Computational Learning Theory and Beyond
In this course you will be introduced to computational learning theory and get a glimpse of other research towards a theory of artificial intelligence.
Our starting point will be a hands-on binary classification task. Basically, this is the challenge of classifying the elements of a given set into two groups (predicting which group each one belongs to) on the basis of given labeled data. Thus the goal of the supervised machine learning algorithms is to derive a correct classification rule. Our interest lies in strategies that work not only for one specific classification task but more universally for a pre-specified set of such. You will get to know a formalization of the aforementioned notions and see illustrating examples. In the main part, you will get to know different learning models which are all based on a modular design. By investigating the learning power of these models and the learnability of the prominent set of half-spaces, we also give arguments for how to choose an appropriate one.
| Provided By | OPEN HPI
 |
| Type of provider | MOOC provider |
| Provided at | OPEN HPI |
| Learning opportunity type | MOOC |
| Language | en |
| Home page | https://open.hpi.de/courses/learningtheory2020 |
| Duration | 1 |
| Workload in hours | 20 |
| Admission procedure | Open to all |
| Assessments | quiz/test |
| Type of credential | Certificate of participation |
| ISCEDF Code | 00 - Generic programmes and qualifications |
| Learning settings | formal learning |
| Learning outcome | machine learning The principles, methods and algorithms of machine learning, a subfield of artificial intelligence. Common machine learning models such as supervised or unsupervised models, semi- supervised models and reinforcement learning models. |
| Related skill | http://data.europa.eu/esco/skill/3a2d5b45-56e4-4f5a-a55a-4a4a65afdc43 |
| Learning outcome | Machine learning – LO – Classify machine Classify machine learning problems |
| Learning outcome type | Skill |
| Reusability level | Sector specific skills and competences |
| Related skill | http://data.europa.eu/esco/skill/8369c2d6-c100-4cf6-bd83-9668d8678433 |
| Learning outcome | Machine learning – LO – Classify supervised Classify supervised learning problems |
| Learning outcome | Machine learning – LO – Classify unsupervised Classify machine learning problems in unsupervised learning |
| Learning outcome | Machine learning – LO – Describe how |
| Learning outcome | Machine learning – LO – Describe the limitations Describe the limitations of machine learning techniques in supervised learning |
| Learning outcome type | Knowledge |
| Reusability level | Sector specific skills and competences |
| Related skill | http://data.europa.eu/esco/skill/e465a154-93f7-4973-9ce1-31659fe16dd2 |
| Learning outcome | Machine learning – LO – Describe the main Describe the main techniques for identifying clusters of data |
| Learning outcome | Machine learning – LO – Describe the utility Describe the utility of dimensionality reduction techniques |
| Learning outcome | Machine learning – LO – Explain Explain what a value function is and how it can be estimated using reinforcement learning |
| Learning outcome | Machine learning – LO – Formulate Formulate a sequential decision-making problem |
| Learning outcome | Machine learning – LO – Identify Identify the key elements of supervised learning algorithms |
| Learning outcome type | Knowledge |
| Reusability level | Cross-sector skills and competences |
| Related skill | http://data.europa.eu/esco/skill/54924a2c-daca-40d3-9716-4b38ceb04f38 |
| Learning outcome | Machine learning – LO – Perform Perform model evaluation and selection in supervised learning |
| Learning outcome | Technologies and platforms for AI – LO – Explain the cloud-based Explain the Cloud-based approaches for AI comprising machine- and deep-learning-as-a-service |
| Learning outcome type | Knowledge |
| Reusability level | sector specific skills and competences |
| Related skill | http://data.europa.eu/esco/skill/bd14968e-e409-45af-b362-3495ed7b10e0 |
| Learning outcome | Technologies and platforms for AI – LO – Identify Identify the Machine and Deep Learning techniques and solutions developed for IoT and Edge Computing systems |
| Learning outcome type | Knowledge |
| Reusability level | Sector specific skills and competences |
| Related skill | http://data.europa.eu/esco/skill/f049d050-12da-4e40-813a-2b5eb6df6b51 |
| Contact form | https://open.hpi.de/pages/contact |
