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Machine Learning for Beginners to Advanced (Step-by-Step Practical Course)
About This Course
This course is designed for students and beginners who want to learn Machine Learning from scratch. You will start with Python essentials, mathematics concepts, and gradually move into data preprocessing, supervised and unsupervised algorithms, model evaluation, deployment, and real-world projects.
The course includes assignments, quizzes, downloadable resources, and one final real project so you gain hands-on learning experience. By the end of this course, you will be able to build, train, evaluate, and deploy machine learning models confidently.
Learning Objectives
Understand fundamentals of Machine Learning and core terminology
Perform data preprocessing and cleaning
Work with supervised and unsupervised learning models
Train and evaluate ML models
Use Python libraries: Numpy, Pandas, Matplotlib, Scikit-learn
Build ML projects including prediction systems
Deploy ML model basics
Material Includes
- Downloadable datasets
- Assignments after each module
- MCQ quizzes per module
- Cheat sheets
- Final assessment project
- Completion certificate
Requirements
- Laptop or computer
- Python installed
- Internet connection
- Basic math understanding (optional, explained in course)
Target Audience
- Beginners
- Students
- Anyone interested in ML or AI
- Python learners
- Data science and automation learners
Curriculum
2 Lessons20h 13m