Certified Artificial Intelligence Practitioner (CAIP) November 16 6AM | Montag, 16. November 2020
About this Event
This class takes place from 6:00 A.M EDT - 10:00 A.M. EDT on November 16 - 20 and November 23 - 27.
There is no better way to future proof your career than becoming a Certified Artificial Intelligence Practitioner. Artificial Intelligence is on everyone organizations to do list. According to LinkedIn, A.I. specialists have seen a 74% annual growth in demand in the past five years, and that trend will continue as organizations look to harvest the most potential out of their data. The good news is you can take the first step into the world of A.I. with CertNexus Certified Artificial Intelligence Practitioner certification. With CAIP you will learn vendor-neutral, cross-industry foundational knowledge of AI and Machine Learning concepts, technologies, algorithms, and applications that will help keep your career ahead of the curve.
In this course, you will implement AI techniques in order to solve business problems.
- 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.
- Build classification models.
- Build 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.
To ensure your success in this course, you should have at least a high-level understanding of fundamental AI concepts, including, but not limited to: machine learning, supervised learning, unsupervised learning, artificial neural networks, computer vision, and natural language processing.
You can obtain this level of knowledge by taking the CertNexus AIBIZ™ (Exam AIZ-110) course.
You should also have experience working with databases and a high-level programming language such as Python, Java, or C/C++.
- Course Outline