The successful completion of a Course leads to the issuance of a certificate for the learner. Moreover, several Courses can be combined to create a complete learning journey.
The successful completion of a Course leads to the issuance of a certificate for the learner. Moreover, several Courses can be combined to create a complete learning journey.
Sign up for the courses
Please, fill in the registration form below:
ViDi courses are available for 1 month: from the first day until the last day of the month of your choice.
When we assign you to a course, you will receive a notification email, asking you to confirm your account
at the EIT Manufacturing Academy.
Tip: check for email subject “[EIT Manufacturing Academy] New Account on EIT Manufacturing Academy!”
- Click on the link in the email and you will be redirected to the registration page. You will be redirected to the platform.
- Add a new password for your new account and click on Save
- Now your password is updated, click on “Go to EIT Manufacturing Academy”
- You will be redirected to the EIT
- Manufacturing Academy homepage. Click on Login and enter your credentials
- Welcome to your page. To find the Course assigned to you, you must click on your profile icon>Courses>My Courses
- To start a Course, click on its title. Pay attention to start consuming the “Courses” and not “Single Lessons”. At any point of consumption, you can check your progress in a course with the progress bar
What is in it for me?
1. Data Science (DS) Journey
- Gain Comprehensive Knowledge: Learn the full process of implementing a data science project from business understanding to model deployment.
- Boost Strategic Capabilities: Helps managers and engineers rethink and optimize business activities with a data-driven approach.
- Unlock DS Potential: Provides insights into utilizing data science techniques to maximize the value of data in manufacturing.
2. Quality Control in Manufacturing
- Enhance Product Consistency: Leverage data science to reduce product defects and improve consistency.
- Real-World Applications: Practical examples show how data science can identify and address quality control issues effectively.
- Improve Reliability: Achieve higher product reliability, leading to greater customer satisfaction and reduced returns.
3. Predictive Maintenance
- Prevent Equipment Failures: Use data to predict maintenance needs, minimizing unexpected downtimes.
- Extend Machine Life: Implement predictive maintenance to optimize machine performance and longevity.
- Increase Operational Efficiency: Reduce unplanned interruptions, leading to smoother operations and cost savings.
4. Performance Monitoring and Tracking
- Optimize Operational Performance: Track and analyze KPIs to identify areas for process improvement.
- Continuous Improvement: Equip teams with tools for ongoing performance tracking, enabling adjustments in real time.
- Enhanced Decision-Making: Data-backed insights help managers make more informed decisions to keep operations efficient.
5. Supply Chain Management
- Improve Demand Forecasting: Leverage data science for accurate demand prediction and inventory management.
- Reduce Costs and Improve Responsiveness: Optimize supply chain logistics, leading to cost savings and a more agile response to market changes.
- Data-Driven Decisions: Enables a structured approach to supply chain management, enhancing overall efficiency.
Testimonials
“Building this course on data-driven quality control was a hands-on experience for us, and we designed it with a clear goal: to make the digitalization journey accessible and valuable for everyone in manufacturing, regardless of their starting point. We wanted managers to get a sense of what’s possible with data, from boosting process efficiency to spotting hidden improvement opportunities. For those just starting out, we break down the basics; for engineers, we offer a quick, practical dive into real-world applications.”
“The coolest part? The course is built around real-life data from an actual manufacturing partner, so we’re tackling the same kinds of challenges you’d face on the shop floor, not just textbook examples. By weaving in these genuine cases, we’re helping bridge the gap between engineering and IT teams, giving everyone a shared language to talk about data-driven quality. We hope our learners come away feeling confident and ready to turn data insights into action in their own roles.”