### Course Overview
- **Course Title:** Complete Guide to Python Data Analysis with Real Datasets
- **Instructor:** Brighter Futures Hub
- **Target Audience:**
- Beginners in **Python** and **data analysis**
- Professionals seeking **data science** and **data visualization** skills
- Students or analysts needing **real-world dataset** experience
- **Prerequisites:** None
### Curriculum Highlights
- **Key Topics Covered:**
- **Python fundamentals**: Variables, data types, lists, dictionaries
- **Control structures**: `if/else` statements, loops
- **Functions and modules** in Python
- **Core libraries**: **NumPy**, **Pandas**, **Matplotlib**, **Seaborn**
- **Data cleaning**: Handling missing data, duplicates, inconsistent formats
- **Data transformation**: Filtering, aggregation, merging **DataFrames**
- **Descriptive statistics**: Mean, median, mode, variance, standard deviation
- **Feature engineering**: Encoding categorical variables, scaling/normalization
- **Data visualization**:
- **Matplotlib**: Line plots, bar charts, pie charts
- **Seaborn**: Heatmaps, pairplots, violin plots
- Customization (titles, labels, legends, colors)
- **Exploratory data analysis (EDA)**: Correlation, regression analysis
- **Intro to machine learning**: **Scikit-learn** for regression/classification
- **Key Skills Learned:**
- Clean and preprocess **real-world datasets** using **Pandas**
- Perform **statistical analysis** and derive insights
- Create **publication-quality visualizations** with **Matplotlib/Seaborn**
- Apply **basic machine learning** workflows
- Work with datasets from **business, finance, healthcare, sports, social media**
### Course Format
- **Duration:** 3 hours on-demand video
- **Format:** Self-paced **online course** (lifetime access)
- **Resources:**
- **Mobile and TV access**
- **Certificate of completion**
- Hands-on **real dataset projects**
### Special Offer
- **Limited Time Coupon Code:** N/A
