Reinforcement Learning

Free of cost

by funding

Reinforcement learning as one of the three main techniques of machine learning describes a learning method in which software is trained to achieve optimal results through direct exchange with its environment in the form of trial and error. Familiarize yourself with the concepts and approaches, but also the challenges of this learning method.
  • Certificates: Reinforcement Learning" certificate
  • Examination: Practical project work with final presentation
  • Teaching Times: Full-time
    Monday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
  • Language of Instruction: German
  • Duration: 4 Weeks

Introduction to reinforcement learning (approx. 1 day)

Definition and basic concepts

Differences to other learning methods

Areas of application and examples


Markov Decision Processes (MDPs) (approx. 2 days)

Definition and properties of MDPs

Value functions and policy

Bellman equations

Dynamic Programming Approach


Q-Learning (approx. 2 days)

Definition and algorithm

Exploration vs. exploitation

Convergence and optimization properties

Applications in games, robotics and other areas


Deep reinforcement learning (approx. 3 days)

Deep Q-Learning

Deep Deterministic Policy Gradients (DDPG)

Actor Critical Methods

Policy Gradient Methods


Advanced topics (approx. 4 days)

Model-Based Reinforcement Learning

Multi-Agent Reinforcement Learning

Inverse Reinforcement Learning

Meta Reinforcement Learning


Practical applications (approx. 3 days)

Implementation of reinforcement learning algorithms

Application to selected problems and case studies

Evaluation and tuning of the algorithms


Summary and outlook (approx. 2 days)

Summary of the most important concepts and results

Challenges and future developments in reinforcement learning


Project work (approx. 3 days)

To consolidate the content learned

Presentation of the project results



Changes are possible. The course content is updated regularly.

Previous knowledge of machine learning and the Python programming language is required.

After completing the course, you will understand the basic concepts of reinforcement learning and know the differences to other learning methods. You will be familiar with Markov decision processes, Q-learning and deep reinforcement learning and will be able to apply advanced topics such as multi-agent and model-based reinforcement learning. You will also be able to implement reinforcement learning algorithms, test them on real-world problems and optimize them.

Computer science, mathematics, electrical engineering and people with a degree in (business) engineering

Reinforcement learning is often used in robotics and automation technology, but also in the automotive industry, e.g. for driver assistance functions, or in the development and optimization of autonomous transport systems. Specialists with the relevant knowledge are in high demand on the job market across all sectors.

Your meaningful certificate provides a detailed insight into the qualifications you have acquired and improves your career prospects.

Didactic concept

Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).

You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.

 

Virtual classroom alfaview®

Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.

 

The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).

We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm
free of charge from all German networks.
Contact
We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm free of charge from all German networks.