Javascript and Python Streamlit ML Certified project course

Javascript and Python Streamlit ML Certified project course, available at $19.99, has an average rating of 5, with 61 lectures, 9 quizzes, based on 2 reviews, and has 19 subscribers.

You will learn about At the end of the course you will have great technical knowledge on HTML, CSS, Javascript and Python Streamlit You will learn theoretical aspects on Javascript You will be able to build projects using HTML, CSS and Javascript to develop games and quizzes Learn Event Handlers and DOM manipulation in a project Set Time Out and Set Interval in a project Create Machine Learning projects webapp using Python Streamlit Learn to use Panda for Data Analysis Linear Regression and Matplotlib Implement Scikit-Learn for Machine Learning Projects Random Forest and Decision Trees This course is ideal for individuals who are Web developer enthusiasts or Game developer enthusiasts or Machine learning students or Data Scientists students It is particularly useful for Web developer enthusiasts or Game developer enthusiasts or Machine learning students or Data Scientists students.

Enroll now: Javascript and Python Streamlit ML Certified project course

Summary

Title: Javascript and Python Streamlit ML Certified project course

Price: $19.99

Average Rating: 5

Number of Lectures: 61

Number of Quizzes: 9

Number of Published Lectures: 61

Number of Published Quizzes: 9

Number of Curriculum Items: 70

Number of Published Curriculum Objects: 70

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

At the end of the course you will have great technical knowledge on HTML, CSS, Javascript and Python Streamlit
You will learn theoretical aspects on Javascript
You will be able to build projects using HTML, CSS and Javascript to develop games and quizzes
Learn Event Handlers and DOM manipulation in a project
Set Time Out and Set Interval in a project
Create Machine Learning projects webapp using Python Streamlit
Learn to use Panda for Data Analysis
Linear Regression and Matplotlib
Implement Scikit-Learn for Machine Learning Projects
Random Forest and Decision Trees

Who Should Attend

Web developer enthusiasts
Game developer enthusiasts
Machine learning students
Data Scientists students

Target Audiences

Web developer enthusiasts
Game developer enthusiasts
Machine learning students
Data Scientists students

If you want to start learning Javascript or to apply HTML5, CSS3 and Javascript in a project to program or you already have some basic knowledge, then you are in the right place. This course gives you a chance to take your knowledge to the next level. You will start from very basics and learn to apply the skills in two different projects (Quiz and Game).

Get certified in Javascript and Python Streamlit Machine Learning. Please send me your email in my inbox and I will forward you your certification after your assessment. Please give at least few weeks to a month to receive your certificate via email as it is a popular course.

You will learn about the very basics of this language, like how to write JavaScript, what kind of syntax it has.

You will learn the following topics on Javascript theory:

Javascript Variables

Javascript Data Type

Javascript Function

Javascript Function Parameter

Javascript Return

Javascript Scope

Javascript Alert Confirm Prompt

Javascript Objects

Javascript Arrays

Javascript If Else statement

Javascript Switch Case

Javascript Maths Operators

Javascript Logical Operators

(More topics will be added in the future)

This is a fun, practical & project based coursefor all skill levels. The projects in this course are designed to get you building things using HTML5, CSS & JavaScript with no frameworks or libraries. Every project is built from scratch and has some kind of dynamic functionality.

Although this is a theoretical and project based course, I will still be explaining everything as I go. There are projects designed for you to complete in a few hours.

You should have some basic knowledge of HTML/CSS/JS. If you are brand new, this course is a mix of both with emphasis on Javascript theory and building two projects. The projects are end to end product.

You will learn to create two projects.

First project is Quiz. The following skills you will learn to implement in the project:

Choosing Random Numbers

User Interface

Calculating Answer (Algorithm)

Win and Lose condition

Progress Bar

Overlay

Animation

Second project is Whack a Mole game. The following skills you will learn to implement in the project:

Learn about ES6 syntax

Event listeners

How to control CSS styles and classes with JavaScript

What’s the difference between setTimeout and setInterval

How to use clearInterval, difference between const and let variables

Regular JavaScript functions and ES6 arrow functions and much more.

Create a plugin that tracks, updates and stores high score. We will also talk about logical operators in JavaScript (OR/AND/NOT) and other fundamental vanilla JavaScript techniques and principles that are useful not only for games, but also for building websites, generative art

JavaScript DOM manipulation (build a simple game add-on that keeps track of high score)

Learn local storage browser objects and it’s associated JavaScript methods.

The projects will help you better understand how JavaScript works, use these skills to level up as a Front end web developer and get one step closer to getting hired for your first coding job. Also, it is a good stepping stone before you start learning React, React native and Next.js

Are you ready to start your career in Machine learning and as a Data Scientist. This course will be your guide to learning how to use the power of Python and the libraries to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!

It is a brilliant course where you will learn how to setup the project step by step from installation of python and the libraries to finished project. There are three projects that will allow you to use and implement supervise and unsupervise learning in the projects.

You will learn to create the following projects:

1. Salary Predictor

2. Classification Webapp

3. BMI Calculator

This course will also allow you to utilise and implement several Machine learning libraries to these projects. The list are:

Streamlit

KNN Clustering

SVM
Numpy

Pandas

MatplotLib

Scikit-Learn

Furthermore, you will be able to assess your knowledge through doing a quiz on Streamlit and Machine Learning. Also, a challenge is set to create a BMI calculator. Solutions are given in text form and video for explanation.

So I invite you to join me, Developer Shack on an exciting journey into unlocking the secrets of Machine Learning for Data Science.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Whack a mole Game

Lecture 1: HTML structure Game

Lecture 2: CSS styling game 1

Lecture 3: CSS styling game 2

Lecture 4: CSS styling game 3

Lecture 5: Javascript Pop out Functionality

Lecture 6: Javascript start to finish skeleton game

Lecture 7: Start game and movement of Objects animated

Lecture 8: Score system and animation improvement

Lecture 9: High Score functionality

Lecture 10: End of game message

Chapter 3: Maths Quiz game

Lecture 1: Setup Javascript

Lecture 2: Generate Problem Javascript

Lecture 3: Console log function Javascript

Lecture 4: Random Generator Javascript

Lecture 5: Live server extension Javascript

Lecture 6: Form Creation Javascript

Lecture 7: Form prevent default Javascript

Lecture 8: Check solution Javascript

Lecture 9: Point System Javascript

Lecture 10: Update system Javascript

Lecture 11: Logic and Reset Game Javascript

Lecture 12: Styling CSS

Lecture 13: Styling and UI system

Lecture 14: UI Design updated and Game Functionality

Lecture 15: End message and Reset functionality

Lecture 16: Game and Animation

Chapter 4: Javascript Theory

Lecture 1: Data Types

Lecture 2: Variables

Lecture 3: Maths Operators

Lecture 4: Logical operators

Lecture 5: Function

Lecture 6: Function Parameter

Lecture 7: Objects

Lecture 8: If Else statement

Lecture 9: Return

Lecture 10: Scoping

Lecture 11: Switch Case

Lecture 12: Increment and Decrement

Lecture 13: Alert Confirm and Prompt

Chapter 5: Salary Predictor Python Streamlit

Lecture 1: Python Start up information

Lecture 2: Startup project

Lecture 3: Installation of Python libraries

Lecture 4: Title and Navigation

Lecture 5: Image and Load Data

Lecture 6: Interactive and Non-Interactive Plots

Lecture 7: Graph Plots adjusted

Lecture 8: Interactive slider connected to plots

Lecture 9: Prediction using Linear Regression on Plots

Lecture 10: Contribution to Data (Primary Data as .csv)

Lecture 11: Changing Image

Lecture 12: Tips on Python Streamlit

Chapter 6: Classifiers and Cluster project

Lecture 1: Setup Introduction and Streamlit

Lecture 2: Title and Sidebar

Lecture 3: Shape of Datasets and Number of Classes

Lecture 4: Select Dataset and Keys

Lecture 5: Streamlit Classifiers and dealing with Errors

Lecture 6: Classifiers Accuracy Score

Lecture 7: Plotting the Dataset

Chapter 7: Challenge: Create a BMI Calculator

Lecture 1: Solution for BMI Calculator

Chapter 8: Chat GPT

Lecture 1: Chat GPT

Chapter 9: Machine Learning and Streamlit Assessment

Instructors

Salvatore Aetos
Professional Web Developer and Teacher

Rating Distribution

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4 stars: 0 votes
5 stars: 2 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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