What You Need to Know Before
You Start
Starts 4 July 2025 09:40
Ends 4 July 2025
00
Days
00
Hours
00
Minutes
00
Seconds
9 hours
Optional upgrade avallable
Not Specified
Progress at your own speed
Paid Course
Optional upgrade avallable
Overview
Are you looking to learn how to do Data Mining like a pro? Do you want to find actionable business insights using data science and analytics and explainable artificial intelligence?You have come to the right place.
Syllabus
- Introduction to Data Mining and Business Analytics
- Setting Up Your Python Environment
- Data Preparation and Exploration
- Data Mining Techniques
- Business Analytics Applications
- Explainable Artificial Intelligence (XAI)
- Advanced Topics in Data Analysis
- Deploying Data Mining Models
- Project Work
- Conclusion and Future Directions
Overview of Data Mining
Importance of Data Mining in Business
Introduction to Business Analytics
Tools and Technologies Used
Installing Python and Jupyter Notebook
Overview of Essential Python Libraries (Pandas, NumPy, Matplotlib, Sci-kit Learn)
Collecting and Importing Data
Data Cleaning and Preprocessing
Exploratory Data Analysis (EDA)
Handling Missing Data and Outliers
Supervised Learning Techniques
Classification (Logistic Regression, Decision Trees, Random Forests)
Regression Analysis
Unsupervised Learning Techniques
Clustering (K-Means, Hierarchical Clustering)
Association Rule Mining
Dimensionality Reduction (PCA)
Market Basket Analysis
Customer Segmentation
Sales Forecasting
Predictive Maintenance
Understanding Model Interpretability
Tools and Techniques for Explainability (e.g., LIME, SHAP)
Time Series Analysis
Text Mining and Sentiment Analysis
Anomaly Detection
Model Evaluation and Validation
Implementing Models in Business Environments
Real-world Business Case Study
Data Mining Project Design and Execution
Presentation of Business Insights and Recommendations
Emerging Trends in Data Mining and Analytics
Continuous Learning Resources and Next Steps
Taught by
Diogo Alves de Resende
Subjects
Data Science