What You'll Learn
- What is Data Science?
- Why Python for Data Science?
- Introduction to Jupyter Notebooks
- Variables, Data Types, and Operators
- Control Flow: Conditionals and Loops
- Working with Modules and Packages
- Error Handling and Assertions
- Introduction to Pandas: Series and DataFrames
- Reading & Writing Data (CSV, Excel, JSON)
- Data Cleaning & Preprocessing
- Handling Missing Values & Duplicates
- Data Transformation & Feature Engineering
- Creating, Indexing, and Slicing Arrays
- Mathematical Operations with NumPy
- Useful NumPy Functions for Data Science
- Introduction to Data Visualization
- Plotting with Matplotlib
- Seaborn for Statistical Graphics
- Advanced Charts: Heatmaps, Pairplots, and Violin Plots
- Identifying Patterns, Outliers & Trends
- Using Pandas Profiling & Sweetviz
Requirements
- No prior data science experience needed
Who This Course is For
- Anyone who wants to work with data using Python
- Students preparing for data science or analytics careers
- Beginners who want to learn Python for Data Science
- Professionals looking to switch into data analytics or data science
Your Instructor
Muhammad Riaz Uddin
Web Developer | AI | Data Analysis | Web Design
3.0 Instructor Rating
7 Reviews
11,098 Students
31 Courses
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