@@ -163,6 +163,8 @@ Enable students to **plan, conduct, and complete a research project** applying k
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164164Statistic Review - Stats Measures - Mean - Median - Mode - Variance] ( )
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166+ https://github.com/Quantum-Software-Development/7-DataMining-Regression-Techniques-Data-Integration
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166168## [ Weekly Schedule] ( )
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@@ -175,18 +177,19 @@ Statistic Review - Stats Measures - Mean - Median - Mode - Variance]()
175177| 4 | [ Data Mining - Concepts - Exploratory Analysis] ( https://github.com/Quantum-Software-Development/4-DataMining_Concepts_ExploratoryAnalysis ) | Active methodology | Python - R |
176178| 5 | [ Data Cleaning - Preparation - Anomalies (Outliers)] ( https://github.com/Quantum-Software-Development/5-DataMining_DataCleaning_Preparation_Anomalies_Outlier ) | Active methodology | Python |
177179| 6 | [ Data Mining - Pre Processing] ( https://github.com/Quantum-Software-Development/6-DataMining_Pre-Processing ) | Active methodology | Python |
178- | 7 | [ Predictive analysis] ( https://github.com/Quantum-Software-Development/7-DataMining_XXX ) | Active methodology | Python |
179- | 8 | Clustering techniques | Active methodology | Python |
180- | 9 | Clustering techniques | Active methodology | Python |
181- | 10 | ** P1 Exam** | Written (Individual) | – |
182- | 11 | K-Means algorithm | Active methodology | Python |
183- | 12 | Affinity Propagation | Active methodology | Python |
184- | 13 | Mean-Shift algorithm | Active methodology | Python |
185- | 14 | Principal Component Analysis (PCA) | Active methodology | Python |
186- | 15 | Dictionary Learning | Active methodology | Python |
187- | 16 | ** P2 Exam** | Written (Individual) | – |
188- | 17 | ** P3 Exam & Grade Closure** | Written (Individual) | – |
189- | 18 | Final grade submission | – | – |
180+ | 7 | [ Regression Techniques with Data Integration] ( https://github.com/Quantum-Software-Development/7-DataMining-Regression-Techniques-Data-Integration ) | Active methodology | Python |
181+ | 8 | [ Predictive analysis] ( ) | Active methodology | Python |
182+ | 9 | Clustering techniques | Active methodology | Python |
183+ | 10 | Clustering techniques | Active methodology | Python |
184+ | 11 | ** P1 Exam** | Written (Individual) | – |
185+ | 12 | K-Means algorithm | Active methodology | Python |
186+ | 14 | Affinity Propagation | Active methodology | Python |
187+ | 14 | Mean-Shift algorithm | Active methodology | Python |
188+ | 15 | Principal Component Analysis (PCA) | Active methodology | Python |
189+ | 16 | Dictionary Learning | Active methodology | Python |
190+ | 17 | ** P2 Exam** | Written (Individual) | – |
191+ | 18 | ** P3 Exam & Grade Closure** | Written (Individual) | – |
192+ | 19 | Final grade submission | – | – |
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