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Data Science Foundations

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About Course

Learn the complete data science workflow from collecting and cleaning data to analyzing trends and building predictive models. This beginner-friendly course introduces Python, data visualization, statistical thinking, and machine learning through practical projects that mirror real-world business and research scenarios.

What Will You Learn?

  • Write Python code for data analysis
  • Clean and prepare datasets
  • Analyze data using Pandas
  • Create effective visualizations
  • Understand statistical concepts
  • Build basic machine learning models
  • Interpret and communicate insights
  • Complete end-to-end data projects

Course Content

Python for Data Analysis
Learn the Python fundamentals necessary for working with data and preparing datasets for analysis.

  • Introduction to Python
  • Working with Data Structures
  • Introduction to Pandas
  • Python Fundamentals
  • Pandas & Data Structures

Data Cleaning & Visualization
Learn how to prepare messy datasets and create visualizations that communicate meaningful insights.

  • Handling Missing Data
  • Data Visualization Fundamentals
  • Using Matplotlib and Seaborn
  • Data Cleaning
  • Visualization Assessment

Introduction to Machine Learning
Understand how machines learn from data and build your first predictive models.

  • What Is Machine Learning?
  • Supervised vs Unsupervised Learning
  • Building Your First Model
  • Machine Learning Basics
  • Model Building Assessment
Free
Free access this course
  • Beginner
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A course by

M
MesazhiNet

Material Includes

  • Practice datasets
  • Python cheat sheet
  • Data cleaning checklist
  • Visualization guide
  • Machine learning workbook

Requirements

  • Basic computer skills
  • No programming experience required
  • Python installation recommended
  • Google Colab or Jupyter Notebook access

Audience

  • Students
  • Aspiring Data Analysts
  • Aspiring Data Scientists
  • Business Professionals
  • Researchers
  • Career Switchers