This course aims to help learners acquire skills in Exploratory Data Analysis (EDA) and machine learning model development without requiring extensive coding knowledge. It will achieve this by implementing Python AutoML and other low-code open-source libraries. Learners will be introduced to the following concepts during the course:
- Setting up a development environment
- Exploratory Data Analysis
- Development of both supervised and unsupervised machine learning model types, including: Classification / Regression / Clustering / Time Series Forecasting
- How to evaluate the performance and interpret the output of machine learning models using visualisations and other explainable AI methods
The skills that you will acquire whilst on this course are extremely valuable to a myriad of industries and can be used towards building more intelligent and business processes and/ or effective applications, to name a few.
Who Is This Course For
- Aspiring computer scientists looking to explore the power of Artificial Intelligence (AI)
- Computer users who want to develop specific Machine Learning skills for immediate impact, bypassing the commitment of a full degree program.
- Those that are looking to gain the latest, specialized knowledge to stand out in a dynamic job market.
- For complete beginners looking to try something new.
What You'll Learn
- Set up a seamless development environment for Machine Learning applications.
- Master the art of Exploratory Data Analysis (EDA) for effective insights.
- Develop both supervised and unsupervised Machine Learning models for diverse applications.
- Learn to employ visualizations and other explainable AI methods for robust model interpretation.
Course Includes
- 20 hours free tuition
- Certificate on the successful completion of an assessment
- Earn a 10-credit digital badge certification.
Place Of Study
Run across locations in South Wales including Blaenau Gwent, Neath Port Talbot, Powys and Vale of Glamorgan. For more information, please contact dtlsn.info@cardiffmet.ac.uk
Contact Us
For more information about this course and details on how to apply, please contact dtlsn.info@cardiffmet.ac.uk
