Course description

Develop the knowledge and skill sets of AI concepts, technologies, and tools that will enable candidate to become a capable AI practitioner in a wide variety of AI-related job functions.This certification exam is designed for practitioners who are seeking to demonstrate a vendor-neutral, cross-industry skill set within AI and with a focus on ML that will enable them to design, immplement, and hand o an AI solution or environment.

Course outline

Solving Business Problems Using AI and ML
Collecting and refining the dataset
Setting Up and Training a Model
Finalizing a Model
Building Linear Regression Models
Building Classification Models
Building Clustering Models
Advanced Models
Building Support-Vector Machines

Contact

Sales Department

+389 75 310 910; +389 2 3130 900 kursevi@semos.com.mk

Contact person

Borjanco Micevski

Business Development Manager, Adriatic region

+389 75 345 258 +389 78 306 647 borjanco.micevski@semos.com.mk

Contact person for
International
Business
Development

Marko Serafimovski

Head of International Business Development

+38978441867 marko.serafimovski@semos.com.mk

Certificate: AIP-110

This certification exam is designed for practitioners who are seeking to demonstrate a vendor-neutral, cross-industry skill set within AI and with a focus on ML that will enable them to design, implement, and hand off an AI solution or environment.

Acquired skills and competencies

In this course, you will implement AI techniques in order to solve business problems, and will learn to:

Specify a general approach to solve a given business problem that uses applied AI and ML.
Collect and refine a dataset to prepare it for training and testing.
Train and tune a machine learning model.
Finalize a machine learning model and present the results to the appropriate audience.
Build linear regression models.
Building Classification Models
Building Clustering Models
Build decision trees and random forests.
Build support-vector machines (SVMs).
Build artificial neural networks (ANNs).
Promote data privacy and ethical practices within AI and ML projects.