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<p>Looking to enhance your energy engineering background with cutting-edge digital techniques? EIT InnoEnergy provides training in fields such as data science, AI, data-driven decision making, and digital business &amp; venturing.</p>
<p>&nbsp;</p>
<p>By completing these courses, you will be equipped with the necessary skills to drive digital transformation within the energy sector and secure promising career opportunities as energy analysts at major consulting companies or as digital pioneers at start-ups or large enterprises. You will also obtain a master-level certificate in data science &amp; AI for energy.</p>
<p>&nbsp;</p>
<p>EIT InnoEnergy master&#8217;s students can benefit from these courses free-of-charge*.</p>
<p>&nbsp;</p>
<p>*<em>The cost of these courses is covered by the participation fee of the master&#8217;s programmes.</em></p>


Build a digital toolkit for your career in energy

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<div>
  
<div>
  <div>Analyse, forecast and optimise energy flexibility and demand.</div>
  <div><p><img loading="lazy" decoding="async" class="alignnone wp-image-269932 size-full" src="http://eit.innoenergy.com/wp-content/uploads/2023/05/52079901354_3fa8065925_c-1.jpg" alt="" width="799" height="533" srcset="https://eit.innoenergy.com/wp-content/uploads/2023/05/52079901354_3fa8065925_c-1.jpg 799w, https://eit.innoenergy.com/wp-content/uploads/2023/05/52079901354_3fa8065925_c-1-300x200.jpg 300w, https://eit.innoenergy.com/wp-content/uploads/2023/05/52079901354_3fa8065925_c-1-768x512.jpg 768w" sizes="(max-width: 799px) 100vw, 799px" /></p>
<p>&nbsp;</p>
<p>This course offers a unique opportunity to analyse, forecast, and optimise energy flexibility and demand using data science and artificial intelligence techniques. The course focuses on practical use cases in the energy sector, providing a comprehensive introduction to data science with a hands-on approach. Participants will learn how to use Python and other tools to analyse and visualise energy demand data, as well as how to share their results with other stakeholders using advanced dashboards.</p>
<p>&nbsp;</p>
<p>Throughout the course, students will gain practical knowledge of state-of-the-art tools for monitoring and experimenting with energy datasets. They will also explore the limitations of machine learning models and how they rely on time series and statistical principles to forecast energy demand. Participants will learn how to optimize the behavior of energy flexible resources using arbitrary cost functions, tracking their experiments using cutting-edge tools.</p>
<p>&nbsp;</p>
<p>Designed based on industry requirements and feedback from hundreds of learners, this course is the fifth iteration of a successful collaboration between EIT InnoEnergy and several leading European partner universities, including KU Leuven, KTH, UPC, and Grenoble INP.</p>
<p>&nbsp;</p>
<p>The Data Science &amp; AI for energy engineers course offered in summer 2024 is powered by:</p>
<p>&nbsp;</p>
<p><img loading="lazy" decoding="async" class="alignnone size-full wp-image-284215" src="http://eit.innoenergy.com/wp-content/uploads/2024/02/Data-and-AI-logos.png" alt="" width="671" height="146" srcset="https://eit.innoenergy.com/wp-content/uploads/2024/02/Data-and-AI-logos.png 671w, https://eit.innoenergy.com/wp-content/uploads/2024/02/Data-and-AI-logos-300x65.png 300w" sizes="(max-width: 671px) 100vw, 671px" /></p>
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<div>
  <div>Overview</div>
  <div><p><strong>Course dates: </strong>22 July &#8211; 02 August 2024</p>
<p>&nbsp;</p>
<p><strong>Effort Level:</strong> 60 to 80 hours, spread over two weeks. Sessions take place from Monday to Friday from 09.30 &#8211; 17.30 CET.</p>
<p>&nbsp;</p>
<p><strong>Course costs:  </strong>3,950 EUR</p>
<p>&nbsp;</p>
<ul>
<li>This course is free of charge for <span style="text-decoration: underline;">EIT InnoEnergy master&#8217;s students</span></li>
<li>The summer 2024 edition of the course is also free of charge for PhD researchers from affiliated universities (KU Leuven, G-INP, UPC, KTH)</li>
<li>Limited seats available for early-stage PhD researchers, academics and industrial participants.  Get in touch with <span class="ui-provider a b c d e f g h i j k l m n o p q r s t u v w x y z ab ac ae af ag ah ai aj ak" dir="ltr"><a href="mailto:contact.sea@innoenergy.com">contact.sea@innoenergy.com</a> for information on customised prices.</span></li>
</ul>
<p>&nbsp;</p>
<p><strong>Delivery: </strong>Hybrid course offered online and face-to-face at KU Leuven. Additional face-to-face sessions at other EIT InnoEnergy partner locations such as KTH Royal Institute of Technology may become available depending on course demand.</p>
<p>&nbsp;</p>
<p><strong>Pre-requisites:</strong></p>
<ul>
<li>Proficiency in a programming language, preferably Python (e.g., familiarity with control commands and loops, etc.). Experience with advanced concepts such as object-oriented programming or deployment is not required. Useful resources will be provided for students not meeting this criterion, to be completed before the start of the course.</li>
<li>Understanding of core concepts in energy and power engineering (e.g., how the grid is organised etc.)</li>
</ul>
<p>&nbsp;</p>
<p><strong>Registration: </strong>registrations will be opened from 15 March &#8211; 15 April 2024.</p>
<p>The final results of the application process will be communicated to applicants in early June 2024.</p>
<p>&nbsp;</p>
<p><strong>Financial support:</strong></p>
<p>InnoEnergy MSc and PhD students can apply for a fee waiver and/or a travel grant (up to 500 euros per student) to cover travel and accommodation expenses in Leuven. Grants are awarded based on a motivation statement submitted by students on the application form.</p>
<p>&nbsp;</p>
</div>
  <div>Register here</div>
  
</div>

<div>
  <div>Who is the course for?</div>
  <div><p>This course on energy data science is designed for <strong>EIT InnoEnergy master&#8217;s students</strong> who wish to learn how to streamline existing workflows and develop new services through data-driven decision making.</p>
<p>The course content is applicable to a wide range of energy careers, including working in energy aggregators, system operators, and utilities.</p>
<p>Students of the <a href="https://eit.innoenergy.com/eit-innoenergy-home-page/for-students/master-school/masters-in-energy-for-smart-cities/" target="_blank" rel="noopener">Master&#8217;s in Energy for Smart Cities</a> obtain 3 ECTS from following this course.</p>
<p>&nbsp;</p>
<p>Limited seats are available for early-stage PhD researchers for the summer 2024 edition of the course. Please get in touch with <span class="ui-provider a b c d e f g h i j k l m n o p q r s t u v w x y z ab ac ae af ag ah ai aj ak" dir="ltr"><a class="fui-Link ___1rxvrpe f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1hu3pq6 f11qmguv f19f4twv f1tyq0we f1g0x7ka fhxju0i f1qch9an f1cnd47f fqv5qza f1vmzxwi f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn" title="mailto:contact.sea@innoenergy.com" href="mailto:contact.sea@innoenergy.com" target="_blank" rel="noreferrer noopener" aria-label="Link contact.sea@innoenergy.com"><u>contact.sea@innoenergy.com</u></a> for information on special price and admission. </span></p>
<p>&nbsp;</p>
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<div>
  Philippe Bergin, Technical Competences Director Global Technology Schneider Electric  <p>As an impact company, Schneider Electric is committed to address one of the biggest challenges of our time: Climate Change.  With Intencity, we put all our expertise to build an environmental-friendly building, which makes the most of data, A.I., solar panels, wind turbines, building management System…</p>
<p>&nbsp;</p>
<p>We are very proud to share this project with the EIT InnoEnergy students. They are part of this innovative journey as they are asked to provide new ideas which will contribute to make this building even smarter.</p>
    </div>

<div>
  <div>How will you learn?</div>
  <div><p>The course follows an immersive learning approach, combining theory and practice with lectures, in-class discussions, and practical lab sessions. Learners will gain a comprehensive understanding of the many different use cases of data in the energy sector, as well as hands-on knowledge and skills in analysing, forecasting, and optimising energy demand data using Python tools. The course will conclude with a real-life application of data science, i.e. the prediction of future thermal energy demand.</p>
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</div>

<div>
  <div>What will you achieve? </div>
  <div><ul>
<li>A broad understanding of the many different use cases of data in the energy domain.</li>
<li>Concrete knowledge and skills to analyse, forecast and optimise energy demand data, as well as ways to track the end-to-end data pipeline and share your results with relevant stakeholders.</li>
<li>Certificate from EIT InnoEnergy and KU Leuven.</li>
</ul>
</div>
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</div>

<div>
  <p>      </p>
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Data science & AI for energy engineers

<div>
  
<div>
  <div>Extract business value from data analyses</div>
  <div><p><img loading="lazy" decoding="async" class="alignnone wp-image-270124 size-full" src="http://eit.innoenergy.com/wp-content/uploads/2023/05/52079901004_386f00f09d_c.jpg" alt="" width="799" height="533" srcset="https://eit.innoenergy.com/wp-content/uploads/2023/05/52079901004_386f00f09d_c.jpg 799w, https://eit.innoenergy.com/wp-content/uploads/2023/05/52079901004_386f00f09d_c-300x200.jpg 300w, https://eit.innoenergy.com/wp-content/uploads/2023/05/52079901004_386f00f09d_c-768x512.jpg 768w" sizes="(max-width: 799px) 100vw, 799px" /></p>
<p>&nbsp;</p>
<p>This comprehensive course on data-driven business decision making is designed to equip you with the skills required to extract and argue business value from data analyses. In today&#8217;s digital energy industry, it is essential to be able to present your recommendations convincingly to business decision makers. This course helps you become a change enabler in this industry by developing the necessary soft skills to work in teams, delegate, prioritise, and drive projects to completion.</p>
<p>&nbsp;</p>
<p>The course is designed to give you practical skills that you can apply immediately in the workplace. It also equips you with tools to recognise new business opportunities driven by digitalisation in energy. You will learn how to create compelling arguments and communicate effectively with business managers. The course includes working on a chosen company case, where you will develop a deeper understanding of the business, and you will learn to create and deliver compelling presentations to business managers.</p>
<p>&nbsp;</p>
<p>This course is offered in cooperation with EIT InnoEnergy partners Aalto Advisors and Aalto University.</p>
</div>
  <div></div>
  
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<div>
  <div>Overview</div>
  <div><p><strong>Course dates:</strong> 10 October 2023 – 16 November 2023.</p>
<p>&nbsp;</p>
<p><strong>Effort Level:</strong> 81 hours.</p>
<ul>
<li>Preparatory reading: 28 hours.</li>
<li>Interative learning sessions + coaching and teamwork: 24 hours (6 weeks, 2 x 2 hours per week)</li>
<li>Independent project work: 29 hours.</li>
</ul>
<p>&nbsp;</p>
<p><strong>Delivery:</strong> Online course offered two times per week from 16.00 &#8211; 18.00 each day.</p>
<p>&nbsp;</p>
<p><strong>Pre-requisites:</strong>Preparatory activities helping to acquire pre-requisite knowledge for the live online sessions are provided as an online package prior to the live online period.</p>
<p>&nbsp;</p>
<p><em>This course is currently only available to EIT InnoEnergy master&#8217;s students. </em></p>
</div>
  <div>Register here</div>
  
</div>

<div>
  <div>Who is the course for?</div>
  <div><p>This course on data-driven business decision making is designed for <strong>EIT InnoEnergy master&#8217;s students </strong>who are interested in developing the skills necessary to extract business value from data analyses and persuasively argue their recommendations to business decision-makers.</p>
</div>
  <div></div>
  
</div>

<div>
  <div>How will you learn?</div>
  <div><p>The course uses modern interactive pedagogical methods, including case teaching, learning by doing, videos, flipped classrooms, coaching, and workshops. Throughout the participants will be working on real-life cases.</p>
<p>&nbsp;</p>
<p>This course builds upon the following values in its teaching and pedagogical methods:</p>
<p>&nbsp;</p>
<ul>
<li>Multi-disciplinary (enables integrated learning paths from technology to business)</li>
<li>Industry-relevant (course staff has practical business experience from various industries)</li>
<li>Interactive (students are coached by senior experts with both industry and academic experience)</li>
<li>Applied (focus on applying tools and methods of business, rather than teaching the tools and methods themselves.</li>
</ul>
<p>&nbsp;</p>
<p>Students will be assessed based on preparatory reading assignment, live online participation, and final presentation.</p>
</div>
  <div></div>
  
</div>

<div>
  <div>What will you achieve? </div>
  <div><ul>
<li>Understanding of how to extract and argue business value from data analyses and how to present and convince business decision makers to follow your recommendations.</li>
<li>Necessary business and soft skills to become a change enabler and leader in the energy industry.</li>
<li>Course completion certificate by EIT InnoEnergy.</li>
</ul>
</div>
  <div></div>
  
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</div>

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<div>
  <p>  </p>
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Data-driven business decision making

<div>
  
<div>
  <div>Develop new business driven by digitalisation in energy</div>
  <div><p><img loading="lazy" decoding="async" class="alignnone wp-image-270144 size-full" src="http://eit.innoenergy.com/wp-content/uploads/2023/05/52079901114_583ea50e4b_c.jpg" alt="" width="799" height="533" srcset="https://eit.innoenergy.com/wp-content/uploads/2023/05/52079901114_583ea50e4b_c.jpg 799w, https://eit.innoenergy.com/wp-content/uploads/2023/05/52079901114_583ea50e4b_c-300x200.jpg 300w, https://eit.innoenergy.com/wp-content/uploads/2023/05/52079901114_583ea50e4b_c-768x512.jpg 768w" sizes="(max-width: 799px) 100vw, 799px" /></p>
<p>&nbsp;</p>
<p>Digital Business and Venturing for Energy Engineers is a tailored course that equips energy engineers with critical business and venturing skills needed in the rapidly developing digital environment. The course aims to enable participants to develop new digital businesses, become entrepreneurs or promote innovations within an existing company. This course is particularly recommended for those participating in the EIT InnoEnergy entrepreneurship competition, Battle of Green Talent.</p>
<p>&nbsp;</p>
<p>Throughout the course, participants will learn how to recognise new business opportunities driven by digitalisation in energy and understand digital technologies that have an impact on the energy sector. Students will also discover the success factors of business models in the energy industry by analysing real-world business cases and applying their learnings to a business idea. Additionally, the course addresses must-know business themes for any growth business leader in the energy sector, such as financial statements, business strategy, company financing, and innovation management. Students will develop interaction and presentation skills, as well as master financial literacy, financial modeling, capital budgeting, opportunity recognition, value creation and capture, intellectual property rights, business plans, digitalisation and digital transformation.</p>
<p>&nbsp;</p>
<p>This course is offered in cooperation with EIT InnoEnergy partner Aalto Advisors.</p>
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<div>
  <div>Overview</div>
  <div><p><strong>Course dates:</strong> 21 February &#8211; 15 March 2024.</p>
<p>&nbsp;</p>
<p><strong>Delivery:</strong> Live online course.</p>
<p>&nbsp;</p>
<p><strong>Course costs:  </strong>1,950 EUR (this course is free of charge for EIT InnoEnergy master’s students)</p>
<p>&nbsp;</p>
<p><strong>Schedule:</strong> every Wednesday and Friday from 18.00 &#8211; 20.00 CET.</p>
<p>&nbsp;</p>
<p><strong>Effort Level: </strong>54 hours (equivalent to 2 ECTS)</p>
<ul>
<li>Live online sessions: 16 hours.</li>
<li>Applying the learnings to your own business case: 38 hours.</li>
</ul>
<p>&nbsp;</p>
<p><strong>Pre-requisites: </strong>This course is open only to first and second year students of EIT InnoEnergy Master&#8217;s programmes.*</p>
<p>&nbsp;</p>
<p><em>*Registration for 2024 edition is closed.</em></p>
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<div>
    <p>During the course &#8216;Digital Business &amp; Venturing for Energy Engineers&#8217;, we got a lot of insights on innovation, strategy, intellectual property rights and finance.</p>
  SIVARAMAN KARTHIKEYAN  </div>

<div>
  <div>What will you learn?</div>
  <div><p>You will learn how to implement the following activities in an energy startup:</p>
<ul>
<li>Pricing &amp; revenue generation</li>
<li>Value capture &amp; value proposition</li>
<li>Go-to-market strategy</li>
<li>Product development</li>
</ul>
<p>&nbsp;</p>
<p>Intended learning outcomes are as follows:</p>
<p>&nbsp;</p>
<ul>
<li>How to implement pricing &amp; revenue generation in an energy startup (week 1)</li>
<li>How to implement value capture &amp; value proposition in an energy startup (week 2)</li>
<li>How to implement go-to-market strategy in an energy startup (week 3)</li>
<li>How to implement product development in an energy startup (week 4)</li>
</ul>
</div>
  <div></div>
  
</div>

<div>
  <div>How will you learn?</div>
  <div><p><i><span style="color: black;">Digital Business and Venturing for Energy Engineers</span></i><span style="color: black;"> uses modern interactive pedagogical methods, including coaching, learning by doing, and flipped classrooms. </span></p>
<p><span style="color: black;"> </span></p>
<p><span style="color: black;">In the beginning of each week, students receive an assignment to implement weekly thematic learnings in their own projects. Students present the results of the assignments on Fridays during flipped classroom sessions, followed by discussion and coaching aimed at improving the students’ own projects. If a student does not have a venture creation project, the student can also complete the weekly assignment by presenting on Friday the key takeaways from the Wednesday sessions. The students can work in teams or individually to complete the weekly assignments. The results of the assignments are presented in the form of a brief slide show presentation. </span></p>
<p>&nbsp;</p>
<p><span style="color: black;">Wednesday sessions are focused on industry examples and theoretical frameworks. Friday sessions are focused on flipped classrooms, in which students present the completed weekly assignments, followed by discussion and coaching. </span></p>
</div>
  <div></div>
  
</div>

<div>
  <div>What will you achieve? </div>
  <div><ul>
<li>Concrete knowledge and skills in digital business and venturing in the energy industry.</li>
<li>Certificate of achievement from EIT InnoEnergy.</li>
</ul>
</div>
  <div></div>
  
</div>

<div>
  <p> </p>
</div>


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Digital business & venturing for energy engineers

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<p>The Engineering and Business Case powered by InnoEnergy (E&#038;BC) is all about real-life interaction between our students and businesses in the renewable energy sector.</p>


<div>
  
<div>
  <div>Build a digital toolkit for your career in energy</div>
  <div><p>Looking to enhance your energy engineering background with cutting-edge digital techniques? EIT InnoEnergy provides training in fields such as data science, AI, data-driven decision making, and digital business &amp; venturing.</p>
<p>&nbsp;</p>
<p>By completing these courses, you will be equipped with the necessary skills to drive digital transformation within the energy sector and secure promising career opportunities as energy analysts at major consulting companies or as digital pioneers at start-ups or large enterprises. You will also obtain a master-level certificate in data science &amp; AI for energy.</p>
<p>&nbsp;</p>
<p>EIT InnoEnergy master&#8217;s students can benefit from these courses free-of-charge*.</p>
<p>&nbsp;</p>
<p>*<em>The cost of these courses is covered by the participation fee of the master&#8217;s programmes.</em></p>
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<div>
  <p></p>
  <p>Courses to boost your digital skills</p>
  <div></div>
  <div></div>
      <ul>
              <li>
          <div>Programme title: Data science &#038; AI for energy engineers</div>
        </li>
              <li>
          <div>Programme title: Data-driven business decision making</div>
        </li>
              <li>
          <div>Programme title: Digital business &#038; venturing for energy engineers</div>
        </li>
          </ul>
  </div>

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InnoEnergy Masters+

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<p>Looking to enhance your energy engineering background with cutting-edge digital techniques? Our master&#8217;s programmes provide complementary training for EIT InnoEnergy students in fields such as Data Science for Energy Engineers, Business Decision Making &amp; Data Analyses, and Digital Business &amp; Venturing for Energy Engineers.</p>
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<p>By completing these courses, students will be equipped with the necessary skills to drive digital transformation within the energy sector and secure promising career opportunities as energy analysts at major consulting companies or as digital pioneers at start-ups or large enterprises.</p>
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<p>All our programmes have real-life challenges embedded in their curricula. Read more here.</p>


Looking to enhance your energy engineering background with cutting-edge digital techniques? Our programmes provides free-of-cost training sessions for EIT InnoEnergy students in fields such as Data Science for Energy Engineers, Business Decision Making & Data Analyses, and Digital Business & Venturing for Energy Engineers.

Complementary training in digital skills

Data science & AI for energy track