Javascript and Python Streamlit ML project based course

--- # Master Javascript & Python with Streamlit ML Projects 🚀 ### Course Title: **Javascript and Python Streamlit ML Project Based Course** #### Instructor: Salvatore Aetos --- ## **Course Headline:** Dive into the world of coding with hands-on projects in Javascript & Python! 🌐✨ --- ### **Overview:** If you're looking to **kickstart your journey** in learning JavaScript or enhance your existing skills, this is the perfect course for you. Whether you're a beginner or an intermediate developer, this comprehensive course will take your knowledge of HTML, CSS, Javascript, and Python with Streamlit to the next level. You'll work on practical projects like interactive Quizzes and engaging Games from scratch. Let's build something cool together! 🛠️✨ --- ### **What You'll Learn in this Course:** #### **Javascript Theory (From Basics to Advanced Concepts):** - Variables & Data Types - Functions, Parameters, and Returns - Scope & Flow Control - Alert, Confirm, Prompt - Objects & Arrays - Mathematical & Logical Operators - **And much more! (Future topics to be added)** 📚💡 --- **This is a fun, practical & project-based course for all skill levels.** You'll get hands-on experience with HTML5, CSS3, and JavaScript. Every project is built from the ground up, ensuring you learn the ins and outs of dynamic functionality without relying on frameworks or libraries. 🛠️💻 --- ### **Your Projects:** #### **Project 1: Quiz Game** - Random Number Generation - User Interface Design - Algorithm Implementation for Calculating Answers - Win and Lose Conditions - Progress Bars & Overlays - Animations to Engage Users 🎮 #### **Project 2: Whack a Mole Game** - ES6 Syntax Exploration - Event Listeners & CSS Control with JavaScript - Timing with `setTimeout` vs. `setInterval` - Working with `const`, `let`, and regular functions - High Score Tracker & Local Storage Implementation 🐀🔨 --- ### **Machine Learning Journey with Python & Streamlit:** Are you ready to leap into the realm of Machine Learning and Data Science? This course will guide you through the process of setting up your environment, installing libraries, and creating projects that apply Supervised and Unsupervised Learning. You'll work on: 1. **Salary Predictor** 💼 2. **Classification Webapp** 📊 3. **BMI Calculator** 🧪 --- ### **Machine Learning Libraries:** Get hands-on with these powerful libraries: - Streamlit for creating interactive web apps without writing boilerplate code - KNN & Clustering for basic classification and clustering algorithms - SVM (Support Vector Machines) for efficient and scalable machine learning models - Numpy for numerical computing - Pandas for data manipulation and analysis - MatplotLib for data visualization - Scikit-Learn for machine learning algorithms and tools 🛠️💻 --- ### **Assessment & Challenges:** - Quiz on Streamlit and Machine Learning to test your knowledge - A challenge to create a fully functional BMI Calculator with explanations provided in text and video format 🏆 --- ### **Join the Developer Shack Today!** Unlock the secrets of Machine Learning for Data Science with Salvatore Aetos. Sign up now, embark on an exciting journey, and create amazing apps with Streamlit ML projects! 🚀🎉 --- **Ready to code, learn, and build? Click [here](#) to enroll and start your coding adventure with us!**