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🙏 Welcome to our AI Online Learning platform
🎓 Learn AI skills with practical online courses
🤖 Master the latest AI tools and technologies
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📚 Learn from structured, expert-led courses
🚀 Upgrade your career with future-ready AI skills
🌐 Learn anytime, anywhere with flexible online learning

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🙏 Welcome to our AI Online Learning platform
🎓 Learn AI skills with practical online courses
🤖 Master the latest AI tools and technologies
💡 Build real-world projects and boost your skills
📚 Learn from structured, expert-led courses
🚀 Upgrade your career with future-ready AI skills
🌐 Learn anytime, anywhere with flexible online learning
🙏 Welcome to our AI Online Learning platform
🎓 Learn AI skills with practical online courses
🤖 Master the latest AI tools and technologies
💡 Build real-world projects and boost your skills
📚 Learn from structured, expert-led courses
🚀 Upgrade your career with future-ready AI skills
🌐 Learn anytime, anywhere with flexible online learning
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Data Science with Python

Categories: Data Science
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About Course

Learn how to use Python for data analysis, visualization, and practical data science workflows. This beginner-friendly course introduces Python, NumPy, Pandas, Matplotlib, data cleaning, exploratory data analysis, and basic statistical concepts to help learners turn raw data into meaningful insights.

What Will You Learn?

  • Understand the fundamentals of Data Science and the role of Python
  • Learn Python programming concepts required for data analysis
  • Work with datasets using NumPy and Pandas
  • Clean, transform, and organize raw data for analysis
  • Perform exploratory data analysis to identify patterns and trends
  • Create meaningful charts and visualizations using Matplotlib
  • Understand basic statistics and interpret data-driven insights
  • Build a practical end-to-end data analysis workflow using Python

Course Content

Module 1: Introduction to Data Science and Python
What is Data Science? Data Science Lifecycle and Workflow Role of Python in Data Science Python Variables, Data Types, and Operators Lists, Dictionaries, Functions, and Loops Introduction to Python Libraries for Data Science

Module 2: Data Analysis with NumPy and Pandas
Introduction to NumPy Arrays and Numerical Operations Introduction to Pandas Series and DataFrames Importing and Exploring Datasets Filtering, Sorting, and Transforming Data

Module 3: Data Cleaning and Exploratory Data Analysis
Understanding Data Quality Handling Missing and Duplicate Data Data Types and Data Transformation Detecting Outliers and Inconsistencies Exploratory Data Analysis Techniques Identifying Patterns, Trends, and Relationships

Module 4: Data Visualization and Practical Data Science
Introduction to Data Visualization Creating Charts with Matplotlib Bar Charts, Line Charts, Histograms, and Scatter Plots Understanding Basic Statistical Concepts Interpreting Data and Communicating Insights Building a Practical Python Data Analysis Project

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