-of-the-Art Deep Learning approaches. It is extremely hard to find good tutorials that teach you how to implement these algorithms, so the instructor, Samuel Boylan-Sajous, who has been programming for years, and has a Computer Science degree at the University of Guelph, has decided to share all of his knowledge with other students that are passionate about Deep Learning and building practical A.I. applications. Here's what's included in the course: Building a neural network on Teachable Machine and exporting it into Flutter project Building a neural network in Keras/Python on Google Collab/Jupyter Notebook and exporting it into Flutter project Using API's to perform some Natural Language Processing and implementing those algorithms into our app. Build a GAN in python and implement it into your flutter application. And much more! This course is for you if ... You're interested in building real native mobile apps for the two most popular mobile platforms - iOS and Android You're passionate about Deep Learning/AI or Mobile Development and want to expand your knowledge. You want to expand your Deep Learning/AI portfolio with 6 Cutting Edge Deep Learning apps! Want to learn State-of-the-Art Deep Learning algorithms and how you can use them on a mobile device! Course prerequisites: Knowing mobile development will help a lot but is not a hard requirement (You would be fine if you only knew CSS/HTML & Object-Oriented Programming, just do some research on what Flutter is) Know some theory behind Neural Networks (Know how data is processed in a Neural Network) Our Promise Teaching our students is our job and we are committed to it. If you have any questions about the course content or anything related to any topic, you can always post a question in the course or send us a direct message. Less
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[100% OFF] Front End Web Development For Beginners (A Practical Guide) Free

Learn Front End Web Development Student reviews... More: "Great Course" -Rich Helton "This is great training for beginners and aspiring front end web developers this is simple yet very very informative" -Leynard Caballero Villagracia "I think it is a great course for the beginning level." -Hoang Cong "Great course and perfect explanation specially for beginners." -Kenan Dedoviq "Easy to understand for beginners..." -Hiren Bechra "Yeah, it's been a good match for me definitely. The content and the way of teaching by the mentors is very effective and efficient. Any one can begin with building web pages, taking up this certain course" -Abhinav Anand ======================================================== Not sure yet? Just scroll down and watch the free preview lectures! Enroll with confidence! Your enrollment is backed by Udemy's 30-day, no-questions-asked, money-back guarantee! What are the requirements? · All information and resources are included in this course. What am I going to get from this course? · Learn how to hand code HTML and CSS · Work with Bootstrap 4 · Build 2 great projects to get you started on your Front End Web Development education What is the target audience? · Anyone who wants to dramatically increase their Front End Web Development Skills! Less
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[100% OFF] Deep Learning for Beginners: Neural Networks in R Studio Free

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

You're looking for a complete Decision tree course... More that teaches you everything you need to create a Decision tree/ Random Forest/ XGBoost model in Python, right? You've found the right Decision Trees and tree based advanced techniques course! After completing this course you will be able to: Identify the business problem which can be solved using Decision tree/ Random Forest/ XGBoost of Machine Learning. Have a clear understanding of Advanced Decision tree based algorithms such as Random Forest, Bagging, AdaBoost and XGBoost Create a tree based (Decision tree, Random Forest, Bagging, AdaBoost and XGBoost) model in Python and analyze its result. Confidently practice, discuss and understand Machine Learning concepts How this course will help you? A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course. If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the advanced technique of machine learning, which are Decision tree, Random Forest, Bagging, AdaBoost and XGBoost. Why should you choose this course? This course covers all the steps that one should take while solving a business problem through Decision tree. 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. What is covered in this course? This course teaches you all the steps of creating a decision tree based model, which are some of the most popular Machine Learning model, to solve business problems. Below are the course contents of this course on Linear Regression: Section 1 - Introduction to Machine Learning In this section we will learn - What does Machine Learning mean. What are the meanings or different terms associated with machine learning? You will see some examples so that you understand what machine learning actually is. It also contains steps involved in building a machine learning model, not just linear models, any machine learning model. Section 2 - Python basic This section gets you started with Python. This section will help you set up the python and Jupyter environment on your system and it'll teach you how to perform some basic operations in Python. We will understand the importance of different libraries such as Numpy, Pandas & Seaborn. Section 3 - Pre-processing and Simple Decision trees In this section you will learn what actions you need to take to prepare it 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. In the end we will create and plot a simple Regression decision tree. Section 4 - Simple Classification Tree This section we will expand our knowledge of regression Decision tree to classification trees, we will also learn how to create a classification tree in Python Section 5, 6 and 7 - Ensemble technique In this section we will start our discussion about advanced ensemble techniques for Decision trees. Ensembles techniques are used to improve the stability and accuracy of machine learning algorithms. In this course we will discuss Random Forest, Baggind, Gradient Boosting, AdaBoost and XGBoost. By the end of this course, your confidence in creating a Decision tree model in Python will soar. You'll have a thorough understanding of how to use Decision tree modelling 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 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 4 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 Linear Regression modelling - Having a good knowledge of Linear Regression gives you a solid understanding of how machine learning works. Even though Linear regression is the simplest technique of Machine learning, it is still the most popular one with fairly good prediction ability. Fifth and sixth section cover Linear regression topic end-to-end and with each theory lecture comes a corresponding practical lecture where we actually run each query with you. Why use Python for data Machine Learning? Understanding Python is one of the valuable skills needed for a career in Machine Learning. Though it hasn’t always been, Python is the programming language of choice for data science. Here’s a brief history: In 2016, it overtook R on Kaggle, the premier platform for data science competitions. In 2017, it overtook R on KDNuggets’s annual poll of data scientists’ most used tools. In 2018, 66% of data scientists reported using Python daily, making it the number one tool for analytics professionals. Machine Learning experts expect this trend to continue with increasing development in the Python ecosystem. And while your journey to learn Python programming may be just beginning, it’s nice to know that employment opportunities are abundant (and growing) as well. 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 Anyone curious to master Decision Tree technique from Beginner to Advanced in short span of time Less
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[100% OFF] Learn Modern Javascript by Coding a Snake Game Free

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

Learn how to create and manage Kubernetes using on... Moree of the leading managed services on the market. Azure Kubernetes Service Zero to Hero admin guide is an intermediate course which describes: Comparison of Managed vs self-managed Kubernetes solutions; Pros and Cons of Managed Kubernetes services; AKS Capacity Analysis; Detailed AKS network architecture; How to create an AKS cluster using Azure Portal and Azure CLI; Integrate AKS with Active Directory; Create Kubernetes users using self-signed certificates; How AKS creates and manages Azure storage resources; AKS monitoring and log debugging. Who this course is for: Fearless Kubernetes administrators. 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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[100% OFF] MERN Stack Master Course - Building your own Instagram Free

MERN stands for MongoDB, Express.js, React.js and ... MoreNode.js - and combined, these four technologies allow you to build amazing web applications In this course we will be building FULL FLEDGED INSTAGRAM website and it will be a lots of fun as we building this together. This course covers - Building an backend API with Node.js & Express Testing API using Postman JWT based authentication Image upload Context API for state management React Hooks React Router hooks Protecting routes or endpoints Sending Emails Forgot & Reset Password This course is NOT an introduction course to React & Node js. It is fully hands on course for building full stacks websites using MERN Less
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[100% OFF] 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] Ultimate Hands-On English Phrasal Verb Guide: Spoken+Written Free

If you want to be fluent in English and sound nati... Moreve, you need to know phrasal verbs well. There's a ton of information on them, but it's all in tiny pieces spread across grammar books, dictionaries, and various websites. I spent a year putting this information together and building this course to make phrasal verbs as easy to understand as physically possible. By taking this course you'll save tons of time and the frustration involved in digging for bits and pieces of necessary information. This course breaks down what phrasal verbs are, why they matter, what kinds of phrasal verbs exist, and what is the best way to learn them. You will learn 10 of the 1.5% most common phrasal verbs in the English language: what they are, which of their meanings are the most/least common (with the % of their usage and examples), and a variety of exercises to help you cement them in your memory. This course will give you the NECESSARY knowledge to transform your "good English" into "native English" - as long as you follow all recommendations and do all the exercises provided. Note that the theoretical part (video) of the course is 40 minutes long, but the activities section is expected to take 5-6 hours. This is because I have created custom exercises for you to practice what is taught in the video. Who this course is for: Pre-Intermediate (or higher) English learners who want to think and speak more naturally. Students trying to write better university papers in English. People that have/are looking for a job that requires English. People who deal with English on a daily basis. People that know that their English is not perfect and there’s space for improvement. People that know that their English is almost perfect and there’s a tiny bit of space for improvement. ;) People that struggle to understand native speakers. Less
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[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] Core Java Interview Bootcamp To Handle Interviews With Confidence. Free

Hi everyone :) Having you stop here simply mean... Mores you are either preparing for a core java interview or want to know the most widely asked questions in the room. This course is intended for you folks, perfectly. The course basically aims at providing an in-depth explanation to most continuously asked questions through very engaging animated PPTs. Whether it's string, or exceptions, or multi-threading, I have got your back on most asked questions from these topics. The much important thing is the clear and concise clarity in explanations that you will get from this course. Note: 1. The course is not intended for complete beginners! You need to have at least basic to intermediate knowledge of core java. 2. I will keep on adding brand new most asked questions regularly. So, this course is not just limited to a fixed number of questions! Rest assured, you will enjoy this awesome Bootcamp with me. See you in the course... Over n Out :) Less
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[100% OFF] Learn to Code with Python 3! Free

If you would like to learn Python 3 programming in... More 2020, you are going to LOVE this course! Get started with the most beginner friendly programming language and start writing your very own programs today! We will cover the following topics in this course: Introduction to Python and setup Python programming basics Functions - coding exercises Lists, tuples and dictionaries Files in Python 3 Error handling Object oriented programming Date & time Regular expressions Interacting with HTTP Networking in Python 3 Threading E-mails, PDFs, images This course was designed for absolute beginners who wish to master the Python programming language. All lectures are downloadable for offline viewing. English subtitles and a certificate of completion are are available as well. Thank you for taking the time to read this and we hope to see you in the course! Who this course is for: Students interested in learning the Python programming language. Students who wish to pursue a career in software development. Less
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[100% OFF] Ionic and React: Building a Mobile Application UI Free

The Ionic Framework is supported on a variety of m... Moreobile (and desktop) platforms. In this course, you will learn how to go from no code to your very own application ready for sale on the Apple App Store and Google Play Store. Unlike many courses that spend a lot of time on background, this course will be fast-paced, with a minimum of fuss and fluff. It's all hands-on. I expect you to have some basic understanding of web development. You should know what a div is, for example; and know how to create a button. You should have a decent grasp of JavaScript, but you don't need to be a master. I don't expect you to be an expert in React, but you should grasp the basics of JSX, component architecture, state, and hooks. Other concepts will be explained as needed, as close to their use as I can get. By the time you complete the course, you should have the confidence you need to create and deploy your own mobile app UI for iOS or Android. It'll be a fast ride, so enroll now and hang on. Who this course is for: Any developer wanting to publish mobile applications with technology they already know and love. 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] Machine Learning with Jupyter Notebooks in Amazon AWS Free

Are you a company or a IT administrator, data cent... Moreer architect, consultant, enterprise architect, data protection officer, programmer, data security specialist, or big data analyst and want to gain fundamental and intermediate level skills and enjoy a fascinating high paying career? Or maybe you just want to learn additional tips and techniques taking to a whole new level? Welcome to Machine Learning, Reinforcement Learning and AWS course For Beginners - A one of its kind course! The flipped classroom model with hand-on learning will help you experience direct into the course as your begin your learning journey. Be sure to watch the preview lectures that set course expectations! In this course, you'll learn and practice: Machine Learning topics Jupyter Notebooks Reinforcement Learning Machine Learning Services in AWS AWS Sagemaker Dynamic Programming Q-Learning Understand best practices, and much more.... You will also get complete resources, toolkit, and code where applicable with this course! We've built this course with our Team ClayDesk of industry recognized developers and consultants to bring you the best of everything! So, if you would like to: - start your freelancing career and consult companies, this course is for you - gain marketable skills as an IT expert and professional, this course is for you - This course is not designed for advanced level students ...this Machine Learning, Reinforcement Learning and AWS course is exactly what you need, and more. (You’ll even get a certification of completion) See what our students say “It is such a solid course that covers all important areas of machine learning, and I now know hoe to predict future products based on their features. Simply awesome!.” - Alex Neuman “This is such an awesome course. I loved every bit of it – Wonderful learning experience!” Ankit Goring. Join thousands of other students and share valuable experience Why take this course? As an enterprise architect consulting with global companies, technology evangelist, and brand innovator, I have designed, created, and implemented enterprise level projects, I am excited to share my knowledge and transfer skills to my students. Enroll now in Machine Learning, Reinforcement Learning and AWS today and revolutionize your learning. Stay at the cutting edge of Machine Learning and Data Science —and enjoy bigger, brighter opportunities with AWS. Qasim Shah Who this course is for: Beginner IT professionals who want to get in the forefront of the Artificial Intelligence and Machine Learning game Anyone who is curios about machine learning 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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