Machine learning in Python with Google Colab

What you'll learn

Prepare, clean, and explore datasets for machine learning
Learn Python basics for machine learning using Google Colab
Build practical machine learning models step by step in Python
Evaluate model performance using accuracy, confusion matrix, and other metrics

Requirements

Basic computer knowledge is enough. No previous machine learning experience is required.

Description

LearnMachine Learning in Python with Google Colab in a simple, practical, and beginner-friendly way. This course is designed for students, researchers, data analysts, public health professionals, business learners, and anyone who wants to learnPython, data science, statistical analysis, data visualization, and machine learning without installing any software.
You will start by learning how to useGoogle Colab to write and run Python code online. You will learn how to create notebooks, save your work, connect Google Drive, import datasets, and manage files easily. Then you will learn basic Python concepts such as variables, data types, and simple coding tasks.
The course also coversdata handling with Pandas, including how to open datasets, view rows and columns, check data types, find missing values, summarize data, and prepare data for analysis. These skills are important fordata cleaning, data analysis, research data management, business analytics, and machine learning projects.
You will also learn beginner-levelstatistical analysis anddata visualization in Python to understand patterns, trends, and relationships in data. Finally, you will learn coremachine learning concepts, including features, target variables, training data, testing data, classification, regression, model building, and model evaluation.
By the end of this course, you will be able to usePython with Google Colab for practicaldata analysis, statistical analysis, data visualization, and machine learning projects with confidence.

Who this course is for

Beginners who want to learn machine learning in Python
Students, researchers, and professionals who want practical machine learning skills

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