What you'll learn

Use Python for Data Science and Machine Learning
Implement Machine Learning Algorithms
Learn to use Pandas for Data Analysis
Learn to use NumPy for Numerical Data
Learn to use Matplotlib for Data Visualizations
Use Plotly for interactive dynamic visualizations
Linear Regression
Decision Trees
Use SciKit-Learn for Machine Learning Tasks
Polynomial Regression
Logistic Regression
Build real world Projects using SciKit-Learn
Learn to use Anaconda and Jupyter Notebook

Requirements

No prior experience is required. We will start from the very basics
You'll need to install Anaconda. We will show you how to do that step by step work on projects
A Willingness to Learn & Practice – Data Science & Machine Learning require hands-on practice, so be ready to experiment and build real-world projects
No prior experience in data science or machine learning is needed—I will guide you step by step from the basics to advanced topics

Description

Course

Description

Data Science & ML Bootcamp 2025: Real Projects – Go from Beginner to Job-Ready with Hands-On Training! Want to break into high-paying Data Science & Machine Learning roles? This project-based bootcamp gives you the exact skills companies want—no fluff, just real-world training that gets you hired faster!Are you ready to master Data Science & Machine Learning and land a high-paying job in 2025? This comprehensive, project-based course will take you from beginner to expert, giving you the skills needed to work as a Data Scientist, Machine Learning Engineer, or AI Specialist. Whether you're just starting out or looking to advance your career, this course will equip you with real-world, job-ready skills to succeed in the fast-growing field of data science and AI.What You'll Learn: Master Python for Data Science & Machine Learning – Learn the essential libraries: Pandas, NumPy, Matplotlib, and Scikit-learn.Work with Real-World Data – Learn how to clean, process, analyze, and visualize data for actionable insights.Build Machine Learning Models – Implement regression, classification, clustering, and advanced ML algorithms. Develop Industry-Ready Projects – Work on hands-on projects to build a strong portfolio.Who Is This Course For? Beginners & Aspiring Data Scientists – No prior experience needed! This course starts from scratch and gradually advances. Students & Career Changers – Looking to break into Data Science & AI? This course is your roadmap. Software Engineers & Developers – Transition into Machine Learning with a structured learning approach.Business Analysts & Professionals – Leverage ML and AI for data-driven decision-making.This is not just another theory-based course. You'll be working on real-world datasets, practical projects, and career-building exercises to help you become job-ready.Why Choose This Course?Beginner-Friendly & Step-by-Step – Learn at your own pace Real-World Projects – Gain practical experience by solving industry-level challenges. By the end of this course, you'll have the skills, confidence, and portfolio to secure a high-paying job in Data Science & Machine Learning!Enroll now and take the first step toward your six-figure career!

Who this course is for

Beginners & Aspiring Data Scientists – No prior experience? No problem! This course starts from the basics and gradually moves to advanced topics.
Students & Recent Graduates – If you want to break into the field of Data Science, AI, or Machine Learning, this course will help you build a solid foundation and portfolio
Software Developers & Engineers – Looking to transition into Machine Learning? This course will help you apply your coding skills to data science projects
Analysts & Business Professionals – If you work with data and want to leverage Machine Learning for better decision-making, this course will give you the necessary skills
Job Seekers & Career Changers – Want to land a high-paying data science job in 2025? This course covers everything from technical skills to interview preparation.
Homepage:

https://www.udemy.com/course/master-data-science-ml-build-real-world-projects/