What You'll Learn
- Overview of Python in Data Science
- Variables, Data Types, Lists, Dictionaries
- Control Structures (if/else, loops)
- Functions and Modules
- Introduction to Key Libraries:NumPy, Pandas, Matplotlib
- Data Selection and Filtering
- Handling Missing Data
- Data Transformation and Aggregation
- Descriptive Statistics: Mean, Median, Mode, Variance, Standard Deviation
- Encoding Categorical Variables
- Feature Scaling and Normalization
- Merging and Joining DataFrames
- Introduction to Matplotlib: Line Plots, Bar Charts, Pie Charts
- Introduction to Seaborn: Heatmaps, Pairplots, Violin Plots
- Customizing Visualizations: Titles, Labels, Legends, Colors
- Correlation and Regression Analysis
Requirements
- No prior experience is needed.
Who This Course is For
- Anyone curious about data and looking to explore data-driven problem solving.
- Students and professionals who want to add Python and data analysis skills to their toolkit.
- Who want to start a career in data analysis or data science.
- Business professionals who want to use data for decision-making and insights.
Your Instructor
Brighter Futures Hub
Instructor at Udemy
4.0 Instructor Rating
234 Reviews
23,320 Students
32 Courses
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