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.
Sign up right now, and let’s create amazing Machine learning apps!
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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- 3 stars: 0 votes
- 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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