Second Semester
Artificial Intelligence & Machine Learning Applications
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Duration :
0 Minutes
Training Level :
Professional
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Training Path Description
Learn AI applications and machine learning to build practical models and evaluate them using real examples.
This course offers a hands-on journey in Artificial Intelligence applications and machine learning—from understanding the problem to building a working model. You’ll learn core ML concepts, data preparation, choosing the right algorithms, training models, and evaluating performance. You’ll also apply these skills to realistic use cases like classification and prediction to improve decision-making. By the end, you’ll have a solid foundation to build and iterate intelligent, scalable solutions.
Accredited certificate
Get an accredited attendance certificate for the training
What Will You Gain?
Skills related to the course
- - Build machine learning models for real use cases
- - Data cleaning, preparation, and splitting
- - Choose and apply algorithms in practice
- - Use evaluation metrics and interpret results
- - Develop a repeatable, improvement-oriented solution approach
Training Path Objectives
- - Understand the difference between AI and machine learning
- - Prepare data for different tasks (classification/prediction)
- - Select suitable algorithms and train effective models
- - Evaluate models using appropriate metrics and improve them
- - Present a solution built on an ML model in a clear, scalable way
- Practical, ready-to-use models
- Focus on data preparation and performance evaluation
- Hands-on real use cases (classification/prediction)
- Understand the ML model lifecycle from start to deployment