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Free Data Science ★ 0.0 11 students 2 hours

Machine Learning in Python with Google Colab

Machine Learning with Statistical Analysis and Data Visualization in Python using Google Colab

Description


Learn Machine 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 learn Python, data science, statistical analysis, data visualization, and machine learning without installing any software.

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You will start by learning how to use Google 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 covers data 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 for data cleaning, data analysis, research data management, business analytics, and machine learning projects.

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You will also learn beginner-level statistical analysis and data visualization in Python to understand patterns, trends, and relationships in data. Finally, you will learn core machine 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 use Python with Google Colab for practical data analysis, statistical analysis, data visualization, and machine learning projects with confidence.


Total Students11
Duration2 hours
LanguageEnglish (US)
Number of lectures30
Number of quizzes0
Total Reviews0
Global Rating0
Instructor NameMd Ahshanul Haque

Course Insights (for Students)

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Student Satisfaction

78% positive recent sentiment

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Momentum

Steady interest

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Time & Value

  • Est. time: 2 hours
  • Practical value: 5/10

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Roadmap Fit

  • Beginner → → Advanced

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Clear explanations and helpful examples.

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No consistent issues reported.

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