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CAIP ELEARNING

60 hours
All levels
29 lessons
0 quizzes
0 students

Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands on activities for each topic area. For a detailed outline including activities, hardware requirements and datasets please contact info@certnexus.com

Understanding of Python programming language 

Program and games creation using Python 2 & 3 

Knowledge of GUI creation 

Advanced Python features such as collections module & timestamps 

Students and freshers with interest in coding 

IT professionals looking for a domain with utmost job security 

Non- IT professionals willing to enter into IT with easy coding  


Organizations focusing on leveraging Python on a large scale 

Understanding of Python programming language 

Program and games creation using Python 2 & 3 

Knowledge of GUI creation 

Advanced Python features such as collections module & timestamps 

Students and freshers with interest in coding 

IT professionals looking for a domain with utmost job security 

Non- IT professionals willing to enter into IT with easy coding  


Organizations focusing on leveraging Python on a large scale 

Objectives

Course Objectives

• Specify a general approach to solve a given business problem that uses applied AI and ML.

• Train and tune a machine learning model.

• Build clustering models.

• Build linear regression models.

• Build support-vector machines (SVMs).

• Build artificial neural networks (ANNs).

• Collect and refine a dataset to prepare it for training and testing.

• Finalize a machine learning model and present the results to the appropriate audience.

• Build classification models.

• Build decision trees and random forests.

• Promote data privacy and ethical practices within AI and ML projects.

Student

Target Student

The skills covered in this course converge on three areas—software development, applied math and statistics, and business analysis. Target students for this course may be strong in one or two or these of these areas and looking to round out their skills in the other areas so they can apply artificial intelligence (AI) systems, particularly machine learning models, to business problems.

So the target student may be a programmer looking to develop additional skills to apply machine learning algorithms to business problems, or a data analyst who already has strong skills in applying math and statistics to business problems, but is looking to develop technology skills related to machine learning. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming.

This course is also designed to assist students in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-110) certification.

Information

Prerequisites

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++. You can obtain this level of skills and knowledge by taking the following Logical Operations or comparable course:

• Database Design: A Modern Approach

• Python® Programming: Introduction

• Python® Programming: Advanced

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