Angular Essentials (Angular 2+ with TypeScript)
Tuesday, November 30, 2021
Online Courses Udemy - Angular Essentials (Angular 2+ with TypeScript), The most efficient way to dive into Angular 2 or Angular 5 if you got limited time or need to refresh the basics!
- 4.6 (2,636 ratings)
- Created by Academind by Maximilian Schwarzmüller, Maximilian Schwarzmüller
- English [Auto-generated], Indonesian [Auto-generated], 4 more
PREVIEW THIS COURSE - GET COUPON CODE
What you'll learn
- Build highly reactive and user-friendly web applications running in the browser (driven by JavaScript)
- Dive deeper into Angular with very solid fundamentals taught by this course
Requirements
- You should bring solid JavaScript knowledge
- NO Angular knowledge is required at all (this includes Angular 1, 2 or 4)
Description
Angular is an amazing JavaScript (TypeScript) framework which allows you to build small, medium or large Single-Page-Applications (SPAs). Since the code runs entirely in the browser, you can build user experiences which are way faster than traditional websites could ever be!
The skills required to build such SPAs are in extremely high demand since this kind of web app is very popular and allows you to build almost mobile-like, highly reactive user experiences. Indeed most modern web applications are built as SPAs today!
As the creator of the 5-star rated, BESTSELLING Angular course here on Udemy, I know what I'm talking about and I know what the core features of Angular are which you need to learn.
It's my goal to allow you to focus on these core features to get the quickest and best introduction into Angular, you can find!
Learning Angular never is a wrong choice and with this course, it's more correct than it ever was before! This course gives you the fastest and most efficient way of diving into Angular. If you don't want or can't take my Complete Guide on Angular or you want to get a feeling for Angular before doing so, this course is for you! It's also your #1 choice if you already know Angular but want to have resource for refreshing your basic Angular knowledge as fast as possible.
Whilst this course is much shorter, it gives you all the core insights into Angular you need. It focuses on the heart of Angular, the most important features Angular offers you and even shows you how to build a complete Angular app!
Telling by the length of the course, you might not believe it, but you'll actually learn about all these topics:
- What Angular is
- What TypeScript is - including a super-efficient introduction to it
- How to use the CLI to create Angular projects and manage them
- How Angular apps start and work
- Which role components play and how to use them
- How to bind and pass data
- How to debug your app
- How to use other, 3rd party JS libraries in an Angular app
- How to use directives
- How you may manage application state with services
- How to turn your SPA into an "illusionary" MPA with routing
- How to handle user input with forms
- How to send Http requests
- How to build your project, optimize it and deploy it
- Much more!
Mastering JavaScript Arrays
Mastering JavaScript Arrays - Accelerate Your JavaScript Skills by Mastering this Very Important Data Structure
What you'll learn
- Every trick and method for working with arrays.
- Different ways to create arrays and work with elements.
- Multiple methods for iterating arrays.
- Methods for working with array-like data and converting them to arrays.
- Unique ways to create arrays and access elements.
- Methods on the array prototype and how to use them.
- Methods preferred with the functional programming paradigm.
- Ways to combine arrays and extract values.
- Multiple ways to search arrays for values.
- Process of working with Maps and Sets.
Requirements
- Basic familiarity with JavaScript. How to enter statements and work with the language.
- Access to a text editor in order to enter and work with JavaScript code and then be able to run it in a browser.
Description
Effectively working with arrays is critical to any JavaScript programmer. Arrays are an important data structure, and this course will provide you with the competency you need to master them.
In this course you are going to learn all there is to know about JavaScript arrays. I start from the beginning, so if you are comfortable with JavaScript, you may want to use the first section as a review or skip it. You will learn the basics of different ways to create an array and work with the elements. You will learn the basics of iterating an array and some unique ways to create arrays and access elements. You will learn all the methods to modify or mutate an array, as well as those methods that are preferred in the functional programming world because they preserve the original array. You will learn how to combine arrays and extract values as well as multiple ways to search arrays for values. We will end with a look at some array-like collections available in JavaScript and how you can use those.
By taking this course:
You will feel more comfortable working with arrays in any coding problem you encounter.
You will become more familiar with functional methods for working with arrays (reduce, map, filter).
You will become familiar with and use all the different methods for manipulating an array in JavaScript.
You will be able to work with arrays using different techniques.
If you learn by doing, this course gives you plenty of chances to work on an exercise and then sit back and watch as I go through that exercise. Jump in today and begin mastering JavaScript Arrays!
Who this course is for:
- From beginner to advanced level JavaScript developer who wants to learn more about arrays.
Python Learn by Python Projects & Python Quizzes in 2021
Python Learn by Python Projects & Python Quizzes in 2021 - Python full Course Python Quizzes, Python Projects in Games,Data Analysis & Python Scripting for all Python 3 Developers
What you'll learn
- Learn Python in easy and simple way.
- How to use Python with PostgreSQL to Analyze Data.
- 13 Python projects to Master The Python Powerful Skills you will learn.
- Learn how to code in Python in simple and easy way.
- Learn Python programming basics.
- Learn how to use Jupyter notebook and IPython for Python coding.
- Learn coding in Python by examples.
- Apply what you will learn in Python through exercises.
- Learn how to use and handle Python strings.
- Learn Python Data Structures.
- Learn how and when to use Control Flow and Loops in Python.
- Learn Python Functions Programming.
- Learn how to use Python to open files.
- Learn Object Oriented Programming(OOP) in Python.
- Learn Python by doing through Python Projects.
Description
Python Programming course, full Guide for Python Programmers & Python Coders in a simple and easy way with Python Examples, Python quizzes, Resources & 13 Python Real Wold Projects in Python Games, Python OOP , Python Data Analysis, Python Database Python Apps & Python Scripting to master Python 3 from zero to hero in this course.
What you will learn in this course ?
Learn Python by doing 13 Python Real World Projects in Python Games, Python OOP , Python Data Analysis, Python Database & Python Scripting.
In this course you will learn how to Install Python 3.
In this course you will learn how to use python IDLE.
In this course you will learn how to choose Python IDE to learn coding.
In this course you will learn how to Install Anaconda for Python coding.
In this course you will learn how to use Online Jupyter for Python Programming.
In this course you will learn how to use Python IDLE.
In this course you will learn how What the difference between Variables & Operators in Python.
In this course you will learn Operators Types in Python.
In this course you will learn Python Data Types.
In this course you will learn String Functions & entries in Python.
In this course you will learn how to use Input String Function in Python.
In this course you will learn Python Data Structures.
In this course you will learn how to create Lists & lists operations in Python.
In this course you will learn how to create Dictionaries & Dictionaries operations in Python .
In this course you will learn how to create Tuples & Tuples operations in Python.
In this course you will learn and when to use For Loop in Python. to create Sets & Sets operations in Python.
In this course you will learn how and when to use Control Flow and Loops in Python.
In this course you will learn IF Statement and control flow in Python.
In this course you will learn how and when to use For Loop in Python.
In this course you will learn how and when to use While Loop in Python.
In this course you will learn how to Handle Errors in your Python programs.
In this course you will learn how and when to use Python Functions.
In this course you will learn how and when to create functions in Python.
In this course you will learn how and when to use Lambda Expression in Python.
In this course you will learn how to create and use to Python Modules.
Lear how to use Python to open files.
Learn coding in Python by examples in this course.
Apply what you will learn in Python through exercises in this course.
Recap files to review what will learn in Python in this course.
Why to master Python Programming Language by this course ?
Python is a high level programming language, strong, elegant, and easy to learn.
Python is Faster than R programming language when used for data science.
Python Has lots of libraries which facilitate its use for data analysis.
Python is Objective oriented programming Language so you can use objects when coding in python.
Python is Free open source programming language.
Python can be used for a large variety of programming tasks, such as for desktop applications, game programming and mobile development all of that can be done using Python programming Language.
Python is a cross platform language, which means that code written for one operating system, such as Windows, will work well on Mac OS or Linux without making any changes to the Python code.
Who this course is for:
- Beginner Python Programmer who want to master Python programming Concepts in simple and easy way.
- Python programmers willing to master python for data analytics.
- Students want to master Python programming basics.
- Students how want to learn how to use python Idle and, jupyter notebook (Ipython).
- Students want to apply Python knowledge through Python Projects
- Students want to learn how use impeded Python interpreter in Udemy.
- Students want to build the skills that is needed to get your first Python programming job.
- By the end of the course you’ll get the confidence to code in Python smoothly & fluently.
- Are you welling to learn Python Pandas & Data Visualization?
React Pizza Shop - Ordering Food with Hooks and Firebase
Sunday, November 28, 2021
React Pizza Shop - Ordering Food with Hooks and Firebase - Build a Tasty Restaurant Ordering App with React Hooks, Firebase, and Styled-Components. Mamma Mia!
What you'll learn
- Cutting-edge React Development with React Hooks : useState, useEffect and your own custom hooks
- Build a Complete Pizza Ordering Application for Customizing Restaurant Orders and Emailing Users
- Beautiful UI Development from Scratch with Food Grids, Popup Dialogs, Buttons, Input Controls and more
- Styled-components : The hottest CSS-in-JS library featuring CSS animations and extendable component styling
- Authenticate Users with Google to Login and Logout
- Firebase Realtime Database : Save pizza orders on Google's Serverless Data Platform
- Firebase Functions and Nodemailer: Respond to order generation by emailing users their order
- Ecommerce Patterns : Adding, Removing and Editing Orders, Calculating Tax and Totals for Dynamic Food Items
- Hosting : Deploy your app on the web with Firebase Hosting
Description
Welcome to React Pizza Shop. Here’s what we’ll be building: A pizza ordering system with multiple types of foods and editable popup dialogs to customize your order with delicious items from a menu. We'll add interactivity with a variety of custom React Hooks. After authenticating with a Google account, we’ll send this order to Firebase Realtime database and a serverless Firebase function will send your user an email confirmation of their order.
This course is intended for intermediate React developers looking for a fun project to practice React Hooks and/or learn Firebase. The full source code is provided. If you have any questions throughout the course, do not hesitate to reach out.
Here's just some of the features included in this 5+ hour course:
React with Hooks
useState, useEffect
Build custom hooks to control input elements, authentication, dialogs and more
Beautiful UI Development
Styled-components
Popup Dialogs
Buttons, Inputs, Checkboxes
Adding Stock Photos
Flexbox and CSS grids
CSS animations
Google Fonts
create-react-app boilerplate
Starting from scratch
Building for production
Firebase
Deploying your site with Hosting
Authenticating users with Google, logging them in and out
Realtime Database to track food orders
Functions to respond to orders
Ecommerce Ordering
Adding, Removing Editing orders
Calculating tax and totals of orders
Dynamic food items
Emailing orders with Node.js and Nodemailer
Favicon app icon
Who this course is for:
- Students learning React and Web Development looking for a professional course at an intermediate to advanced level.
Deep Learning Practical-Neural Network Projects Bootcamp2021
Deep Learning Practical-Neural Network Projects Bootcamp2021 - Build Real World Deep Learning Projects, Learn Deep Learning Algorithms with Python (Data science, Machine Learning)
- Hot & New
- Created by TheMachineLearning.Org .
- English [Auto]
What you'll learn
- Have a great intuition of many Deep Learning models
- Apply Artificial Neural Networks in practice
- Make robust Deep Learning models
- Master Deep Learning With Python
- Understand the intuition behind Artificial Neural Networks
Description
A newly re-invigorated form of machine learning, which is itself a subset of artificial intelligence, deep learning employs powerful computers, massive data sets, “supervised” (trained) neural networks and an algorithm called back-propagation (backprop for short) to recognize objects and translate speech in real time by mimicking the layers of neurons in a human brain’s neocortex.
Deep learning (sometimes known as deep structured learning) is a subset of machine learning, where machines employ artificial neural networks to process information. Inspired by biological nodes in the human body, deep learning helps computers to quickly recognize and process images and speech. Computers then "learn" what these images or sounds represent and build an enormous database of stored knowledge for future tasks. In essence, deep learning enables computers to do what humans do naturally- learn by immersion and example.
Deep learning has been around since the 1950s, but its elevation to star player in the artificial intelligence field is relatively recent. In 1986, pioneering computer scientist Geoffrey Hinton — now a Google researcher and long known as the "Godfather of Deep Learning" — was among several researchers who helped make neural networks cool again, scientifically speaking, by demonstrating that more than just a few of them could be trained using backpropagation for improved shape recognition and word prediction. By 2012, deep learning was being used in everything from consumer applications like Apple's Siri to pharmaceutical research.
Who this course is for:
Beginners in deep learning
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Complete Backend (API) Development with Python A-Z™
Saturday, November 27, 2021
Complete Backend (API) Development with Python A-Z™ - Learn how to build fast, secure and documented API with python. Backend best practices, load balancers, stress tests etc
What you'll learn
- Python API Frameworks
- Building API from scratch
- HTTP Methods
- API versioning
- API Authentication Methods
- API documentation
- Docker containers
- Database Connection - ORM
- API caching
- Load Balance your backend
- Building secure backend
- API Load Testing
- API Unit Testing
- Reverse proxy - NGINX
- Connect domain with API server
- HTTPS
- Technologies that you will learn: fastapi, locust, apache bench, nginx, redis, docker, postgresql, ssh, insomnia, postman, swagger
Requirements
- You need to have basic programming skill
- You should be heard of what is cloud, backend and API
Description
This course for anyone who wants to be python backend developer. You will learn what is API and some python API frameworks. You will find all the fundamentals about backend development in lectures. With this course, you will learn how to build secure, fast, scalable, documented and well tested API. Beside this, you will learn the caching and database best practices. This is not just an API framework course, this is complete course that teaches you everything about backend development. You will learn the best practices. You will see the best path of how to develop a good API.
In this course you will learn fastapi python framework. It is the fastest and most convenient python framework. As a production environment you will learn digital-ocean cloud and as a deployment mechanism you will learn docker. This course starts from teaching what is API and ends with secure, tested, documented, cached and versioned best practice API. After this course you will be able to create your own API and create your own database and connect it from your API. Also you will get a domain name and put it to your API server. With load balancer, millions of users will be no more trouble. With nginx reverse proxy, you will be able to set any security or rate limit configuration to your API.
This is very comprehensive and complete backend development course. You will learn a lot of concepts and best practices. After this course you will reach the senior developer knowledge.
Who this course is for:
- Backend Developers
- Full-Stack Developers
- Python Developers
- People who want to build own backend architecture
- Curious about backend API systems
Complete Machine Learning with R Studio - ML for 2021
Complete Machine Learning with R Studio - ML for 2021 - Linear & Logistic Regression, Decision Trees, XGBoost, SVM & other ML models in R programming language - R studio
- Created by Start-Tech Academy
- English [Auto]
What you'll learn
- Learn how to solve real life problem using the Machine learning techniques
- Machine Learning models such as Linear Regression, Logistic Regression, KNN etc.
- Advanced Machine Learning models such as Decision trees, XGBoost, Random Forest, SVM etc.
- Understanding of basics of statistics and concepts of Machine Learning
- How to do basic statistical operations and run ML models in R
- Indepth knowledge of data collection and data preprocessing for Machine Learning problem
- How to convert business problem into a Machine learning problem
Description
You're looking for a complete Machine Learning course 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
React js. From the beginning. w/ Redux and React Router
Friday, November 26, 2021
Free Coupon Discount - Learn React v16 from the beginning! Including React Router, redux, and create react app with multiple projects | Created by Robert Bunch
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- Server Side Rendering with React and Redux
- React - The Complete Guide (incl Hooks, React Router, Redux)
- Advanced React and Redux
- 2019 Update! React Testing with Jest and Enzyme
Preview this Udemy Course GET COUPON CODE
Description
TL;DR - React is awesome. I've been teaching it professionally for 4 years and love it. Learn it here!
This course:
Starting with Angular 1 in 2010, JavaScript frameworks exploded onto the scene and are required by virtually every large website on the Internet. React, which appeared a few years later in 2013 has become the dominant tool in that group. What does that mean for you? You can learn to use the same front-end framework used by Facebook, Amazon, Netflix, BBC, Airbnb, and Ebay, to name a few. And you won't just learn how to use it, but you'll learn the fundamentals around it.
What I need from you:
I need you to know JavaScript, CSS, and HTML.
It's not required to use React, but React makes very heavy use of ES6 (the 2015 update to JavaScript), so the course will use ES6 after the first main section. I will briefly mention how it works as needed, and add a supplemental section that covers those parts.
I need you know how to navigate your computer, not be afraid of the terminal, and ask questions as you have them!
Why me:
I first used React in 2014 for a small company website. I've also used Angular, Vue, and Ember along with most other major UI frameworks and I'm a believer in React. I've taught it professionally for 4 years, and have built sites for some of the largest companies in the United States using React Router and redux alongside. I will teach you one step at a time, whiteboard, and start from ground zero before getting to webpack and eventually Redux. Prepare to start learning the best JavaScript framework!
Sections:
Environment Setup (skip if you have node installed already)
React 101
State and Events
The Component Lifecycle and HTTP
Project 1 - Flash Card app (AWS services)
React Router
Redux
Redux Middleware (redux-promise and redux-thunk)
AirBnB Clone with Redux - (still In development)
Context - (still In development)
Hooks - (still In development)
React Deployment - (still In development)
Supplemental - ES6 for React - (still In development)
Who this course is for:
Devs who know how to use JavaScript and want to start using React to make their UI's easier to manage
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The Complete React Bootcamp 2021 (w/ React Hooks, Firebase)
The Complete React Bootcamp 2021 (w/ React Hooks, Firebase), Become an advanced ReactJS developer, build and deploy three production-ready apps with React, React Hooks, and NodeJS.
What you'll learn
- Build and deploy responsive and production-ready React apps from scratch
- Setup and develop a React app with firebase (cloud functions, cloud messaging, realtime database, storage, auth)
- Master React Hooks and latest React syntax
- Master state management with React Hooks and Context API
- Learn and practice bleeding-edge JavaScript (ES2020)
Requirements
- HTML + CSS fundamentals
- Basic comprehension of programming (i.e variables, loops)
- JavaScript basic knowledge would be a PLUS, but NOT essential
- NO prior experience with JS-frameworks is required
Description
Created with up-to-date versions of React, React Hooks, Node.js, JavaScript, and Firebase.
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What is this course all about?
This course is about React - a library that helps developers to create user interfaces on the web. But React is not limited only to user interfaces, there is much more to that.
Have you ever wondered how Facebook, Twitter, or Netflix websites are built and why they don't feel like websites at all? React can answer all of that. In this course, we show how to create mobile-feel-like websites (Single Page Apps) where React is the foundation.
First, we will guide you through the basics of web development before jumping into React. Here we will talk about the latest JavaScript, Node.JS, Git, APIs, and essential tools to make you feel as comfortable as possible at any stage of the development process.
Then we slightly move to React with a small portion of theory. At this point, you will get to know what React is made of and how it works.
Our first project is a Tic-Tac-Toe game. Here you will get to know React basics, hooks, and core functionality. By the end of this project, you will be able to create a simple web app that shows off your strong React basics. Here you will experience the development flow of a React app in general.
The second project is a movie search web-app called Box Office. With this project, we move towards more complex React use-cases and we start working with external APIs, dynamic layout, and pages combined with different approaches for styling a React app. Here we will work with more advanced and custom React Hooks. At the end of this project, we will analyze and optimize the app with React hooks to make it even more faster and reliable. We will even turn it into a Progressive Web App that works offline!
The final project is going to be a Chat app. It will include the following features: social media logins, account management, role-based permissions, real-time data, and lots of others. In this project, we will combine React with Firebase - a backend solution in the cloud, powered by NoSQL database. You will master global state management with Context API and sharpen your knowledge of React hooks. At the final stage, we will extend the app with a custom backend in form of serverless.
All of our projects will have a user-friendly and well-designed user interface that is responsive and optimized for all devices.
Is this course exactly what are you looking for?
If ...
... you are eager to learn front-end development with React from scratch ...
... you have some experience with React, but you don't feel confident ...
... you only started to learn web development and want to move towards modern tools and technologies ...
... you feel that you stuck doing only HTML, CSS and some JavaScript ...
... then this course is definitely for you!
What do you need to succeed in this course?
HTML and CSS is absolutely required
General/basic understanding of programming or JavaScript
No prior experience with React or JavaScript frameworks
Passion to learn new things :)
After this course, you will have:
Three real-world React projects of different complexity that can be put into your resume
Total React comprehension
Experience with popular React libraries
Knowledge of how to create and deploy React apps
Knowledge of custom serverless backend and Firebase
Topics that will be covered and explained:
React basics (syntax, core concepts, theory)
Scaffolding templates (create-react-app, nano-react-app /w Parcel)
Styling of React apps (CSS, SASS, UI components library, CSS-IN-JS /w Styled components)
Conditional rendering (dynamic content and styles)
State management, local + global (/w React Hooks, Context API)
Components analysis and optimization (/w React hooks)
Complex layout management
Dynamic pages with React Router
Progressive Web Apps and service workers
Real-time subscriptions in React
Using external APIs to fetch remote data
Deployment of React apps (github pages, surge, firebase)
Serverless backend with cloud functions in node.js
Latest and modern JavaScript (ES6 - ES2020)
Not part of React, but included:
Git, Node.js, APIs, ESLint and Prettier quick guides
Firebase (/w NoSQL realtime database, cloud functions, cloud messaging, cloud storage)
Serverless cloud computing idea and concept + explanation about docker containers
Don't just take our word for it, see what our past students had to say about this course:
"First of all, the course is really well done and very comprehensive. It covers important real-world concepts like optimizing your code with code splitting, memoizing, useCallback." - Toni S
"Great course content & prompt response to Q&A!" - R L
"Instructors are responsive, got help quickly when I needed it." - Leigham Springer-sutton
What if you stuck during the course?
Getting stuck is the worse and inevitable. At the same time it's a common thing for a developer. We understand that and we are always ready to help you out with your questions as quickly as possible.
What if you are not satisfied with this course?
We are so confident that you will love this course that we're offering a 30-day money-back guarantee! You can sign up today with zero risks.
What are you waiting for? Enroll today!
Who this course is for:
- Anyone who wants to develop scalable web-apps with React
- Programmers who want to increase their value as web developers
- People who are eager to learn how modern web-apps are working and how everything is connected
- Anyone who wants to develop applications like Facebook or Twitter
- Anyone who wants to become a freelancer or an independent web app developer
Advanced REST APIs with Flask and Python
Advanced REST APIs with Flask and Python - Take your REST APIs to a whole new level with this advanced Flask and Python course!
What you'll learn
- Integrate advanced functionality in your API such as image upload, payments, or user confirmation e-mails!
- Bring your REST API development to a whole new level by getting familiar with more of the Flask ecosystem
- Improve operations of existing REST APIs with database migrations and extensive refactoring knowledge
- Easily deploy documentation pages and test your API with Postman's collection runner
Requirements
- Have programming experience with Python (preferable) or another Object-Oriented Programming language
- Some knowledge of how the web works (requests and responses) will be helpful!
- PyCharm (free) or another code editor
Description
Welcome to our Advanced REST APIs with Flask and Python Course!
We created the most popular introductory REST API development course on Udemy, with over 15,000 reviews and 80,000 students. Now we want to help you get even farther with your Flask REST APIs, with new features and functionality.
Our first course took you from zero to a deployed REST API that users could access. In this one we will cover new and advanced features that take your REST APIs with the next level!
Topics covered
Simplify data serialization and deserialization in REST APIs using marshmallow
Handle user account confirmations by sending e-mails with Python
Image uploads using Flask-Upload
Simplify making changes to your database structure with database migrations using alembic
Write documentation and test your REST API using Postman
Handle payments and process orders using Stripe
Social login using OAuth. You can use this log in with Twitter, Facebook, GitHub, or any other third party.
Use the latest technologies and the best practices. Everything you'll learn works with Python 3.10, the latest version.
Course structure
This course builds upon another: "REST APIs with Flask and Python". If you don't have any Flask experience we recommend taking that course first.
We won't teach you the very basics of REST API development or Python in this course. We'll give you a finished project and extend it every section. We explain everything about the starter project very carefully, and we've even written an e-book about it!
We introduce new features and technologies by adding them to the starter application so you can see how we build professional REST APIs. As we add features, we'll also test them.
That will also help you understand more about how to add features to your REST API incrementally. This makes development faster and minimises risk.
Extra resources
Many lectures contain extra resources, such as links to external documentation and projects, for you to learn more. And for each lecture, we include the source code at the start and at the end so you can follow along and never get lost. All the source code is on GitHub for your convenience.
We're always available to help in the Udemy Course Q&A and also our own student community Discord server.
Advanced REST APIs with Flask and Python
Remember, this is our most advanced course yet! You should have enough programming experience with Python or another programming language. You should have knowledge of how to install Python packages and how to run your Python applications. Some knowledge of how the web works is also really helpful.
Thank you for considering this course. I'll see you on the inside!
Who this course is for:
- Software developers working on a REST API who want to add advanced functionality to it
- Backend developers interested in gaining knowledge of Flask and its ecosystem
- Advanced developers of other programming languages who want to get up to speed quickly with Advanced REST API development in Python
Practical Machine Learning: Build 25 Projects From Scratch
Wednesday, November 24, 2021
Practical Machine Learning: Build 25 Projects From Scratch - Practical Machine Learning Course: Learn To Build Machine Learning, Data Science Projects & Case Studies With Python
What you'll learn
- Build Best Performing Machine Learning Models
- Have a great intuition of many data science models
- Learn how to build data science models
- Learn how to use Scikit-learn to apply powerful machine learning algorithms.
- Make robust data science models
- How to improve your Machine Learning Models
- Create supervised machine learning algorithms to predict classes.
- Learn best practices for real-world data sets.
Description
Basically, the machine learning process includes these stages:
Feed a machine learning algorithm examples of input data and a series of expected tags for that input.
The input data is transformed into text vectors, an array of numbers that represent different data features.
Algorithms learn to associate feature vectors with tags based on manually tagged samples, and automatically makes predictions when processing unseen data.
While artificial intelligence and machine learning are often used interchangeably, they are two different concepts. AI is the broader concept – machines making decisions, learning new skills, and solving problems in a similar way to humans – whereas machine learning is a subset of AI that enables intelligent systems to autonomously learn new things from data.
Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to self-learn and improve over time without being explicitly programmed. In short, machine learning algorithms are able to detect and learn from patterns in data and make their own predictions.
In traditional programming, someone writes a series of instructions so that a computer can transform input data into a desired output. Instructions are mostly based on an IF-THEN structure: when certain conditions are met, the program executes a specific action.
Machine learning, on the other hand, is an automated process that enables machines to solve problems and take actions based on past observations.
Who this course is for:
- Beginners in data science
MERN Stack Full Ecommerce Site - Using React, Redux, Node.js
MERN Stack Full Ecommerce Site - Using React, Redux, Node.js, Build Powerful MERN Stack Ecommerce Project using React, Redux, Node.js, Express, MongoDB, Stripe from DEV to DEPLOYMENT
What you'll learn
- Full Stack Web Development using MERN
- How to Build powerful projects using MERN
- Learn how to build powerful and fully functional E-commerce website using MERN
- Learn how to build backend API using node and express
- Learn about Redux (Best state management tool)
- Payment Integration using Stripe
- Best Authentication practices
- Add filters, search and pagination
- Complete Admin Dashboard to manage products, orders, reviews, users
- Complete ratings & reviews system
- Learn how to add third party site like cloudinary to upload images
- Complete Cart & Checkout process
- Deployment
- and much more ...
Requirements
- Must understand and write JavaScript code
- Must be familiar with main technologies like Node, React, MongoDB
- Nothing else is required
Description
If you want to learn Full Stack Web Development using MERN stack then you have arrived at the right page. In this course, you will How to Build a Fully Functional E-commerce website using MERN Stack.
In this course, we will use four powerful technologies: React (Frontend), Node.js (Backend runtime environment), Express (Backend Framework), MongoDB (Database).
We are also going to using Redux for state management, stipe to handle our payments, Cloudinary to handle our images, and follow the best practices to implement Authentication & Authorization.
So if you are really interested in full-stack development or if you want to learn real implementation of MERN stack, Then I will see you in the course. Below are course highlights that you can read:
Setting Up Environment
Starting with ShopIT Backend
Adding Products Resource
Backend Error Handling
Adding Filter, Pagination, Search
Authentication & Authorization
User Routes
Adding Orders Resource
User Reviews
Starting with ShopIT Frontend
Implementing Redux
Adding Pagination, Search & Filters
Users & Authentication Frontend
Adding Shopping Cart
Handle Checkout & Payments
User Orders & Reviews
Admin Routes
Deployment
Your Task / Assignment
Who this course is for:
- JavaScript Developers
- Anyone who want to learn about Full Stack Web Development
- Anyone who want to learn MERN stack
- Anyone who wants to learn, How to build real world project like: Ecommerce
Deep Learning for Beginners in Python: Work On 12+ Projects
Tuesday, November 23, 2021
Free Coupon Discount - Deep Learning for Beginners in Python: Work On 12+ Projects, Work On 12+ Projects, Deep Learning Python, TensorFlow 2.0, Neural Networks, NLP, Data Science, Machine Learning, More !
Created by Vijay Gadhave
Students also bought
- Natural Language Processing (NLP) with Python: 2020
- Machine Learning using Python : Learn Hands-On
- Real-World Machine Learning Projects with Scikit-Learn
- Data Science for AI and Machine Learning Using Python
- Data Science Projects with Python
- Speech Recognition A-Z with Hands-on
Preview this Udemy Course GET COUPON CODE
Description
The Artificial Intelligence and Deep Learning are growing exponentially in today's world. There are multiple application of AI and Deep Learning like Self Driving Cars, Chat-bots, Image Recognition, Virtual Assistance, ALEXA, so on...
With this course you will understand the complexities of Deep Learning in easy way, as well as you will have A Complete Understanding of Googles TensorFlow 2.0 Framework
TensorFlow 2.0 Framework has amazing features that simplify the Model Development, Maintenance, Processes and Performance
In TensorFlow 2.0 you can start the coding with Zero Installation, whether you’re an expert or a beginner, in this course you will learn an end-to-end implementation of Deep Learning Algorithms
List of the Projects that you will work on,
Part 1: Artificial Neural Networks (ANNs)
Project 1: Multiclass image classification with ANN
Project 2: Binary Data Classification with ANN
Part 2: Convolutional Neural Networks (CNNs)
Project 3: Object Recognition in Images with CNN
Project 4: Binary Image Classification with CNN
Project 5: Digit Recognition with CNN
Project 6: Breast Cancer Detection with CNN
Project 7: Predicting the Bank Customer Satisfaction
Project 8: Credit Card Fraud Detection with CNN
Part 3: Recurrent Neural Networks (RNNs)
Project 9: IMDB Review Classification with RNN - LSTM
Project 10: Multiclass Image Classification with RNN - LSTM
Project 11: Google Stock Price Prediction with RNN and LSTM
Part 4: Transfer Learning
Part 5: Natural Language Processing
Basics of Natural Language Processing
Project 12: Movie Review Classifivation with NLTK
Part 6: Data Analysis and Data Visualization
Crash Course on Numpy (Data Analysis)
Crash Course on Pandas (Data Analysis)
Crash course on Matplotlib (Data Visualization)
With this course you will learn,
1) To buils the Neural Networks from the scratch
2) You will have a complete understanding of Artificial Neural Networks, Convolutional Neural Networks and Recurrent Neural Networks
3) You will learn to built the neural networks with LSTM and GRU
4) Hands On Transfer Learning
5) Learn Natural Language Processing by doing a text classifiation project
6) Improve your skills in Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib
So what are you waiting for, Enroll Now and understand Deep Learning to advance your career and increase your knowledge !
Regards,
Vijay Gadhave
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Computer Vision Course
Computer Vision Course - Learn Deep Learning & Computer Vision with Python, Tensorflow 2.0, OpenCV, FastAI. Object Detection & GAN and much more!
What you'll learn
- Using Latest Tools & Techniques in Deep Learning & Computer Vision
- Learning how to used the latest Tensorflow 2.0
- How to apply Transfer Learning, Ensemble Learning, using GPUs & TPUs
- How to work & win Kaggle Competitions
- Learning to use FastAI
- How to use Generative Adversarial Networks
- How to use Weights & Biases for recording Experiments
- Learning to use Detectron2 for Object Detection
- Making Machine Learning Web Application from Scratch
- Learn how to use OpenCV for Computer Vision
- How to make Real World Applications & Deploy into Cloud
- Learning Techniques like Object Detection, Classification & Generation
- Learning how to use Heroku for deploying ML models
- Working on Kaggle Competitions & Kaggle Kernels
- Exploring & Visualizing Datasets using popular libraries like Matplotlib & Plotly.
- Learinng how to use libraries like Pandas, Sklearn, Numpy
- Creating Advance Data Pipelines using Tensorflow for training Deep Learning Models
- Setting up Environment & Project for Deep Learning & Computer Vision
Requirements
- Basic Python programming knowledge
- A Computer with Internet Connection
- All tools used in this course are free to use
Description
This Brand New and Modern Deep Learning & Computer Vision Course will teach you everything you will need to know to learn the fundamentals of computer vision.
Deep Learning & Computer Vision is currently one of the most increasing fields of Artificial Intelligence and Companies like Google, Apple,
Facebook, Amazon are highly investing in this field. Deep Learning & Computer Vision jobs are increasing day by day & provide some of the highest paying jobs all over the world.
If We Want Machines to Think, We Need to Teach Them to See.-Fei Fei Li, Director of Stanford AI Lab and Stanford Vision Lab
Computer Vision allows us to see the world & process digital images & videos to extract useful information to do a certain task from classification, object detection, and much more. Python is one of the most popular used programming language in Deep Learning and Computer Vision.
All the tools, techniques & technologies used in this course -
Learning Computer Vision & Deep Learning Fundamentals
Setting up Anaconda, Installing Libraries & Jupyter Notebook
Learning fundamentals of OpenCV & Numpy - Reading images, Colorspaces, Drawing & Callbacks
Advanced OpenCV - Image Preprocessing, Geometrical transformations, Perspective transformations & affine transformations, image blending & pyramids, image gradients & thresholding, Canny Edge Detector and contours
Working with videos in OpenCV - Using webcam, Haar Cascades & Object Detection, Lane Detection
Deep Learning & How Neural Network Works? - Artificial neural networks, Convolution Neural Networks & Transfer Learning
Image Classification - Plant leaf Classification
Working on very recent Kaggle Competitions
Using Google Colab & Kaggle Kernels
Using the latest Tensorflow 2.0 & Keras
Using Keras Data Generators & Data Argumentation
Using Transfer Learning & Ensemble learning
Using State of The Art Deep Learning Models
Using GPU & TPU for Model Training
Hyperparameter Tuning
Using Weights & Biases for recording Deep Learning experimentations
Saving & Loading Models
Creating a Weights & Biases Report & Showcasing the Project!
Object Detection - Wheat heads Detection
Working on Kaggle Competitions, again!
Using Facebook's Detectron2 for Object Detection
Creating COCO Dataset from scratch
Training Faster RCNN Model and Custom Weights & Biases callback
Using Retinanet
Saving & Loading Detectron2 models
Generative Adversarial Networks - Creating Fake Leaf Images
Learning How Generative Adversarial Networks works
Using FastAI
Creating & Training Generative Adversarial Networks
Making Fake Images using GAN
Making ML Web Application
Getting started with Streamlit
Creating an ML Web Application from scratch using Streamlit
making a React Web Application
Deploying ML Applications
Learning how to use Cloud Services to Deploy Models & Applications
Using Heroku
Learning how to Open Source Projects on GitHub
How to showcase your projects to impress boss & employees & Get Hired!
A lot of bonus lectures!
This is what included in the package
All lecture codes are available for downloadable for free
110+ HD video lectures ( over 50 more to come very soon! )
Free support in course Q/A
All videos with English captions available
This course is for you if..
... you want to learn the Latest Tools & Techniques used in Deep Learning & Computer Vision
... you want to get more experience to Win Kaggle Competitions
... you want to get started with Computer Vision to become a Computer Vision Engineer
.. you are interested in learning Image Classification, Object Detection, Generative Adversarial Networks, Making & Deploying Machine Learning Applications
Who this course is for:
- You want to become a Computer Vision Engineer & Get Hired
- Anyone who want to learn latest tools & techniques used in Computer Vision
- You are already a Programmer and what to extend your skills by learning Computer Vision
- Who want to learn new Tools & Techniques used in Computer Vision
- You want to get more experience for winning Kaggle Competitions
Python and Django Full Stack Web Developer Bootcamp
Sunday, November 21, 2021
Python and Django Full Stack Web Developer Bootcamp, Learn to build websites with HTML , CSS , Bootstrap , Javascript , jQuery , Python 3 , and Django! | BESTSELLER, Created by Jose Portilla, English [Auto-generated], French [Auto-generated], 9 more
PREVIEW THIS COURSE - GET COUPON CODE
What you'll learn
- Create a fully functional web site using the Full-Stack with Django 1.11
- Learn how to use HTML to create website content
- Use CSS to create beautifully styled sites
- Learn how to take advantage of Bootstrap to quickly style sites
- Use Javascript to interact with sites on the Front-End
- Learn how to use jQuery to quickly work with the DOM
- Understand HTTP requests
- Create fantastic landing pages
- Learn the power of Python to code out your web applications
- Use Django as a back end for the websites
- Implement a full Models-Views-Templates structure for your site
Description
Welcome to the Python and Django Full Stack Web Developer Bootcamp! In this course we cover everything you need to know to build a website using Python, Django, and many more web technologies!
Whether you want to change career paths, expand your current skill set, start your own entrepreneurial business, become a consultant, or just want to learn, this is the course for you!
We will teach you the latest technologies for building great web applications with Python 3 and Django! But we don't just teach that, we also teach the Front End technologies you need to know, including HTML, CSS, and Javascript. This course can be your one stop shop for everything you need! It will serve as a useful reference for many of your questions as you begin your journey in becoming a web developer!
This course is designed so that anyone can learn how to become a web developer. We teach you how to program by using HD Video Lectures, Walkthrough Code Projects, Exercises, Concept Presentation Slides, Downloadable Code Notes, Reading Assignments, and much more!
Here is just a small sampling of the topics included in this course:
HTML5
CSS3
Javascript
jQuery
Bootstrap 3 and 4
Document Object Model
Python
Django Basics
Django Templates
Django Forms
Django Admin Customization
ORM
Class Based Views
REST APIs
User Authentication
and much,much more!
You will also get access to our online community of thousands of students, happy to help you out with any questions you may have! Any questions, feel free to send me a message here on Udemy and connect with me on LinkedIn, check out my profile for other courses.
We also have a 30-day money back guarantee, so you can try out the course for an entire month, risk-free!
Always keep learning!
Jose
30 Real World Data Science & Machine Learning Projects 2021
Friday, November 19, 2021
30 Real World Data Science & Machine Learning Projects 2021 - Practical Data Science Course: Learn To Build Machine Learning, Data Science Projects & Case Studies With Python
What you'll learn
- Master Machine Learning on Python
- Learn to perform Classification and Regression modelling
- Learn best practices when it comes to Data Science Workflow
- How to improve your Machine Learning Models
- Create supervised machine learning algorithms to predict classes.
- Learn best practices for real-world data sets.
- Learn how to use Scikit-learn to apply powerful machine learning algorithms.
Description
Resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. Things like growing volumes and varieties of available data, computational processing that is cheaper and more powerful, and affordable data storage.
All of these things mean it's possible to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results – even on a very large scale. And by building precise models, an organization has a better chance of identifying profitable opportunities – or avoiding unknown risks.
Most industries working with large amounts of data have recognized the value of machine learning technology. By gleaning insights from this data – often in real time – organizations are able to work more efficiently or gain an advantage over competitors.
Financial services
Banks and other businesses in the financial industry use machine learning technology for two key purposes: to identify important insights in data, and prevent fraud. The insights can identify investment opportunities, or help investors know when to trade. Data mining can also identify clients with high-risk profiles, or use cyber surveillance to pinpoint warning signs of fraud.
Government
Government agencies such as public safety and utilities have a particular need for machine learning since they have multiple sources of data that can be mined for insights. Analyzing sensor data, for example, identifies ways to increase efficiency and save money. Machine learning can also help detect fraud and minimize identity theft.
Health care
Machine learning is a fast-growing trend in the health care industry, thanks to the advent of wearable devices and sensors that can use data to assess a patient's health in real time. The technology can also help medical experts analyze data to identify trends or red flags that may lead to improved diagnoses and treatment.
Retail
Websites recommending items you might like based on previous purchases are using machine learning to analyze your buying history. Retailers rely on machine learning to capture data, analyze it and use it to personalize a shopping experience, implement a marketing campaign, price optimization, merchandise supply planning, and for customer insights.
Oil and gas
Finding new energy sources. Analyzing minerals in the ground. Predicting refinery sensor failure. Streamlining oil distribution to make it more efficient and cost-effective. The number of machine learning use cases for this industry is vast – and still expanding.
Transportation
Analyzing data to identify patterns and trends is key to the transportation industry, which relies on making routes more efficient and predicting potential problems to increase profitability. The data analysis and modeling aspects of machine learning are important tools to delivery companies, public transportation and other transportation organizations.
Who this course is for:
- Beginners in data science
Python 3 Programming: Beginner to Pro Masterclass
Free Coupon Discount - Python 3 Programming: Beginner to Pro Masterclass, Learn Python 3 with more than 100 Practical Exercises and 20 Hands-on Practical Projects | Created by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, Mitchell Bouchard, SuperDataScience Team
Students also bought
- Tensorflow 2.0: Deep Learning and Artificial Intelligence
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- Bayesian Machine Learning in Python: A/B Testing
- Building Machine Learning Web Apps with Python
Preview this Udemy Course GET COUPON CODE
Description
We are on a mission to create the most complete Python programming guide in the World.
From Python basics to techniques used by pros, this masterclass provides you with everything you need to start building and applying Python.
“Python Beginner to Pro Masterclass” is our flagship Python course that delivers unique learning with 3 immersive courses packed into 1 easy-to-learn package:
First, prepare yourself by learning the basics and perfect your knowledge of the language with a beginner to pro Python programming course.
Next, build on your knowledge with a practical, applied and hands-on Python course with over 20 real-world applications problems and 100 coding exercises to help you learn in a practical, easy and fun way. These will be invaluable projects to showcase during future job interviews!
Finally, push your boundaries with a data science and machine-learning course covering practical machine learning applications using Python. Dive into real-life situations and solve real-world challenges.
So, why is Python the golden programming language these days? And what makes it the best language to learn today?
Python ranks as the number one programming language in 2018 for five simple reasons that are bound to change the shape of your life and career:
(1) Easy to learn: Python is the easiest programming language to learn. In fact, at the end of this single course, you’ll be able to master Python and its applications regardless of your previous experience with programming.
(2) High Salary: Did you know that the average Python programmer in the U.S. makes approximately $116 thousand dollars a year? With “Python 3 Beginning to Pro Masterclass” you’re setting yourself for up for increased earning potential that can only rise from here.
(3) Scalability: It’s true, Python is easy to learn. But it’s also an extremely powerful language that can help you create top-tier apps. In fact, Google, Instagram, YouTube, and Spotify are all built using Python.
(4) Versatility: What’s more, Python is by far the most versatile programming language in the world today! From web development to data science, machine learning, computer vision, data analysis and visualization, scripting, gaming, and more, Python has the potential to deliver growth to any industry.
(5) Future-proof Career: The high demand and low supply of Python developers make it the ideal programming language to learn today. Whether you’re eyeing a career in machine learning or artificial intelligence, learning Python is an invaluable investment in your career.
Who this course is for:
Anyone who wants to learn Python.
Beginners who have just started to learn Python
Professionals who want to learn Python through Real World Applications
Professionals who want to obtain particular skill, such as Web Scraping, Working With Databases, Build Websites, etc
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