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Module 2 (Applications) is only available after completing Module 1 (Introduction), allowing you to confidently build on the foundation you have established. In this second module, you will further expand and deepen the knowledge gained in Module 1 by applying it to realistic Data & AI challenges.

Depending on your chosen track and learning objectives, you will gain practical experience through a complex group project or the AI Case Study Lab. In the group project, you work with a multidisciplinary team to develop a realistic Data & AI solution, supported by experienced practitioners and technical and domain experts. In the AI Case Study Lab, you analyse and evaluate real-world AI cases, with particular attention to project definition, implementation choices and the role of the Analytics Translator.

You can read more about the group project and the AI Case Study Lab on this page.

Your CORE curriculum:

• Introduction to Data & AI (module 1)
• Data & AI Strategy in your organizatoin (pt. 1 - 3)
• Time series forecasting
• Modern Data Engineering pt. 2
• Pitching / Presentation Skills
• Stakeholder & Change Management
• Visualisation pt. 1 & pt. 2
• Language creates meaning
• Advanced Data Modelling
• Intervision
• Natural Language Processing (NLP)
• Sector-specific electives

Further details about the content of the core courses can be provided during the information session or in a personal conversation. 

The Applications module allows participants to tailor their program to specific learning objectives and challenges within their organization. The list below provides an indication of the current range of electives, which may change from time to time:

• Stakeholder & Change Management
• NLP & Deep Learning
• Ethics & Responsible AI
• Generative AI / AI Agents
• Experimentation
• Monitoring
• GDPR / EU AI Act
• Procurement Strategy for Digitalization

More details about the content and relevance of the electives will be shared during the information session or in a personal consultation. No rights can be derived from the above description of the curriculum.

In Applications of Data & AI, you move beyond theory and apply your knowledge to realistic AI challenges. Depending on your chosen track and learning objectives, you can deepen your practical experience through a group project or the AI Case Study Lab.

WORK ON A REAL-LIFE CASE IN THE GROUP PROJECT 
For participants in the Expert track, the group project is an important part of the program. Together with a multidisciplinary team, you work on a complex, real-life case involving an actual case owner or stakeholder, relevant data and a meaningful business challenge.
The project closely resembles a real business environment. Teams translate the challenge into a structured Data & AI project, collaborate effectively and work towards valuable, actionable outcomes.

Throughout the project, each team is supported by an experienced practitioner. The practitioner helps participants achieve both their individual and team learning objectives and provides guidance on technical and substantive questions related to the group project.

Participants in the Business Manager track can choose to join the group project in the role of Business Manager. In this role, they actively contribute to project definition and data understanding. They also connect the business challenge to the technical work, safeguard stakeholder interests and challenge the Experts to critically substantiate their choices, assumptions and proposed solutions.
 

ANALYSE AND EVALUATE CASES IN THE AI CASE STUDY LAB
Depending on their learning objectives, Business Managers can also choose to participate in the AI Case Study Lab. In this lab, participants explore multiple real-world case studies from a variety of domains.
Because the outcomes of these cases are already known, participants can examine the decisions and results in greater depth. This creates room for critical reflection: What worked? What did not? Which implementation choices were made, and why?

The AI Case Study Lab places particular emphasis on the role of the Analytics Translator. You learn how to analyse, structure and assess AI initiatives, with additional attention to key phases of the CRISP-DM model, including business understanding, project definition, evaluation and implementation.

• Completed Bachelor鈥檚 and/or Master鈥檚 degree and several years of work experience.
• Ambition to grow in senior professional position, combining technical expertise with skills in leadership, entrepreneurship, complex problem solving and critical thinking.

Certificate

Certified Data Scientist or Certified Analytics Translator. Certificates issued by the Scientific Director EAISI, Prof. dr. ir. Wim Nuijten and the Program Director dr. Daniel Kapitan. The certificate will be awarded during a ceremony where employers and loved ones are warmly welcome.

黑料福利网 CAMPUS: Eindhoven Artificial Intelligence Systems Institute (EAISI) 鈥� Building: Neuron. To ensure the best possible learning experience, physical presence on campus is required on lecture days (Fridays). The program is not designed to be followed online. The exact dates depend partly on the chosen elective courses. 

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THIS PROGRAM IS A COLLABORATION BETWEEN EAISI ACADEMY AND JADS