13 KiB
13 KiB
| Week | Ready | Main item | Classes | Student work | ||
|---|---|---|---|---|---|---|
| 1 | Yes | Python Prep | - L1: Introduction and motivation of the course - L2: Simulation, Optimization and Machine Learning in companies |
- Python prep | ||
| 2 | Yes | Case 1 | - L3: Introduction to simulation: What is it, When do we use it, Types of simulation - L4: Simulation examples in Python. Introduction to case 1. |
- Python prep - View Primer: Simulating a pandemic - Read Agent-based modeling: Methods and techniques for simulating human systems - Read case 1. |
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| 3 | Case 1 | - L5: Simulation methodology. - L6: Simulation-based optimization I. Challenges and issues with simulation. Where to go from here - S1: Workshop for case 1 |
- Work on case 1 - Review HASH model market simulation - Review HASH warehouse simulation |
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| 4 | Case 1/2 | - L7: Introduction to optimization - L8: Modeling optimization problems - S2: Workshop for case 1 |
- Work on case 1 - Read Gurobi's Modelling Basics - Read Neos taxonomy of optimization problems - View this video on the Simplex algorithm |
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| 5 | Case 2 | - L9: Taxonomy of optimization techniques - L10: Simulation-based optimization II. Introduction to case 2 |
- Deliver case 1 - Read case 2 - Enjoy watching simulation-based race car training - Read how the 4th most popular database software in the world uses GAs to access data faster. |
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| 6 | Case 2 | - L11: Challenges in real-world usage. Simulation vs Optimization - L12: Introduction to Machine Learning - S3: Workshop for case 2 |
- Work on case 2 - Read this review on simulation optimization techniques and softwares |
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| 7 | Case 2/3 | - L13: Supervised Machine Learning (SML): NIPS - L14: Typical SML workflow. Introduction to case 3 - S4: Workshop for case 2 |
- Work on case 2 - Read case 3 |
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| 8 | Case 3 | - L15: Algorithm deep dive: Decision trees - L16: Feature Engineering and Model Evaluation - S5: Workshop for case 3 |
- Deliver case 2 - View this intro to neural networks and this intro to random forests |
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| 9 | Case 3 | - L17: Deployment of Models - L18: Stories from the trenches: applying all of this in the real world - S6: Workshop for case 3 |
- Work on case 3 - View this video on why businesses fail at ML |
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| 10 | Case 3 | - L19: Where to go from here: further learning and carreer advice - L20: Final Q&A, exam preparation |
- Work on case 3 | |||
| 11 | - Exam | - Deliver case 3 |
| Week | Ready | Main item | Classes | Student work | ||
|---|---|---|---|---|---|---|
| 1 | Yes | Python Prep | - L1: Introduction and motivation of the course - L2: Simulation, Optimization and Machine Learning in companies |
- Python prep | ||
| 2 | Yes | Case 1 | - L3: Introduction to optimization - L4: Case 1 Discussion |
- Python prep - View Primer: Simulating a pandemic - Read Agent-based modeling: Methods and techniques for simulating human systems - Read case 1. |
||
| 3 | Case 1 | - L5: Introduction to simulation: What is it, When do we use it, Types of simulation - L6: Simulation Methodology |
- Work on case 1 - Review HASH model market simulation - Review HASH warehouse simulation |
|||
| 4 | Case 1/2 | - L7: Case 1 Workshop - L8: Simulation-based Optimization I |
- Work on case 1 - Read Gurobi's Modelling Basics - Read Neos taxonomy of optimization problems - View this video on the Simplex algorithm |
|||
| 5 | Case 2 | - L9: Case 2 Discussion - L10: Simulation-based optimization II: GA |
- Deliver case 1 - Read case 2 - Enjoy watching simulation-based race car training - Read how the 4th most popular database software in the world uses GAs to access data faster. |
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| 6 | Case 2 | - L11: Challenges in real-world usage. Stochastic vs Traditional Optimization - L12: Case 2 Workshop |
- Work on case 2 - Read this review on simulation optimization techniques and softwares |
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| 7 | Case 2/3 | - L13: Supervised Machine Learning (SML): NIPS - L14: Typical SML workflow. Introduction to case 3 - S4: Workshop for case 2 |
- Work on case 2 - Read case 3 |
|||
| 8 | Case 3 | - L15: Algorithm deep dive: Decision trees - L16: Feature Engineering and Model Evaluation - S5: Workshop for case 3 |
- Deliver case 2 - View this intro to neural networks and this intro to random forests |
|||
| 9 | Case 3 | - L17: Deployment of Models - L18: Stories from the trenches: applying all of this in the real world - S6: Workshop for case 3 |
- Work on case 3 - View this video on why businesses fail at ML |
|||
| 10 | Case 3 | - L19: Where to go from here: further learning and carreer advice - L20: Final Q&A, exam preparation |
- Work on case 3 | |||
| 11 | - Exam | - Deliver case 3 |