Coursera - Process Mining: Data science in Action
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File List:
- 3 - 6 - Lecture 2.6- Alpha Algorithm- A Process Discovery Algorithm (25 min.).mp4 54.98 MB
- 2 - 4 - Lecture 1.4- Learning Decision Trees (27 min.).mp4 53.50 MB
- 3 - 8 - Lecture 2.8- Introducing ProM and Disco (25 min.).mp4 52.83 MB
- 3 - 7 - Lecture 2.7- Alpha Algorithm- Limitations (23 min.).mp4 50.55 MB
- 5 - 2 - Lecture 4.2- Alternative Process Discovery Techniques (23 min.).mp4 50.54 MB
- 2 - 3 - Lecture 1.3- How Process Mining Relates to Data Mining (20 min.).mp4 49.57 MB
- 2 - 2 - Lecture 1.2- Different Types of Process Mining (21 min.).mp4 46.29 MB
- 4 - 4 - Lecture 3.4- Dependency Graphs and Causal Nets (21 min.).mp4 44.65 MB
- 5 - 8 - Lecture 4.8- Exploring Event Data (21 min.).mp4 43.31 MB
- 3 - 4 - Lecture 2.4- Transition Systems and Petri Net Properties (21 min.).mp4 42.71 MB
- 5 - 7 - Lecture 4.7- Aligning Observed and Modeled Behavior (18 min.).mp4 42.54 MB
- 4 - 1 - Lecture 3.1- Four Quality Criteria For Process Discovery (19 min.).mp4 42.43 MB
- 4 - 6 - Lecture 3.6- Learning Causal nets and Annotating Them (18 min.).mp4 40.76 MB
- 2 - 6 - Lecture 1.6- Association Rule Learning (18 min.).mp4 40.64 MB
- 4 - 8 - Lecture 3.8- Using Regions to Discover Concurrency (18 min.).mp4 40.43 MB
- 2 - 5 - Lecture 1.5- Applying Decision Trees (21 min.).mp4 40.08 MB
- 2 - 1 - Lecture 1.1- Data Science and Big Data (17 min.).mp4 38.99 MB
- 6 - 5 - Lecture 5.5- Mining Social Networks (17 min.).mp4 38.32 MB
- 4 - 2 - Lecture 3.2- On The Representational Bias of Process Mining (17 min.).mp4 37.65 MB
- 3 - 3 - Lecture 2.3- Petri Nets (2-2) (18 min.).mp4 37.57 MB
- 6 - 2 - Lecture 5.2- Mining Decision Points (17 min.).mp4 37.00 MB
- 7 - 1 - Lecture 6.1- Operational Support- Detect, Predict and Recommend (17 min.).mp4 36.73 MB
- 7 - 2 - Lecture 6.2- Getting the Right Event Data (17 min.).mp4 36.05 MB
- 4 - 5 - Lecture 3.5- Learning Dependency Graphs (21 min.).mp4 35.75 MB
- 7 - 4 - Lecture 6.4- Process Mining Software (16 min.).mp4 35.54 MB
- 3 - 5 - Lecture 2.5- Workflow Nets and Soundness (17 min.).mp4 35.49 MB
- 5 - 1 - Lecture 4.1- Two-Phase Process Discovery And Its Limitations (15 min.).mp4 35.14 MB
- 3 - 2 - Lecture 2.2- Petri Nets (1-2) (16 min.).mp4 34.67 MB
- 4 - 7 - Lecture 3.7- Learning Transition Systems (15 min.).mp4 33.60 MB
- 2 - 8 - Lecture 1.8- Evaluating Mining Results (15 min.).mp4 32.77 MB
- 5 - 5 - Lecture 4.5- Conformance Checking Using Token-Based Replay (15 min.).mp4 32.51 MB
- 4 - 3 - Lecture 3.3- Business Process Model and Notation (BPMN) (15 min.).mp4 31.93 MB
- 3 - 1 - Lecture 2.1- Event Logs and Process Models (14 min.).mp4 31.42 MB
- 5 - 6 - Lecture 4.6- Token Based Replay- Some Examples (15 min.).mp4 29.24 MB
- 7 - 8 - Lecture 6.8- Process Models as Maps (12 min.).mp4 28.92 MB
- 2 - 7 - Lecture 1.7- Cluster Analysis (13 min.).mp4 28.61 MB
- 6 - 1 - Lecture 5.1- About the Last Two Weeks of This Course (10 min.).mp4 28.21 MB
- 6 - 8 - Lecture 5.8- Comparative Process Mining Using Process Cubes (13 min.).mp4 27.81 MB
- 6 - 3 - Lecture 5.3- Discovering Data Aware Petri Nets (12 min.).mp4 26.88 MB
- 6 - 4 - Lecture 5.4- Mining Bottlenecks (11 min.).mp4 26.86 MB
- 6 - 7 - Lecture 5.7- Combining Different Perspectives (13 min.).mp4 26.03 MB
- 6 - 9 - Lecture 5.9- Refined Process Mining Framework (11 min.).mp4 25.98 MB
- 5 - 3 - Lecture 4.3- Introduction to Conformance Checking (12 min.).mp4 25.54 MB
- 7 - 3 - Lecture 6.3- Guidelines for Logging (10 min.).mp4 25.18 MB
- 7 - 5 - Lecture 6.5- How to Conduct a Process Mining Project (11 min.).mp4 25.14 MB
- 7 - 9 - Lecture 6.9- Data Science in Action (9 min.).mp4 23.32 MB
- 5 - 4 - Lecture 4.4- Conformance Checking Using Causal Footprints (10 min.).mp4 20.09 MB
- 6 - 6 - Lecture 5.6- Organizational Mining (9 min.).mp4 19.94 MB
- 7 - 7 - Lecture 6.7- Mining Spaghetti Processes (8 min.).mp4 19.77 MB
- 7 - 6 - Lecture 6.6- Mining Lasagna Processes (6 min.).mp4 13.02 MB
Coursera - Process Mining: Data science in Action
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