Summary
Confidently visualise and interpret complex datasets, apply statistical methods and hypothesis testing, and leverage machine learning techniques for building several models from data.
In today's data-driven engineering landscape, the ability to effectively use data science techniques is a career defining skill for engineers.
This course is designed to equip engineers with hands-on experience in Python, SQL, and databases. Delegates will also learn to perform data analysis and create impactful visualisations on a variety of datasets.
The course covers areas such as mathematical concepts, statistical hypothesis testing, descriptive and inferential statistics, and the art of storytelling with data. This enables engineers to not only extract meaningful insights from data but also communicate trends and patterns.
Equipped with these skills, engineers will be better positioned to lead data-driven projects, innovate within their fields, and enhance their career prospects in an increasingly data-centric world.
Who should attend?
• Engineers seeking to integrate data science principles into their engineering projects to enhance decision-making and innovation.
• Engineering Managers who wish to understand the potential of data science in optimising team projects and driving efficiency within their engineering processes.
• Engineers looking to transition into data science roles or incorporate data science methodologies into their engineering expertise.
This course assumes basic experience with Python and Python Package Manager. You can complete Foundation Python course to prepare for this course.
Foundation Python
Take your data expertise further. Explore Data science and AI modelling in mechanical engineering applications.
Predictive AI Modelling
Software requirements: Please ensure you are able to download Docker, Python and Visual studio code. Plus the ability to install Python packages including but not limited to: numpy, pandas, scikit-learn, statsmodels, scipy, matplotlib, seaborn, opencv-python, pytorch, requests.
How will I benefit?
After the course you will be able to:
• Learn to use Python and SQL for effective data analysis and visualisation.
• Gain insights into complex statistical methods applicable in engineering.
• Acquire skills to implement machine learning models for mechanical engineering applications.
• Enhance your ability to make data-driven decisions in engineering projects.
• Stay ahead in your field by mastering skills that are increasingly in demand.
• Develop skills to manage and analyse complex engineering datasets.
• Gain proficiency in building, training, and validating AI models.
• Learn to interpret the results of AI models and communicate these insights effectively.
• Stay updated with the latest trends and advancements in AI.
• Improve your ability to work with data in your engineering projects.