Python Data Analytics Course

Python Data Analytics Course

Learn industry-relevant Python skills with hands-on projects, real datasets, and expert guidance. This course covers Python end-to-end analysis.

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Course Syllabus

Module 1: Python Basics

  • Introduction to Python
  • Python Installation and IDE Setup
  • Variables and Data Types
  • Operators
  • Conditional Statements (if, if-else, nested if)
  • Loops (for, while)
  • Functions and Lambda Functions
  • List, Tuple, Set, Dictionary
  • String Manipulation
  • Exception Handling
  • File Handling

Module 2: Python for Data Handling

  • Introduction to Libraries: NumPy, Pandas
  • Arrays, Indexing, Slicing, Mathematical Operations
  • Pandas: Series and DataFrames
  • Data Import/Export (CSV, Excel)
  • Data Selection and Filtering
  • Handling Missing Data & Cleaning
  • GroupBy, Pivot Tables, Merging, Joining

Module 3: Data Visualization

  • Matplotlib & Seaborn Basics
  • Line, Bar, Pie, Scatter, Histogram
  • Customizing Graphs: Labels, Legends, Colors
  • Advanced Seaborn Charts
  • Correlation Matrix & Heatmaps

Module 4: Exploratory Data Analysis (EDA)

  • Understanding Data & Summary Statistics
  • Outlier Detection
  • Data Distribution Analysis
  • Handling Duplicates
  • Data Transformation Techniques
  • Encoding Categorical Variables

Module 5: Working with Real-Time Datasets

  • Importing Data from APIs
  • Web Scraping Basics (Optional)
  • Time Series Data Handling
  • Case Studies with Real Datasets

Module 6: Statistical Analysis (Optional)

  • Descriptive Statistics
  • Probability Basics
  • Hypothesis Testing

Module 7: Project Work

  • End-to-End Data Analysis Project
  • Data Cleaning & EDA
  • Visualization
  • Insights and Recommendations
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