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@@ -162,6 +162,7 @@ Enable students to **plan, conduct, and complete a research project** applying k
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+
 ##  [Weekly Schedule]()
 
 <br>
@@ -171,7 +172,8 @@ Enable students to **plan, conduct, and complete a research project** applying k
 | 1     | [Course introduction](https://github.com/Quantum-Software-Development/specialized-consulting-data-mining/tree/d737ff164c6b4d6e580d5ba6e95c54ac604f7ea4/class_1-Introduction) | Active methodology | – |
 | 2–3   | [Statistical Review](https://github.com/Quantum-Software-Development/2-3-DataMining_Statistical_Review) | Active methodology | Python |
 | 4     | [Fundamentals of Data Mining](https://github.com/Quantum-Software-Development/4-DataMining_Concepts_ExploratoryAnalysis) | Active methodology | Python |
-| 5–6   | [Data cleaning and preparation](https://github.com/Quantum-Software-Development/5-DataMining) | Active methodology | Python |
+| 5   | [Data Cleaning - Preparation - Anomalies (Outliers)](https://github.com/Quantum-Software-Development/5-DataMining_DataCleaning_Preparation_Anomalies_Outlier) | Active methodology | Python |
+| 6     | [Fundamentals of Data Mining - Pre Processing](https://github.com/Quantum-Software-Development/6-DataMining_Pre-Processing) | Active methodology | Python |
 | 7     | Predictive analysis | Active methodology | Python |
 | 8, 10 | Clustering techniques | Active methodology | Python |
 | 9     |  **P1 Exam** | Written (Individual) | – |