Data engineering for mechanical engineers

Summary

This comprehensive course covers the essentials of databases, data processing, and cloud computing, along with specialised topics such as big data handling, data pipelining, and database design. You will delve into the world of IoT data, learn to design event-driven data systems, and understand the security best practices when working with data.

As the world of mechanical engineering evolves, embracing the digital revolution with Industry 4.0, IoT, and big data becomes not just an advantage but a necessity. This course is designed to equip you with the essential skills to step beyond traditional tools like Excel, enabling you to manage and leverage measurement data like never before.

Attendance of this course provides skills to efficiently collect, process and analyse data from a variety of sources using cutting edge tools and methodologies. Attendees will familiarise themselves with data warehousing and data streaming and develop practical skills in Python scripting, working in terminal, writing SQL queries and executing comprehensive data wrangling as well as the use of webservices. 

This course is an essential step for mechanical engineers ready to harness the power of data engineering to revolutionise their approach to mechanical design, maintenance, and innovation.

Enhancing their capability to design, implement and maintain sophisticated data systems in today’s competitive job market, where data proficiency is a key asset in engineering roles.

Pre-requisite course

This course assumes basic experience with Python and Python Package Manager. You can complete our Foundation Python course to prepare for this course.

Take your data expertise further

Who should attend?

This course is ideal for:

• Mechanical engineers looking to enhance their data handling capabilities and adapt to the digital transformation in engineering.
• Professionals in the mechanical engineering field seeking to leverage data engineering techniques for better system design, implementation, and maintenance.
• Individuals interested in expanding their skill set beyond traditional analysis tools like Excel, to include Python programming, advanced SQL, and data wrangling with modern tools and technologies.

 

How will I benefit?

After the course you will be able to:

• Manage and process large datasets beyond the capacity of traditional tools like Excel.
• Gain proficiency in Python for data processing, advanced SQL queries, and the use of key data libraries such as NumPy and pandas.
• Work with diverse data forms and sources, including IoT sensors and online APIs.
• Understand the data pipelinging workflow.
• Understand the pitfalls of data processing and issues that may go under the radar.
• Design, model and create databases.
• Understand how to design data warehouse system architecture-physical and logical.
  

Key topics

• Fundamentals of data engineering in the context of engineering systems.
• Python programming for data engineering, including libraries like NumPy and pandas.
• Advanced SQL operations for data storage and analysis.
• Real-time data collection from IoT sensors and their integration with Azure services.
• Techniques for complex data retrieval and management.
• Working with different types of engineering datasets.
• Strategies for efficient problem-solving in scripts.

Meet our trainers

These trainers regularly teach Data engineering for mechanical engineers.