PYTHON FOR DATA ANALYSIS & DATA SCIENCE

1. Introduction to Python for Data Analysis (1 hour)

• Overview
  of Python and its applications in data science
• Basics
  of Python programming: variables, data types, and basic operations

2. Working with Libraries (1 hour)

• Introduction
  to essential libraries: NumPy, Pandas, and Matplotlib
• Basic
  operations using NumPy arrays
• Data
  manipulation with Pandas DataFrames
• Basic
  data visualization with Matplotlib

3. Data Cleaning and Preprocessing (1 hour)

• Handling
  missing data
• Removing
  duplicates
• Data
  normalization and scaling

4. Exploratory Data Analysis (1 hour)

• Descriptive
  statistics
• Data
  visualization for analysis
• Correlation
  and covariance

ADVANCED DATA ANALYSIS WITH PRACTICAL DATASETS
(5 HOURS)

1. Recap of Python for Data Analysis (1 hour)

• Brief
  review of Python basics and key libraries (NumPy, Pandas, Matplotlib)

2. Importing and Exploring Datasets (1 hour)

• Reading
  data from various sources (CSV, Excel, SQL)
• Exploring
  dataset structure, dimensions, and basic statistics

3. Data Cleaning and Pre-processing (1 hour)

• Handling
  missing values
• Dealing
  with outliers
• Data
  transformation and feature engineering

4. Advanced Data Visualization (1 hour)

• Utilizing
  Seaborn for advanced visualization
• Creating
  interactive visualizations with Plotly

5. Statistical Analysis and Hypothesis Testing (1 hour)

• Introduction
  to statistical concepts
• Performing
  hypothesis tests using Python (e.g., t-tests)

6. Practical Data Analysis Project (1 hour)

• Guided
  analysis of a real-world dataset
• Applying
  learned concepts to solve a specific problem

Iris Dataset

• Description:
  Measurements of sepal length, sepal width, petal length, and petal width
  for three species of iris flowers
• Domain:
  Botany
• Use:
  Classification, basic statistical analysis, visualization

Titanic Dataset

• Description:
  Passenger information on the Titanic, including survival status, class,
  gender, and age
• Domain:
  Transportation
• Use:
  Survival analysis, categorical analysis, visualization

Boston Housing Dataset

• Description:
  Housing prices and various factors affecting them in Boston suburbs
• Domain:
  Real Estate
• Use:
  Regression analysis, correlation analysis, visualization

Wine Dataset

• Description:
  Chemical analysis results of wines from three different cultivars
• Domain:
  Food and Beverage
• Use:
  Classification, cluster analysis, visualization

Diabetes Dataset

• Description:
  Various health metrics for diabetes patients
• Domain:
  Healthcare
• Use:
  Regression analysis, correlation analysis, visualization

Heart Disease UCI Dataset

• Description:
  Patient data related to heart disease
• Domain:
  Healthcare
• Use:
  Classification, statistical analysis, visualization

Breast Cancer Wisconsin (Diagnostic) Dataset

• Description:
  Biopsy results for breast cancer diagnosis
• Domain:
  Healthcare
• Use:
  Classification, statistical analysis, visualization

Penguins Dataset

• Description:
  Measurements and characteristics of penguin species
• Domain:
  Biology
• Use:
  Classification, cluster analysis, visualization