Top 50 Free & Discounted Udemy Courses in Development Category

Top 50 Free & Discounted Udemy Courses in Development Category

Vue.js + Google Maps API for Beginners

Build a User Location Detector App Using HTML5 Geolocation & Geocoding APIs

Create a Close Buy App Using Places API - Nearby Search

Place Details

Understand basics of the VueJs - Components



Learn How Geocoding API

Places API Work

Able to Design professional UI Quickly Using Semantic UI CSS Framework

tutorials and teach you how to build a couple of location-based apps.

Our Vue.js & Google Maps API for Beginners course teaches you how to get started with Vue.js and Google Maps API to build location-based apps faster with a little bit of HTML and JavaScript knowledge.

By the end of this course, you will be fluently coding in Vue.js and utilizing the Google Maps Platform to make your own location-based apps.

Who this course is for:

  • If you are an absolute beginner to Vue.js but know a little bit of HTML and JavaScript, then take this course.

  • If you are a Front-end or JavaScript Developer, then take this course to get up to speed quickly with building location-based apps using Google Maps API.

  • If you are a Vue.js developer and curious to know how the Google Maps Platform works, then this course will be worth taking.


Get This Course Free udemy course: Make your own Netflix clone website 101

Make your own Netflix clone website 101

making a clone website like Netflix

Sharing movies & tv series online

making extra money every month

p prices, get the script and upload it into the Cpanel, creating database & user, give the permissions or the privilege to the user. You will understand how to configure ad customize the clone website like (add pages, change the backgrounds ... etc). And i will help you make a payments system to help yourself make extra money from the membership options. Before the end of the course you will be able to make a full Netflix clone website and start sharing movies,Tv series, actors, genre and more ... 


Get This Course Free udemy course: Complete course of Java Server Pages (JSP) Programming

Complete course of Java Server Pages (JSP) Programming

Java based web application development using Jave Server Pages (JSP) Programming

va Server Pages. Here, we will focus more on implementation and provided theory and source code with live demonstration to make concepts and fundamentals clear. Here, we will be promising to provide you more upcoming interesting and important educational announcements to practice project for hands-on experience. In addition, we will be providing some experienced technical interview tips and web component application technical professional certifications information. We can provide some sample practice  certification question upon request.  Thanks for enrolling this course. Good luck

Let's make coding fun!

Good Luck!


Get This Course Free udemy course: The ABCD of Blogging

The ABCD of Blogging

What is a Blog?

The paper work before planning a blog.

Basic brainstorming when you are planning for Blog writing.

Learn to decide your Niche

Blog Name and type.

Understand the basic anatomy of the blog writing.

Earn through Blogging

Prepare Subconsciously for Blog writing with NLP guided Visualizations.

most of them are BLOGS... And the more the blog is used, more it will be liked and shared and you will start getting invitations to write more.

Do you feel you have some abstract knowledge about your field that can be actually helpful to others? Can it be value added information? Can you express it in a way that others would love to read? If your answer is 'YES' for all these questions, the world is waiting for you.

Start sharing your knowledge through blogging. Grow as you develop yourselves too....


Get This Course Free udemy course: Python 3.7 Beginner's Bootcamp 2020

Python 3.7 Beginner's Bootcamp 2020

Learn Python 3.7 concepts and features

Learn Python 3 basic and advance topics

Assignments to test your Python grasping power

Learn Python Object Oriented Programming

reer Opportunities in Python are growing in numbers across the world. Not only small companies but even top companies are using Python as their business application development. which includes Google, Facebook, IBM, Nokia and many more..

This course will teach/give you

  • Complete basics of Python from level zero.

  • Assignments to test your grasping power.

    ***NOTE: This course is still being developed to give you 10+ hours of video content.***

****ENROLL NOW ****

Below are the topics covered in the course:

  • Python Installation

  • Running Python Code

  • Variables

  • Data types

  • Operators

  • Lists

  • Tuples

  • Strings

  • Sets

  • Dictionaries

  • Conditional statements

  • Loops

  • Custom Functions

  • Modules

  • Packages

  • File Handling

  • Errors and Exceptions

  • Handling Exceptions

  • Database Expressions

  • Regular Expressions

.........and many Coding Assignments.

You will also get:

  • 30 day money back guarantee

  • Lifetime Access

****ENROLL NOW ****

To your Freedom and Success!!

Happy Learning!!


Get This Course Free udemy course: Python 3 Crash Course

Python 3 Crash Course

Installing Python

Data Types



Functions & Booleans

Comparison Operators

Statesments In python

Object Oriented Programming

can do all of this using python! This course will teach you some of the most essential basics of python.If you’re looking to learn Python for the very first time or need a quick brush-up, this is the course for you!

Python has rapidly become one of the most popular programming languages around the world. Compared to other languages such as Java or C++, Python consistently outranks and outperforms these languages in demand from businesses and job availability. The average Python developer makes over $100,000 - this number is only going to grow in the coming years.Designed for the students with a basic understanding of Python, this training opportunity will focus more on practical video lectures.


Get This Course Free udemy course: Learn Web Development From Scratch: Hands On Practical Guide

Learn Web Development From Scratch: Hands On Practical Guide

Setting Up Environment

Basics Of HTML

Advanced HTML

Basics Of CSS3

Advanced CSS3

Basics Javascript & Jquery

Advanced Javascript & Jquery

Basics Bootstrap

ent full-stack web developer in a matter of weeks.


  • Anyone who is curious about programming

  • Entrepreneurs

  • Those looking for a career change

  • Serious coders & hobbyists

  • Students & teenagers

  • Anyone who wants to learn web development


Get This Course Free udemy course: The Ultimate Guide to Creating Savegames in Unity

The Ultimate Guide to Creating Savegames in Unity

Create simple Savegames in Unity

Create more complex Savegames in Unity

Serialize Data

Encrypt Data

ll teach you best practices for the most basic savegame-solutions like PlayerPrefs, but we will also handle some more advanced topics like Json and Encryption.

In this course you will:

  • Save and load the Gamestate

  • Save/Load simple Data with Playerprefs

  • Create your own Save-Files with Streamwriter

  • Create unreadable Savegames with Binaryformatter

  • Create advanced up- and downward-compatible Savegame-Solutions with Json

  • Encrypt your Savegames

This course is very project-based and practical, so you will implement the concepts directly in exercises.

For each Concept you will be challenged to implement it yourself, but if you don't feel up to the task you will also be shown a well explained step-by-step guide how to implement it.

The course also features several Demo-Projects, where you can look up best practice implementations.

Why learn from me?

I have been teaching game-programming for more than 5 years now and as a result I have plenty of experience in what works and what doesn't when it comes to teaching programming. Also I am a firm believer, that you can only learn the high craft (some might even say art) of programming, by practicing it.

Who is the target Audience?

  • Unity Developers who want to create Simple Savegames

  • Unity Developers who want to create more sophisticated encrypted Savegames

  • Programmers who want to improve their Skills in the Unity3D - Engine

Become a better Programmer, now! I'll meet you inside the course!


Get This Course Free udemy course: Hands-on Tableau-10: Data Science Case Studies In Tableau

Hands-on Tableau-10: Data Science Case Studies In Tableau

Data Visualization

Connect Tableau to various Datasets: Excel and CSV files

Create various plots

hase behavior, sales trends, or production bottlenecks.

Tableau is an interactive, self-service reporting and analytics tool that enables faculty and staff to integrate and combine data from multiple sources into visualizations and be accessed in a single desktop environment using Tableau Desktop or through a shared dashboard


Get This Course Free udemy course: Java Programming: Complete Beginner to Advanced

Java Programming: Complete Beginner to Advanced

Learn core Java skills from complete beginner to advanced features

programming languages used to create Web applications and platforms. It was designed for flexibility, allowing developers to write code that would run on any machine.

So it’s your time now to take advantage of a loads of jobs and freelance opportunities that are available for java programmers out there.

This course is provided by CodeIn Academy Instructors who are Oracle Certified professionals with many years’ experience in java programming

The course is very comprehensive and will be constantly updated. Once you have gone through this course you will be able to understand Java 8 features very easily. So, this course covers each topic in details and is focused to break down topics with simplified examples. Thus, it is for anyone who wants to learn java programming and no previous programming experience is required.

Enroll in this course now because its your time to get these highly paid and very on-demand skills.


Get This Course Free udemy course: Unreal Engine 4 - Create a Standard Megascans Shader

Unreal Engine 4 - Create a Standard Megascans Shader

Understanding the logic between Master Materials and Instances

Create material functions

Optimize your materials

Create combined textures

Import and setup LODs (Level of Details)

tandard shader for Quixel Megascans.

You will be able to apply this material to any rocks, branches, trunks, stumps, debris, mushrooms, assemblages but also any other 3d models available in the library (except "Plants" type models).


Get This Course Free udemy course: Google Sites Google Apps Script File Sharing Mini Web App

Google Sites Google Apps Script File Sharing Mini Web App

How to apply Google Apps Script

Creating a web app with Google Apps Script

Connecting GSuite Products together to make amazing applications and save time

ile notify via email.

Step by step of building web applications that make use of GSuite connecting varies Classes together to rapidly build powerful applications.

JavaScript is a prerequisite to this course - Prior coding experience is required!!!!

Source code is included so that you can build your own version of the application.

Course covers applying Google Script Code - JavaScript and HTML to build a web application that can upload files into Google Drive.  Also track uploaded file details within a Spreadsheet while sending notification emails as new content is uploaded.

Course cover coding relevant to the project - SCOPE OF THIS COURSE IS BUILDING THE WEB APP - and will not cover basics of coding using JavaScript.

Lessons and Learning Objective for this course

  • Google Script editor and how to setup a Web App

  • Getting a web app and how to develop and update code

  • Setting up Google Sites page to host your Google Scripts Web App

  • Frontend client side code to upload file and send data to Google Scripts Server Side

  • Handling of data with Google Scripts - use of Utilities Class to manage file data

  • Creating Blob and copying file blob to Google Drive

  • Selecting specific Drive using ID value

  • Getting File Object details and saving to Spreadsheet

  • Selecting of files on the drive getting file object details from Google Script

  • Sending Email on File Upload

Taught by an instructor with many years of web development experience ready to help you learn about Google Apps Script and how you can write code to create custom applications. 

You have nothing to lose, start building your application today.


Get This Course Free udemy course: Introduction to AI, Machine Learning and Python basics

Introduction to AI, Machine Learning and Python basics

Learn to understand between Machine Learning

Deep learning and Neural networks

Learn where AI and Machine learning algorithms are used today

Learn basics of Python programming

Build simplest machine learning models in Excel

os and images on social networks, and even when we drive a car or use our smartphones. AI is widely used in medicine, sales forecasting, space industry and construction.

Since we are surrounded by AI technologies everywhere, we need to understand how these technologies work. And for such understanding at a basic level, it is not necessary to have a technical or IT education.


In this course, you will learn about the fundamental concepts of Artificial Intelligence and Machine learning. You will get acquainted with their main types, algorithms and models that are used to solve completely different problems. We will even create models together to solve specific practical examples in Excel - for those who do not want to program anything. And for those who want to get acquainted with Python , a programming language that solves more than 53% of all machine learning tasks today, in this course you will find lectures to familiarize yourself with the basics of programming in this language.


This course may become a kind of springboard for your career development in the field of AI and Machine learning. Having mastered this short course, you will be able to choose the particular area in which you would like to develop and work further. It is worth mentioning that today, AI and Machine Learning specialists are among the highest paid and sought after on the market (according to various estimates, there are about 300,000 AI experts on the global market today, while the demand for them is several million).


So why not reinforce your resume with a certificate from Udemy, the largest international educational platform , that you have completed this course on Artificial Intelligence and Machine Learning, and the basics of Python programming .


After completing this course, you will be able to communicate freely on topics related to Artificial Intelligence, machine and deep learning, and neural networks. You will be able to analyze and visualize data, use algorithms to solve problems from different areas.


This course will be regularly supplemented with new lectures and after enrolling in it you will have full access to all materials without any restrictions. Spend a few hours studying this course to get new or improve existing skills and broaden your horizons using the acquired knowledge.

See you inside the course!



Get This Course Free udemy course: C++ Crash Course

C++ Crash Course

Basics Of C++ & Installation


Data Types & Variables

Classes & Functions

If-Else Statements

Arrays & Strings

Web Programming In C++

it is also a very relevant language. If you go to GitHub you will see that there are a huge number of active C++ repositories and C++ is also extremely active on stack overflow.

There are many, many leading software titles written entirely or partly in C++. These include the Windows, Linux and Mac OSX operating systems!

Many of the Adobe products such as Photoshop and Illustrator, the mySQL and MongoDB database engines, and many many more are written in C++.


Get This Course Free udemy course: WordPress Fundamentals 2020

WordPress Fundamentals 2020

We shall explore the main features of WordPress.

You will learn how to install WordPress.

You will be walked through the Admin dashboard and understand what it can do.

You will learn how to write your first post using blocks.

You will learn how to add categories and tags to your posts and understand why they are important for search engines.

You will learn how to write your first page and understand why these are different from posts.

We shall explore WordPress plugins and how they can enhance your website to suit your needs.

We shall explore WordPress themes and how to make your site look and feel different.

You will understand why it is important to make sure your site can be seen on desktop


tablet or phone.

We shall explore Menus & Widgets. Personalising your website to help your audience find the content they need.

You will how to learn how to configure your WordPress website for speed

security and privacy.

Bonus: You will learn how to maintain your website going forward.

g, a portfolio, a personal website, a project website, some sort of side-hustle hobby business, etc.

We'll run through what everything means and then work on:

  • Making a post

  • Creating an About page

  • Making a Homepage

  • Creating a Contact page

Simple and straightforward lessons to help get you up and running as quickly a possible.


Get This Course Free udemy course: How To Make A Home Care Agency Website With WordPress 2020

How To Make A Home Care Agency Website With WordPress 2020

This video is for you when you want to create a Home Care Agency website quickly

bsite can be adjusted. In this tutorial I show you how to make a Home Care Agency website by importing pre-made templates, so you can focus on creating a Home Care Agency website rather than learning every detail in the process.

Good luck!!


Get This Course Free udemy course: JavaScript HTML CSS Project make a Quiz Tutorial

JavaScript HTML CSS Project make a Quiz Tutorial

Know how JavaScript works

Build dynamic JavaScript Applications

Build a quiz from start to finish

Create your own JavaScript code

Add JavaScript to a website

How JavaScript works in a browser

know JavaScript syntax and how to use it

t dynamic quiz incorporating CSS HTML JavaScript and Twitter Bootstrap to build a web project. Learn JavaScript from a real world example.

Learn to make Quiz using Javascript. We will walk you through all the basic building blocks of JavaScript.

Web Development project create a JavaScript Quiz. Using CSS, HTML, JavaScript, Twitter Bootstrap.

This JavaScript course is exclusive on Udemy we build web development courses. Learn to create DYNAMIC INTERACTIVE web pages using JAVASCRIPT.

Everything you need to learn about JavaScript is provided within this course.

  • exclusive download PDF resource ebook
  • no wasted time watching someone type
  • quick lessons get right to the point
  • fully covered topics with real world examples
  • source files downloadable to work along
  • challenges and lessons
  • 30 day money back guarantee
  • new course material added regularly
  • trusted name in education since 2002
  • full HD easy to read source coding

Learn how Javascript works and it's fundamental concepts. Learn to build your own Javascript code to make you website interactive.


Get This Course Free udemy course: Complete CSS3 and Bootstrap Course: Beginning to Advanced

Complete CSS3 and Bootstrap Course: Beginning to Advanced

Will able to code responsive web using CSS

Will able to code responsive web using Bootstrap

Will be able to design & develop responsive web page

on and practical experience on detailed CSS3 and Bootstrap and more.

Contents of this tutorial # 

Interactive CSS3: Basics

  • What is CSS? Why we need it?

  • What's new in CSS3

  • CSS Selectors, properties and attributes

  • ID Selectors

  • Class Selectors

  • Element Selectors

  • All Selectors

  • Inline style sheets

  • External Style sheets

Interactive CSS3: Advanced

  • The Box model

  • Adding Color

  • Working with fonts

  • Background images

  • Styling ID tags

  • Float and Clear

  • Block and inline elements

  • Positioning

  • Adding the elements

Interactive Bootstrap: Basic

  • Why Bootstrap? 

  • Downloading Bootstrap

  • Adding Bootstrap in your site

  • Creating navigation 

  • Styling images 

  • Creating the footer 

  • Adding styled buttons

Interactive Bootstrap: Advance

  • Adding Google Maps

  • Adding an image carousel

  • Adding a contact form

  • Creating a complete web page: Part 1

  • Creating a complete web page: Part 2

  • Creating a complete web page: Part 3

Learning CSS3 and Bootstrap is one of the fastest ways to improve your career, especially on web design and development. 

Hope this course will be used as a helping hand for your prospective career. Please dig on free preview videos for more information.


Get This Course Free udemy course: Python Programming & Software Design For Absolute Beginners

Python Programming & Software Design For Absolute Beginners

Python Programming

Software Design - Flowcharts

Basic Sorting algorithms

ced level. You will learn about Software Design as well. eg: Flow charts, pseudacodes, algorithms

By the end of these videos, you will get the understanding of following areas the 

  • Python Programming

    Setting up the environment

    Python For Absolute Beginners : Setting up the Environment : Anaconda

    Python For Absolute Beginners : Variables , Lists, Tuples , Dictionary

  • Boolean operations

  • Conditions , Loops

  • (Sequence , Selection, Repetition/Iteration)

  • Functions

  • File Handling in Python

  • Flow Charts

  • Algorithms

  • Modular Design

  • Introduction to Software Design - Problem Solving

    Software Design - Flowcharts - Sequence

    Software Design - Modular Design

    Software Design - Repetition

    Flowcharts Questions and Answers # Problem Solving


Get This Course Free udemy course: Modern Javascript Crash Course

Modern Javascript Crash Course

let var and const

switch case

template literal

arrow function


spread operator


primitive vs reference

import and export

array function

iterate through object and array [for\of for\in]

building one large project this course is focused on learning Javascript and what the code you are writing does. I focus on simplifying and explaining in depth every complex Javascript topic so you have a deep understanding of something that you may miss out.

In order to accomplish such a highly focused all unrelated concepts are kept to a bare minimum. This means no extra time will be wasted on building out huge CSS files or writing html, and instead every minute of this course will be focused solely on learning Javascript. Because of the focused nature of this course you will learn the important things about Javascript in a shorter time.

Why Javascript important? Javascript is important for you not just frontend but also backend nowadays. Angular,React and Vue are very popular framework, they not just can build the website, but also build apps for iOS and Android. Nodejs  is also an open source server environment which allow to use Javascript on server side. So, no matter you are a frontend developers or backend developer, this course is perfect for you.


Get This Course Free udemy course: MongoDB In Nutshell - Example driven Quick Start in MongoDB

MongoDB In Nutshell - Example driven Quick Start in MongoDB

MongoDB from basic to advanced

Learn MongoDB through hands-on practicals in most Simple way & Direct

Understand the basic concepts of MongoDB database

collection and document

Understand various forms of documents on the go as you learn how to access them and manipulate them

Understand CRUD operations

various functions and operators relevant to the CRUD operations

Extension of this course to include concepts like cursor methods






Several lessons to be added every week

but here to start with most basic operations the course has been launched

e seeking job in the IT field can ignore it. The developers in MongoDB can claim high salary as there is a big gap between demand of MongoDB developers and their availability.

Optimization of the databases and complexities in accessing various forms of data have always been the challenges, the MongoDB has met them very easily with its simple to handle JSON document type model. The students of this course will just not be introduced to all the features of this incredibly complete database system but also learn all the techniques to make their applications developed with MongoDB to perform efficiently.

The course currently is not complete, but I promise it will keep on receiving addition of lesson every week to make it eventually complete and most comprehensive as my other courses did.


Get This Course Free udemy course: HTML & CSS Basics: Learn How to Build Your First Web Page

HTML & CSS Basics: Learn How to Build Your First Web Page

How to build a web page using HTML & CSS

HTML5 Semantic Elements

Take Your First Steps As a Front End Web Developer

Develop Websites Using Code Only

course, you will learn from the absolute beginning.

With our hands-on project, learning how to build a beautiful web page will be fun and intuitive to you.

Whether if you are aiming for a career as a web developer of you are a freelance web designer who want to master front end development, this course is what you're looking for.

Enroll now and let's start building amazing websites!


Get This Course Free udemy course: Finding Actionable Insights using Keras Autoencoders

Finding Actionable Insights using Keras Autoencoders

Learn to build a Keras Autoencoder using Python

Learn to extract actionable insights from data using unsupervised and semi-supervised modeling

Learn to find anomalies in data

Remember at the end of the day modeling and data science don't mean much if we can't extract actual insights to help guide our customers, our friends, the research community in the advancement of whatever it is they are after using data. Autoencoders can help you better understand your data, answer your questions, and even discover new ones! Please join me on this exciting adventure!


Get This Course Free udemy course: The Complete Angular Course: Zero to Hero

The Complete Angular Course: Zero to Hero

Basics and Setting Up Angular

Angular Modules

Data Binding & Controllers


Filtters & Services

Routing In Angular


Tables & Sql

Angular DOM

Animation & CLI In Angular

u will be at advanced level. This course contain Real-World examples and Hands On practicals. We will guide you step by step so that you can understand better. This course will allow you to work on the Real-World as a professional.This course teaches all about AngularJS. The course is designed for people having basic understanding of HTML,CSS & JavaScript. Learning AngularJS will surely be an added advantage for you as a web-developer.This course covers all the basic and advanced topics.


Get This Course Free udemy course: Algorithms for Job Interviews and Competitive Programming

Algorithms for Job Interviews and Competitive Programming

Find efficient solutions to algorithmic programming problems.

Analyse why code runs slowly and significantly improve run time.

Apply most important algorithms to solve real problems.

gorithmic thinking is by far the most effective way of rapidly improving as a developer and problems solver.
That's why I will teach you the most interesting and useful algorithms in this course. (I intentionally skipped sorting algorithms as they are so over-discussed and rarely need to be implemented by yourself).
For each algorithm or topic, I give a concise explanation, example and implementation outline. Then it's your turn to apply the new learned algorithm to solve real problems. For that, I hand-picked tasks from programming websites. When you struggle with an issue and need help, I answer every question and provide personal feedback for your problems.
Sign up now and begin a new chapter in your programming world.


Get This Course Free udemy course: Programlamaya Giriş İçin Temel Kurs

Programlamaya Giriş İçin Temel Kurs

Programlama için temel konuları öğreneceksiniz.

Nereden başlayacağınızı bilmiyorsanız

sizin için doğru bir yol haritası çizeceğiz.

Basitten zora algoritmalar öğreneceksiniz.

Atölye çalışmaları (workshop) yapacaksınız.

ramlama öğrenme serüveninin hemen başında pes etmektedir.

Bunun nedeni genellikle aşağıdakilerden biridir;

  • Nerden başlayacağını bilmemek.

  • Programlama dilleri arasında dönüp dolaşmak

  • Doğru kaynaktan öğrenmemek

Daha önce 130.000'den fazla kişiye online eğitim, 400'den fazla kuruma/şirkete kurumsal eğitim/danışmanlık vermenin tecrübesiyle hazırladığım bu ücretsiz eğitimde, programlamaya temeli sağlam bir giriş yapacaksınız.

Keyifli eğitimler dilerim.


Get This Course Free udemy course: Racket and ELM Programming for Beginners

Racket and ELM Programming for Beginners

You will have basic understanding of the Racket language.

Gain Functional Programming knowledge and skills

Would be able to start developing their own application in Elm.

s actively developed and maintained. Racket’s crown jewel is its macro system, which lets you freely extend the language. Racket consists of extensive standard library that gets your projects off the ground quickly. Racket runs on Linux, macOS, and Windows. Develop on one; deploy to all three.

Racket (formerly PLT Scheme) is a general purpose, multi-paradigm programming language in the Lisp-Scheme family. One of its design goals is to serve as a platform for language creation, design, and implementation.The language is used in a variety of contexts such as scripting, general-purpose programming, computer science education, and research.

Racket's core language includes macros, modules, lexical closures, tail calls, delimited continuations, parameters (fluid variables), software contracts, green and OS threads, and more. The language also comes with primitives, such as eventspaces and custodians, which control resource management and enables the language to act like an operating system for loading and managing other programs. Further extensions to the language are created with the powerful macro system, which together with the module system and custom parsers can control all aspects of a language. Unlike programming languages that lack macro systems, most language constructs in Racket are written on top of the base language using macros. These include a mixin class system, a component (or module) system as expressive as ML's, and pattern matching.

The feature that distinguishes Racket from other languages in the Lisp family is its integrated language extensibility. Racket's extensibility features are built into the module system to allow context-sensitive and module-level control over syntax

In this course we use DrRacket IDE , which is a graphical environment for developing programs using the Racket programming languages. DrRacket (formerly DrScheme) is widely used among introductory Computer Science courses that teach Scheme or Racket and is lauded for its simplicity and appeal to beginner programmers. The IDE was originally built for use with the TeachScheme! project (now ProgramByDesign), an outreach effort by Northeastern University and a number of affiliated universities for attracting high school students to computer science courses at the college level. It is the fastest way to get a sense of what the language and system feels like, even if you eventually use Racket with Emacs, vi, or some other editor.

Curious why Functional Programming is on the Rise? Do you wish there was a better option than JavaScript? Would you like to learn Elm or Functional Programming in general, but short on time?

If you answered yes, then this course is for you. 

Elm is very approachable, and is the best language to learn functional programming.

Elm is a functional programming language that compiles to JavaScript and runs in the browser. It is designed to be fun and friendly to use. Indeed, Elm upends the notion that functional programming is only accessible to mad scientists and academics. With its clean and readable syntax, world-class tooling, and friendly compiler, Elm is truly a delightful language.

The Elm Architecture helps you create complex, modular web apps with code that stays easy to maintain as you add features. Toss in great performance, no runtime exceptions, and JavaScript interop, and you've got a super-charged way to produce reliable, scalable, and maintainable web apps!

But what we love most about Elm is that you can actually build practical stuff with it quickly, which is exactly what we do in this course.

Elm compiles to JavaScript, so trying out Elm is easy. Convert a small part of your app to Elm and embed it in JS. No full rewrites, no huge time investment.

Unlike hand-written JavaScript, Elm code does not produce runtime exceptions in practice. Instead, Elm uses type inference to detect problems during compilation and give friendly hints. This way problems never make it to your users. There are several examples where companies are running applications on thousands of lines of Elm, and even after more than a year in production, it still has not produced a single runtime exception anywhere.

Elm has its own virtual DOM implementation, designed for simplicity and speed. All values are immutable in Elm, and the benchmarks show that this helps us generate particularly fast JavaScript code.

As Elm compiles to JavaScript, you can really use it to build very complicated single page applications. Eventually it’s possible to interface with other JavaScript code when necessary.  With Elm, cost savings are enormous. Elm component architecture allows problems to be solved encapsulated. No more side-effects. No more pages and page scripts. No more untraceable bugs because of changing pages.

Why should you consider using Elm?

Elm offers many benefits over JavaScript, which you’ll see in this course.

Benefits such as:

- Zero Runtime Exceptions

- Simplified Debugging

- Easy Refactoring

- Helpful Type System & Compiler

- Improved Productivity

- Inherently testable code

- Enforced Semantic Versioning

- and many more...

Can we ask a favor? Lot of efforts have gone into creating this course, and new videos would be continuously added. We would be very grateful if you would help spread the word about this course. Thanks!


Get This Course Free udemy course: Complete Python Course - Learn From Scratch

Complete Python Course - Learn From Scratch

Learn The Basics

Learn Advanced Methods

Step By Step Instructions So That You Can Go From Zero To Hero

A Complete Tutorial Explaining Everything You Need To Know

Real-World Examples With Hands On Tutorials

Get Answers To Your Every Single Questions

plete beginner and by the end of the course you will be at advanced level. This course contain Real-World examples and Hands On practicals. We will guide you step by step so that you can understand better. This course will allow you to work on the Real-World as a professional.

Enroll Now! Get the opportunity to learn from this complete course.


Get This Course Free udemy course: JavaScript Learn JavaScript Quick Course Beginners

JavaScript Learn JavaScript Quick Course Beginners

JavaScript Fundamentals

Applying JavaScript in a project Game

Core JavaScript Skills

epts quickly!  - Source code is included and its suggested that you try the code between the lessons to get more familiar with it.

Several students asked for a quick refresher on the core concepts of JavaScript - this course delivers just that.

Code samples and explanations on what the code does - and demos of the code in the browser.

Course covers

  • adding JavaScript to your HTML page

  • Running JavaScript code in your browser

  • Variables and assigning values

  • Functions and running blocks of code

  • Arrays and Objects - how to hold multiple values in one variable

  • Loops and iterations

  • Conditions and ternary operator to apply logic within coding

  • DOM - selection of elements from the webpage

  • DOM - adding event listeners like click to page elements

Create a GAME at the end - last 2 lessons you can apply what you learned to create a fun dice roll game.

Apply what you learned create your own version of the game

Dice rolling game see who wins - display results on the webpage.  Create dynamic page content and page interactions with event listeners.

Step by step learning - everything you need to create YOUR OWN VERSION OF THIS GAME!!!!

Taught by an instructor with many years of REAL WORLD web development experience - READY to HELP YOU LEARN

Fast friendly support is always available within the Q&A section

What are you waiting for - you have nothing to lose!!!

Source code is included step by step so you can copy the code try it out and get a feel for what JavaScript is doing.


Get This Course Free udemy course: Symfony 4 curso básico e intensivo

Symfony 4 curso básico e intensivo

Conocerás los conceptos básicos del framework Symfony.

Construirás una aplicación web real con Symfony 4.

Configurar tu IDE PhpStorm para un rendimiento óptimo con Symfony

Crear rutas y controladores



Configuración de assets con Symfony


como obtener los datos dinámicamente

barca las mejores prácticas en la programación orientada a objetos. No solo podrás construir algo potente, flexible y rápido: también dominarás algunos de los conceptos de programación más importantes y las mejores prácticas web de hoy.

  • Configuraremos nuestra app con Symfony 4

  • Configuraremos nuestro IDE (PhpStorm )para trabajar efectivamente con Symfony

  • Flex y las recipes

  • Rutas y controladores

  • Herramientas de consola

  • Twig

  • Instalaremos Doctrine

  • Crearemos tablas con Doctrine e importaremos datos

  • Querys con Doctrine para obtener el contenido dinámicamente

  • Como extra instaleremos el web debug toolbar o profiler!


Get This Course Free udemy course: JavaScript Bootcamp 2020

JavaScript Bootcamp 2020


Data Types & Variables


Objects & Classes

Conditionals & Loops


Booleans & Statements

Object Oriented Java Programming

hard to find one to start off with yet alone find a good course that will show you how to learn the language effectively.Because of all this I put together this free JavaScript basics course that will show you as a complete beginner how to begin creating programs using JavaScript.This course is created for anyone brand new to web development, or simply for those who know HTML, CSS, or any other programming language but have never worked with JavaScript before.


Get This Course Free udemy course: Learn Angular 2 from Zero to HERO Certified Course

Learn Angular 2 from Zero to HERO Certified Course

Understand and use Angular2's Component paradigm

Develop web applications using Angular 2

Understand TypeScript & Angular 2

mework that allows you to use HTML as your template language, and is JavaScript based. It has many high-power features like data binding and dependency injection that eliminates huge chunks of coding for the developer, making the process much more efficient and streamlined. It’s mostly maintained by Google and a wide network of users. Angular 2 is the latest version of the framework, first released in September 2014.

If you are looking to advance your skills with Angular 2, then look no further because this course is just right for you! Become an advanced programmer in Angular 2 in no time using this course which will continue to educate and motivate you along the way.

There is no reason to feel discouraged if you have no previous experience with Angular 2 since this course starts off with the mere basics. Even if you do have previous Angular 2 knowledge, this course covers interesting topics that you might have missed or would like to learn about. Each section of the course is related to the previous one in terms of utilizing what was already learned. All the covered subjects come with loads of examples to aid students in the process of learning and improving their skills. Upon the completion of this course, you should be able to write your own programs that have real-life applications, making it interesting for both beginner and advanced students alike.

What I think is the best about this course is that you can check out questions that were posted by other students as well as ask your own questions, and get answers to challenges you are currently facing in learning and using Angular 2. You get paid Angular 2 expert technical support in this course here to answer every single question you ask!


Get This Course Free udemy course: R Programming A-Z™: R For Data Science With Real Exercises!

R Programming A-Z™: R For Data Science With Real Exercises!

Learn to program in R at a good level

Learn how to use R Studio

Learn the core principles of programming

Learn how to create vectors in R

Learn how to create variables

Learn about integer



character and other types in R

Learn how to create a while() loop and a for() loop in R

Learn how to build and use matrices in R

Learn the matrix() function

learn rbind() and cbind()

Learn how to install packages in R

Learn how to customize R studio to suit your preferences

Understand the Law of Large Numbers

Understand the Normal distribution

Practice working with statistical data in R

Practice working with financial data in R

Practice working with sports data in R

en get overwhelmed. This course is different!

This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward.

After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.

This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises.

In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course!

I can't wait to see you in class,


Kirill Eremenko


Get This Course Free udemy course: Python for Statistical Analysis

Python for Statistical Analysis

Gain deeper insights into data

Use Python to solve common and complex statistical and Machine Learning-related projects

How to interpret and visualize outcomes

integrating visual output and graphical exploration

Learn hypothesis testing and how to efficiently implement tests in Python

statistics and data science.

  1. Learn through real-world examples: Instead of sitting through hours of theoretical content and struggling to connect it to real-world problems, we'll focus entirely upon applied statistics. Taking theory and immediately applying it through Python onto common problems to give you the knowledge and skills you need to excel.

  2. Presentation-focused outcomes: Crunching the numbers is easy, and quickly becoming the domain of computers and not people. The skills people have are interpreting and visualising outcomes and so we focus heavily on this, integrating visual output and graphical exploration in our workflows. Plus, extra bonus content on great ways to spice up visuals for reports, articles and presentations, so that you can stand out from the crowd.

  3. Modern tools and workflows: This isn't school, where we want to spend hours grinding through problems by hand for reinforcement learning. No, we'll solve our problems using state-of-the-art techniques and code libraries, utilising features from the very latest software releases to make us as productive and efficient as possible. Don't reinvent the wheel when the industry has moved to rockets.


Get This Course Free udemy course: Python A-Z™: Python For Data Science With Real Exercises!

Python A-Z™: Python For Data Science With Real Exercises!

Learn to program in Python at a good level

Learn how to code in Jupiter Notebooks

Learn the core principles of programming

Learn how to create variables

Learn about integer



string and other types in Python

Learn how to create a while() loop and a for() loop in Python

Learn how to install packages in Python

Understand the Law of Large Numbers

e and students often get overwhelmed. This course is different!

This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward.

After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.

This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises.

In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course!

I can't wait to see you in class,


Kirill Eremenko


Get This Course Free udemy course: Natural Language Processing (NLP) with BERT

Natural Language Processing (NLP) with BERT

Natural Language Processing

How to implement the BERT model

Sentiment Analysis

How to code on Python and Google Colab

t at the beginning. BERT stands for Bidirectional Encoder Representations from Transformers. Still none the wiser?

Let’s simplify it.

BERT is a deep learning framework, developed by Google, that can be applied to NLP.

Bidirectional (B)

This means that the BERT framework learns information from both the right and left side of a word (or token in NLP parlance). This makes it more efficient at understanding context.

For example, consider these two sentences:

Jimmy sat down in an armchair to read his favorite magazine.

Jimmy took a magazine and loaded it into his assault rifle.

The same word – two meanings, also known as a homonym. As BERT is bidirectional it will interpret both the left-hand and right-hand context of these two sentences. This allows the framework to more accurately predict the token given the context or vice-versa.

Encoder Representations (ER)

This refers to an encoder which is a program or algorithm used to learn a representation from a set of data. In BERT’s case, the set of data is vast, drawing from both Wikipedia (2,500 million words) and Google’s book corpus (800 million words).

The vast number of words used in the pretraining phase means that BERT has developed an intricate understanding of how language works, making it a highly useful tool in NLP.

Transformer (T)

This means that BERT is based on Transformer architecture. We’ll discuss this in more detail in the next section.

Why is BERT so revolutionary?

Not only is it a framework that has been pre-trained with the biggest data set ever used, it is also remarkably easy to adapt to different NLP applications, by adding additional output layers. This allows users to create sophisticated and precise models to carry out a wide variety of NLP tasks.


Get This Course Free udemy course: Modern Natural Language Processing in Python

Modern Natural Language Processing in Python

Build a Transformer

new model created by Google

for any sequence to sequence task (e.g. a translator)

Build a CNN specialized in NLP for any classification task (e.g. sentimental analysis)

Write a custom training process for more advanced training methods in NLP

Create customs layers and models in TF 2.0 for specific NLP tasks

Use Google Colab and Tensorflow 2.0 for your AI implementations

Pick the best model for each NLP task

Understand how we get computers to give meaning to the human language

Create datasets for AI from those data

Clean text data

Understand why and how each of those models work

Understand everything about the attention mechanism

lying behind the newest and most powerful NLP algorithms


Nowadays, the industry is becoming more and more in need of NLP solutions. Chatbots and online automation, language modeling, event extraction, fraud detection on huge contracts are only a few examples of what is demanded today. Learning NLP is key to bring real solutions to the present and future needs.

Throughout this course, we will leverage the huge amount of speech and text data available online, and we will explore the main 3 and most powerful NLP applications, that will give you the power to successfully approach any real-world challenge.

  1. First, we will dive into CNNs to create a sentimental analysis application.

  2. Then we will go for Transformers, replacing RNNs, to create a language translation system.

The course is user-friendly and efficient: Modern NL leverages the latest technologies—Tensorflow 2.0 and Google Colab—assuring you that you won’t have any local machine/software version/compatibility issues and that you are using the most up-to-date tools.


Get This Course Free udemy course: Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Master Machine Learning on Python & R

Have a great intuition of many Machine Learning models

Make accurate predictions

Make powerful analysis

Make robust Machine Learning models

Create strong added value to your business

Use Machine Learning for personal purpose

Handle specific topics like Reinforcement Learning

NLP and Deep Learning

Handle advanced techniques like Dimensionality Reduction

Know which Machine Learning model to choose for each type of problem

Build an army of powerful Machine Learning models and know how to combine them to solve any problem

s so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.

We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time we dive deep into Machine Learning. It is structured the following way:

  • Part 1 - Data Preprocessing
  • Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
  • Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
  • Part 4 - Clustering: K-Means, Hierarchical Clustering
  • Part 5 - Association Rule Learning: Apriori, Eclat
  • Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
  • Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP
  • Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
  • Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA
  • Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.

And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.


Get This Course Free udemy course: Logistic Regression Practical Case Study

Logistic Regression Practical Case Study

How to build a Logistic Regression model for a Real-World Case Study

Work on Google Colab

information for decision-making. Model performance depends on the ability of the radiologists to accurately identify findings on mammograms.

In statistics, the logistic model (or logit model) is used to model the probability of a particular class or event existing, such as pass/fail, win/lose, alive/dead, or healthy/sick. This can be extended to model several classes of events such as determining whether an image contains a cat, dog, lion, etc. Each object is detected in the image would be assigned a probability between 0 and 1, and the sum adding to one.

Logistic regression is a statistical model that, in its basic form, uses a logistic function to model a binary dependent variable, although many more complex extensions exist. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (a form of binary regression). Mathematically, a binary logistic model has a dependent variable with two possible values, such as pass/fail, which is represented by an indicator variable, where the two values are labeled "0" and "1". In the logistic model, the log-odds (the logarithm of the odds) for the value labeled "1" is a linear combination of one or more independent variables ("predictors"); the independent variables can each be a binary variable (two classes, coded by an indicator variable) or a continuous variable (any real value). The corresponding probability of the value labeled "1" can vary between 0 (certainly the value "0") and 1 (certainly the value "1"), hence the labeling; the function that converts log-odds to probability is the logistic function, hence the name. The unit of measurement for the log-odds scale is called a logit, from the logistic unit, hence the alternative names. Analogous models with a different sigmoid function instead of the logistic function can also be used, such as the probit model; the defining characteristic of the logistic model is that increasing one of the independent variables multiplicatively scales the odds of the given outcome at a constant rate, with each independent variable having its own parameter; for a binary dependent variable this generalizes the odds ratio.


Get This Course Free udemy course: Deep Learning A-Z™: Hands-On Artificial Neural Networks

Deep Learning A-Z™: Hands-On Artificial Neural Networks

Understand the intuition behind Artificial Neural Networks

Apply Artificial Neural Networks in practice

Understand the intuition behind Convolutional Neural Networks

Apply Convolutional Neural Networks in practice

Understand the intuition behind Recurrent Neural Networks

Apply Recurrent Neural Networks in practice

Understand the intuition behind Self-Organizing Maps

Apply Self-Organizing Maps in practice

Understand the intuition behind Boltzmann Machines

Apply Boltzmann Machines in practice

Understand the intuition behind AutoEncoders

Apply AutoEncoders in practice

g up millions of miles, IBM Watson is diagnosing patients better than armies of doctors and Google Deepmind's AlphaGo beat the World champion at Go - a game where intuition plays a key role.

But the further AI advances, the more complex become the problems it needs to solve. And only Deep Learning can solve such complex problems and that's why it's at the heart of Artificial intelligence.

--- Why Deep Learning A-Z? ---

Here are five reasons we think Deep Learning A-Z™ really is different, and stands out from the crowd of other training programs out there:


The first and most important thing we focused on is giving the course a robust structure. Deep Learning is very broad and complex and to navigate this maze you need a clear and global vision of it. 

That's why we grouped the tutorials into two volumes, representing the two fundamental branches of Deep Learning: Supervised Deep Learning and Unsupervised Deep Learning. With each volume focusing on three distinct algorithms, we found that this is the best structure for mastering Deep Learning.


So many courses and books just bombard you with the theory, and math, and coding... But they forget to explain, perhaps, the most important part: why you are doing what you are doing. And that's how this course is so different. We focus on developing an intuitive *feel* for the concepts behind Deep Learning algorithms.

With our intuition tutorials you will be confident that you understand all the techniques on an instinctive level. And once you proceed to the hands-on coding exercises you will see for yourself how much more meaningful your experience will be. This is a game-changer.


Are you tired of courses based on over-used, outdated data sets?

Yes? Well then you're in for a treat.

Inside this class we will work on Real-World datasets, to solve Real-World business problems. (Definitely not the boring iris or digit classification datasets that we see in every course). In this course we will solve six real-world challenges:

  • Artificial Neural Networks to solve a Customer Churn problem
  • Convolutional Neural Networks for Image Recognition
  • Recurrent Neural Networks to predict Stock Prices
  • Self-Organizing Maps to investigate Fraud
  • Boltzmann Machines to create a Recomender System
  • Stacked Autoencoders* to take on the challenge for the Netflix $1 Million prize

*Stacked Autoencoders is a brand new technique in Deep Learning which didn't even exist a couple of years ago. We haven't seen this method explained anywhere else in sufficient depth.


In Deep Learning A-Z™ we code together with you. Every practical tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means. 

In addition, we will purposefully structure the code in such a way so that you can download it and apply it in your own projects. Moreover, we explain step-by-step where and how to modify the code to insert YOUR dataset, to tailor the algorithm to your needs, to get the output that you are after. 

This is a course which naturally extends into your career.


Have you ever taken a course or read a book where you have questions but cannot reach the author? 

Well, this course is different. We are fully committed to making this the most disruptive and powerful Deep Learning course on the planet. With that comes a responsibility to constantly be there when you need our help.

In fact, since we physically also need to eat and sleep we have put together a team of professional Data Scientists to help us out. Whenever you ask a question you will get a response from us within 48 hours maximum. 

No matter how complex your query, we will be there. The bottom line is we want you to succeed. 

--- The Tools ---

Tensorflow and Pytorch are the two most popular open-source libraries for Deep Learning. In this course you will learn both!

TensorFlow was developed by Google and is used in their speech recognition system, in the new google photos product, gmail, google search and much more. Companies using Tensorflow include AirBnb, Airbus, Ebay, Intel, Uber and dozens more. 

PyTorch is as just as powerful and is being developed by researchers at Nvidia and leading universities: Stanford, Oxford, ParisTech. Companies using PyTorch include Twitter, Saleforce and Facebook.

So which is better and for what? 

Well, in this course you will have an opportunity to work with both and understand when Tensorflow is better and when PyTorch is the way to go. Throughout the tutorials we compare the two and give you tips and ideas on which could work best in certain circumstances.

The interesting thing is that both these libraries are barely over 1 year old. That's what we mean when we say that in this course we teach you the most cutting edge Deep Learning models and techniques.

--- More Tools ---

Theano is another open source deep learning library. It's very similar to Tensorflow in its functionality, but nevertheless we will still cover it.

Keras is an incredible library to implement Deep Learning models. It acts as a wrapper for Theano and Tensorflow. Thanks to Keras we can create powerful and complex Deep Learning models with only a few lines of code. This is what will allow you to have a global vision of what you are creating. Everything you make will look so clear and structured thanks to this library, that you will really get the intuition and understanding of what you are doing.

--- Even More Tools ---

Scikit-learn the most practical Machine Learning library. We will mainly use it:  

  • to evaluate the performance of our models with the most relevant technique, k-Fold Cross Validation
  • to improve our models with effective Parameter Tuning
  • to preprocess our data, so that our models can learn in the best conditions

And of course, we have to mention the usual suspects. This whole course is based on Python and in every single section you will be getting hours and hours of invaluable hands-on practical coding experience. 

Plus, throughout the course we will be using Numpy to do high computations and manipulate high dimensional arrays, Matplotlib to plot insightful charts and Pandas to import and manipulate datasets the most efficiently.

--- Who Is This Course For? ---

As you can see, there are lots of different tools in the space of Deep Learning and in this course we make sure to show you the most important and most progressive ones so that when you're done with Deep Learning A-Z™ your skills are on the cutting edge of today's technology.

If you are just starting out into Deep Learning, then you will find this course extremely useful. Deep Learning A-Z™ is structured around special coding blueprint approaches meaning that you won't get bogged down in unnecessary programming or mathematical complexities and instead you will be applying Deep Learning techniques from very early on in the course. You will build your knowledge from the ground up and you will see how with every tutorial you are getting more and more confident.

If you already have experience with Deep Learning, you will find this course refreshing, inspiring and very practical. Inside Deep Learning A-Z™ you will master some of the most cutting-edge Deep Learning algorithms and techniques (some of which didn't even exist a year ago) and through this course you will gain an immense amount of valuable hands-on experience with real-world business challenges. Plus, inside you will find inspiration to explore new Deep Learning skills and applications.

--- Real-World Case Studies ---

Mastering Deep Learning is not just about knowing the intuition and tools, it's also about being able to apply these models to real-world scenarios and derive actual measurable results for the business or project. That's why in this course we are introducing six exciting challenges:

#1 Churn Modelling Problem

In this part you will be solving a data analytics challenge for a bank. You will be given a dataset with a large sample of the bank's customers. To make this dataset, the bank gathered information such as customer id, credit score, gender, age, tenure, balance, if the customer is active, has a credit card, etc. During a period of 6 months, the bank observed if these customers left or stayed in the bank. 

Your goal is to make an Artificial Neural Network that can predict, based on geo-demographical and transactional information given above, if any individual customer will leave the bank or stay (customer churn). Besides, you are asked to rank all the customers of the bank, based on their probability of leaving. To do that, you will need to use the right Deep Learning model, one that is based on a probabilistic approach. 

If you succeed in this project, you will create significant added value to the bank. By applying your Deep Learning model the bank may significantly reduce customer churn.

#2 Image Recognition

In this part, you will create a Convolutional Neural Network that is able to detect various objects in images. We will implement this Deep Learning model to recognize a cat or a dog in a set of pictures. However, this model can be reused to detect anything else and we will show you how to do it - by simply changing the pictures in the input folder. 

For example, you will be able to train the same model on a set of brain images, to detect if they contain a tumor or not. But if you want to keep it fitted to cats and dogs, then you will literally be able to a take a picture of your cat or your dog, and your model will predict which pet you have. We even tested it out on Hadelin’s dog!

#3 Stock Price Prediction

In this part, you will create one of the most powerful Deep Learning models. We will even go as far as saying that you will create the Deep Learning model closest to “Artificial Intelligence”. Why is that? Because this model will have long-term memory, just like us, humans. 

The branch of Deep Learning which facilitates this is Recurrent Neural Networks. Classic RNNs have short memory, and were neither popular nor powerful for this exact reason. But a recent major improvement in Recurrent Neural Networks gave rise to the popularity of LSTMs (Long Short Term Memory RNNs) which has completely changed the playing field. We are extremely excited to include these cutting-edge deep learning methods in our course! 

In this part you will learn how to implement this ultra-powerful model, and we will take the challenge to use it to predict the real Google stock price. A similar challenge has already been faced by researchers at Stanford University and we will aim to do at least as good as them. 

 #4 Fraud Detection

According to a recent report published by Markets & Markets the Fraud Detection and Prevention Market is going to be worth $33.19 Billion USD by 2021. This is a huge industry and the demand for advanced Deep Learning skills is only going to grow. That’s why we have included this case study in the course.  

This is the first part of Volume 2 - Unsupervised Deep Learning Models. The business challenge here is about detecting fraud in credit card applications. You will be creating a Deep Learning model for a bank and you are given a dataset that contains information on customers applying for an advanced credit card. 

This is the data that customers provided when filling the application form. Your task is to detect potential fraud within these applications. That means that by the end of the challenge, you will literally come up with an explicit list of customers who potentially cheated on their applications.

#5 & 6 Recommender Systems

From Amazon product suggestions to Netflix movie recommendations - good recommender systems are very valuable in today's World. And specialists who can create them are some of the top-paid Data Scientists on the planet.

We will work on a dataset that has exactly the same features as the Netflix dataset: plenty of movies, thousands of users, who have rated the movies they watched. The ratings go from 1 to 5, exactly like in the Netflix dataset, which makes the Recommender System more complex to build than if the ratings were simply “Liked” or “Not Liked”. 

Your final Recommender System will be able to predict the ratings of the movies the customers didn’t watch. Accordingly, by ranking the predictions from 5 down to 1, your Deep Learning model will be able to recommend which movies each user should watch. Creating such a powerful Recommender System is quite a challenge so we will give ourselves two shots. Meaning we will build it with two different Deep Learning models.

Our first model will be Deep Belief Networks, complex Boltzmann Machines that will be covered in Part 5. Then our second model will be with the powerful AutoEncoders, my personal favorites. You will appreciate the contrast between their simplicity, and what they are capable of.

And you will even be able to apply it to yourself or your friends. The list of movies will be explicit so you will simply need to rate the movies you already watched, input your ratings in the dataset, execute your model and voila! The Recommender System will tell you exactly which movies you would love one night you if are out of ideas of what to watch on Netflix!  

--- Summary ---

In conclusion, this is an exciting training program filled with intuition tutorials, practical exercises and real-World case studies. 

We are super enthusiastic about Deep Learning and hope to see you inside the class!

Kirill & Hadelin


Get This Course Free udemy course: Data Science A-Z™: Real-Life Data Science Exercises Included

Data Science A-Z™: Real-Life Data Science Exercises Included

Successfully perform all steps in a complex Data Science project

Create Basic Tableau Visualisations

Perform Data Mining in Tableau

Understand how to apply the Chi-Squared statistical test

Apply Ordinary Least Squares method to Create Linear Regressions

Assess R-Squared for all types of models

Assess the Adjusted R-Squared for all types of models

Create a Simple Linear Regression (SLR)

Create a Multiple Linear Regression (MLR)

Create Dummy Variables

Interpret coefficients of an MLR

Read statistical software output for created models

Use Backward Elimination

Forward Selection

and Bidirectional Elimination methods to create statistical models

Create a Logistic Regression

Intuitively understand a Logistic Regression

Operate with False Positives and False Negatives and know the difference

Read a Confusion Matrix

Create a Robust Geodemographic Segmentation Model

Transform independent variables for modelling purposes

Derive new independent variables for modelling purposes

Check for multicollinearity using VIF and the correlation matrix

Understand the intuition of multicollinearity

Apply the Cumulative Accuracy Profile (CAP) to assess models

Build the CAP curve in Excel

Use Training and Test data to build robust models

Derive insights from the CAP curve

Understand the Odds Ratio

Derive business insights from the coefficients of a logistic regression

Understand what model deterioration actually looks like

Apply three levels of model maintenance to prevent model deterioration

Install and navigate SQL Server

Install and navigate Microsoft Visual Studio Shell

Clean data and look for anomalies

Use SQL Server Integration Services (SSIS) to upload data into a database

Create Conditional Splits in SSIS

Deal with Text Qualifier errors in RAW data

Create Scripts in SQL

Apply SQL to Data Science projects

Create stored procedures in SQL

Present Data Science projects to stakeholders

way it should and your training is smooth sailing. This course throws you into the deep end.

In this course you WILL experience firsthand all of the PAIN a Data Scientist goes through on a daily basis. Corrupt data, anomalies, irregularities - you name it!

This course will give you a full overview of the Data Science journey. Upon completing this course you will know:

  • How to clean and prepare your data for analysis
  • How to perform basic visualisation of your data
  • How to model your data
  • How to curve-fit your data
  • And finally, how to present your findings and wow the audience
This course will give you so much practical exercises that real world will seem like a piece of cake when you graduate this class. This course has homework exercises that are so thought provoking and challenging that you will want to cry... But you won't give up! You will crush it. In this course you will develop a good understanding of the following tools:
  • SQL
  • SSIS
  • Tableau
  • Gretl

This course has pre-planned pathways. Using these pathways you can navigate the course and combine sections into YOUR OWN journey that will get you the skills that YOU need.

Or you can do the whole course and set yourself up for an incredible career in Data Science.

The choice is yours. Join the class and start learning today!

See you inside,


Kirill Eremenko


Get This Course Free udemy course: A Complete Guide on TensorFlow 2.0 using Keras API

A Complete Guide on TensorFlow 2.0 using Keras API

How to use Tensorflow 2.0 in Data Science

Important differences between Tensorflow 1.x and Tensorflow 2.0

How to implement Artificial Neural Networks in Tensorflow 2.0

How to implement Convolutional Neural Networks in Tensorflow 2.0

How to implement Recurrent Neural Networks in Tensorflow 2.0

How to build your own Transfer Learning application in Tensorflow 2.0

How to build a stock market trading bot using Reinforcement Learning (Deep-Q Network)

How to build Machine Learning Pipeline in Tensorflow 2.0

How to conduct Data Validation and Dataset Preprocessing using TensorFlow Data Validation and TensorFlow Transform.

Putting a TensorFlow 2.0 model into production

How to create a Fashion API with Flask and TensorFlow 2.0

How to serve a TensorFlow model with RESTful API

ent and maintenance processes. From the educational side, it boosts people's understanding by simplifying many complex concepts. From the industry point of view, models are much easier to understand, maintain, and develop.

Deep Learning is one of the fastest growing areas of Artificial Intelligence. In the past few years, we have proven that Deep Learning models, even the simplest ones, can solve very hard and complex tasks. Now, that the buzz-word period of Deep Learning has, partially, passed, people are releasing its power and potential for their product improvements.

The course is structured in a way to cover all topics from neural network modeling and training to put it in production.

In Part 1 of the course, you will learn about the technology stack that we will use throughout the course (Section 1) and the TensorFlow 2.0 library basics and syntax (Section 2).

In Part 2 of the course, we will dig into the exciting world of deep learning. Through this part of the course, you will implement several types of neural networks (Fully Connected Neural Network (Section 3), Convolutional Neural Network (Section 4), Recurrent Neural Network (Section 5)). At the end of this part, Section 6, you will learn and build their own Transfer Learning application that achieves state of the art (SOTA) results on the Dogs vs. Cats dataset.

After passing the part 2 of the course and ultimately learning how to implement neural networks, in Part 3 of the course, you will learn how to make your own Stock Market trading bot using Reinforcement Learning, specifically Deep-Q Network.

Part 4 is all about TensorFlow Extended (TFX). In this part of the course, you will learn how to work with data and create your own data pipelines for production. In Section 8 we will check if the dataset has any anomalies using the TensorFlow Data Validation library and after learn how to check a dataset for anomalies, in Section 9, we will make our own data preprocessing pipeline using the TensorFlow Transform library.

In Section 10 of the course, you will learn and create your own Fashion API using the Flask Python library and a pre-trained model. Throughout this section, you will get a better picture of how to send a request to a model over the internet. However, at this stage, the architecture around the model is not scalable to millions of request. Enter the Section 11. In this section of the course, you will learn how to improve solution from the previous section by using the TensorFlow Serving library. In a very easy way, you will learn and create your own Image Classification API that can support millions of requests per day!

These days it is becoming more and more popular to have a Deep Learning model inside an Android or iOS application, but neural networks require a lot of power and resources! That's where the TensorFlow Lite library comes into play. In Section 12 of the course, you will learn how to optimize and convert any neural network to be suitable for a mobile device.

To conclude with the learning process and the Part 5 of the course, in Section 13 you will learn how to distribute the training of any Neural Network to multiple GPUs or even Servers using the TensorFlow 2.0 library.


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The student be able to understand the concepts of new-age programming language - The DART.

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Use the numpy library to create and manipulate arrays.

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Use Typescript with confidence in a full stack development context

Some Angular notions are needed to understand the last section of the course

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Master modern Python 3 fundamentals as well as advanced topics

Learn Object Oriented Programming

Automate extracting data from websites using web scraping libraries like BeautifulSoup and Selenium.

Interact with REST APIs using Python and build a OpenWeatherMap API!

Use Python to send Emails

Creating Snake Game for Terminal

Learn advanced Python features and Understand complex topics

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Learn Function


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Data Types & Variables


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Object Oriented Java Programming

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Setting Up



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Installing Node

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استخدم بايثون لعلوم البيانات والتعلم الآلي

تنفيذ خوارزميات تعلم الآلة

ريادة الأعمال بأستخدام الذكاء الاصطناعي

كيفية صنع بيئة عمل أفتراضية للتأهيل لسوق العمل

العقلية التحليلة

NumPy for Numerical Data تعلم ال

Pandas for Data Analysis تعلم ال

SciKit-Learn for Machine Learning Tasks استخدام ال

K-Means Clustering

Logistic Regression

Linear Regression

Random Forest and Decision Trees

Neural Networks

Support Vector Machines

       Advanced Numpy                                      

                   Advanced Pandas

                   Data Preprocessing                

الجزء - 2 


                  Simple Linear Regression

                  Multiple Linear Regression Intuition

                  Polynomial Regression

                  Support Vector Regression (SVR)

                  Decision Tree  Regression,

                  Random Forest Regression   


  الجزء - 3

Classification :

                الانحدار اللوجستي



               Kernel SVM                

               Naive Bayes                

               Decision Tree Classification                

               Random Forest Classification                

الجزء - 4  

Clustering  :


               Hierarchical Clustering                

الجزء - 5   

Association Rule Learning::



الجزء - 6

Reinforcement Learning :

                Upper Confidence Bound                

               Thompson Sampling               

الجزء - 7   

Natural Language Processing (NLP) :

                Bag-of-words model               

                algorithms for NLP               

الجزء - 8   

Deep Learning :

                 الشبكات العصبية الاصطناعية، الشبكات العصبية التلافيفية 

                (Deep Learning: Artificial Neural Networks, Convolutional Neural Networks)

الجزء - 9

Dimensionality Reduction  :


               Kernel PCA               


الجزء - 10 

Model Selection & Boosting :

                k-fold Cross Validation               

                Parameter Tuning,                

                Grid Search               


فضلا على ذلك، فإن الدورة مليئة بالتمارين العملية التي تستند إلى أمثلة واقعية. لذا لن تتعلم النظرية فحسب، بل ستحصل أيضًا على بعض التدريب العملي  و تتعلم كيفية بناء النماذج الخاصة بك.

أيضا ستشتمل هذه الدورة التدريبية على قوالب بالبايثون و التي يمكنك تنزيلها واستخدامها في مشروعاتك الخاصة.

سيكون لديك فهم أساسي للعديد من نماذج تعلم الألة 

عمل تحليل قوي وتوقعات دقيقة للبيانات

Reinforcement Learning  و NPL و ال Deep Learning التعامل مع موضوعات محددة مثل

 Dimensionality Reduction التعامل مع التقنيات المتقدمة مثل

 سوف تتعلم كيف تختار النموذج الصحيح والمناسب لكل نوع من أنواع تعليم الألة  لكافة المشاكل المختلفة او متطلبات عملك  

  قم ببناء مزيج من عدة نماذج مختلفة لتعليم الألة بالتعلم كيفية دمجها معا لحل المشاكل الصعبة


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