1: Introduction to Business Analytics
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2: Types of Data
3: Key Roles in Data Analytics
4: Data Sources and Methods of Data Collection
5: Data Cleaning Techniques
6: Data Integration and Transformation
7: Descriptive Statistics
8: Feature Scaling and Normalization
9: Using Python Libraries: Pandas, Matplotlib, Seaborn for Business Analytics
10: Introduction to Identifying Patterns and Trends
11: Introduction to SQL for Business Analytics
12: Probability and Distributions for Business Analytics
13: Hypothesis Testing
14: Statistical Inference for Business Analytics
15: Introduction to Regression Analysis
16: Introduction to Machine Learning
17: Supervised vs. Unsupervised Learning
18: Basic Algorithms: Linear Regression, K-Means Clustering
19: Basic Algorithms: Linear Regression, K-Means Clustering
20: Model Evaluation Metrics
21: Time Series Analysis
22: What is Anomaly Detection?
23: Bias in Variables