The Complete Python And JavaScript Course: Build Projects

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Want to learn ES6 development and TensorFlow stock market prediction modeling? Build your first web app in this course!

What you’ll learn

  • Build web apps using JavaScript ES6!
  • Code in JavaScript and Python.
  • Calculate the linear regression in the TensorFlow framework.
  • Make an app with Python that uses data to predict the stock market.
  • Build impressive models with a single variable.
  • Understand where to use machine learning and how to use data.
  • Navigate the PyCharm integrated development environment.
  • Download all source code and files from projects.
  • And much more in this epic Mammoth Interactive course!

Requirements

  • Modern web browser.
  • PyCharm Community Edition.
  • Basic HTML/CSS knowledge is helpful but not required. Enroll in “Kids Coding – Introduction to HTML, CSS, and JavaScript” to learn!
  • Prior coding experience is helpful. For an in-depth intro to Python, search for our “Ultimate Python Beginner Course.”
  • Topics involve intermediate math, so familiarity with university-level math is helpful.

Description

“It’s a great course for someone with little experience with programming” – Joshua, Mammoth Interactive student ⭐ ⭐ ⭐ ⭐ ⭐

This amazing Mammoth Interactive course will make clear to you many obscure concepts on JavaScript, Python, and machine learning!

Funded by a #1 Kickstarter Project by Mammoth Interactive

Python & JS Masterclass: Build TensorFlow & ES6 Projects is detailed coverage you will not get in other Python courses.

Our collaborative instructors will teach you the impressive application of machine learning in-depth and realism!

Enroll now to learn how to develop in PyCharm Community Edition 2017.

Python and JS Masterclass: Build TensorFlow and ES6 Projects

  • 27 hours on-demand video!
  • Learn offline via the Udemy app
  • 8 Articles
  • 5 Supplemental Resources
  • Full lifetime access

Learn to Code in JavaScript and Python!

In Python & JS Masterclass: Build TensorFlow & ES6 Projects, you will learn the fundamentals of coding in JavaScript, including ES6. You will learn how to change what is displayed on a webpage using JavaScript.

No prior experience in JavaScript is required. We will explore ES6 in-depth and cover many of its new features. You will learn the newest possibilities and fundamental building blocks of JavaScript.

  • Get started with JavaScript basics
  • Learn about ES6 and its new features
  • Apply ES6 concepts in your projects
  • Use build tools like Gulp and Webpack
  • Compile ES6 into ES5 using Babel

Predict the Stock Market with Automated Tasks

You will learn how to code in Python 3, calculate linear regression with TensorFlow, and make a stock market prediction app. We interweave theory with practical examples so that you learn by doing.

  • Learn how to code in Python, a popular coding language used for websites like YouTube and Instagram.
  • Learn TensorFlow and how to build models of linear regression.
  • Build stock market prediction models for integration into apps!

Blend Theory with Hands-On Coding Projects!

You will learn how to build an impressive model with a single variable. We don’t go into daily stock market prediction.

Build Powerful Web Apps with ES6

With ES6 (ECMAScript 6th Edition), you can code for the web. ECMAScript is another name for JavaScript. ES6 has standardized features that JavaScript engines implement. ES6 is well-supported across different web browsers.

Become a Data Scientist Today

You too can become a web developer by learning the popular programming language JavaScript. You’ll also learn hands-on Python coding, TensorFlow logistic regression, regression analysis, machine learning, and data science!

Enroll now while on sale! Who is the target audience?

  • Anyone who wants to learn to code in JavaScript!
  • Any JavaScript developers who want to learn ES6.
  • Anyone who wants to build data models for short-term stock market prediction!

Created by Mammoth Interactive, John Bura
Last updated 7/2018
English
English [Auto-generated]

Size: 15.72 GB

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