Unlocking AI: From Data to Predictions and Beyond (Classroom and Asynchronous e-learning)
About This Course
Unveil the secrets behind AI-powered insights and predictions. This course delves into the core concepts of machine learning and deep learning, providing a comprehensive understanding of how AI models work. Participants will learn to interpret model outputs, assess their reliability, and identify potential biases. By the end of this course, participants will be equipped to build and deploy AI-powered solutions, driving innovation and making data-driven decisions with confidence.
What You'll Learn
1. Understand statistics as a methodology that is concerned with formulating question, collecting, and analysing data and interpreting results.
2. Use basic terminology in statistics such as random variable, population, and sample.
3. Distinguish between the different types of data such as qualitative and quantitative and map it to the appropriate Python data type.
4. Define random variables and use probability rules.
5. Describe the different categories of analytic models.
6. Distinguish between supervised and unsupervised techniques.
7. Describe the different steps in a data mining project.
8. Perform data pre-processing using Python.
9. Implement different machine learning algorithms using scikit learn.
10. Evaluate machine learning models.
11. Understand and apply ethical AI and data practices.
12. Describe various components of a generative AI models.
13. Implement effective prompt engineering techniques.
Entry Requirements
At least a Higher Nitec qualification. Basic English Proficiency, foundational numeracy skills and familiarity with using digital tools such as Excel. Prior experience in programming or data analysis is advantageous but not mandatory. Participants without the necessary qualification can be considered on a case-by-case basis.