Course Content

Description

CPMAI v7.0 Introduction & Welcome

Summary of the learning path and goals of the certification program.

What is Artificial Intelligence

Fundamental investigation of AI theories, innovations, and revolutionary possibilities.

Applications of AI

Useful information about actual AI applications in a variety of business domains.

Best Practices & Methodologies for Successful AI Implementation

A strategic framework for putting organised and successful AI project management techniques into practice.

CPMAI Phase I: Business Understanding

Methodical process for establishing the goals, scope, and organisational AI preparedness of a project.

Machine Learning Fundamental Concepts

Fundamental ideas and theoretical underpinnings of the creation of machine learning algorithms.

Machine Learning Algorithms – Part I

Thorough investigation of basic machine learning algorithmic techniques.

Machine Learning Algorithms – Part II: Neural Networks & Deep Learning

Sophisticated methods for implementing deep learning and designing neural networks.

Generative AI, Transformer Models, and Large Language Models (LLMs)

Innovative research on transformative language models and generative AI technology.

Managing Data for AI

Methods for gathering, managing, and preparing data strategically for AI applications.

CPMAI Phase II – Data Understanding

Methodological foundation for thorough data interpretation and analysis.

Data Preparation for AI

Methods for preparing datasets for machine learning through transformation, cleaning, and optimisation.

CPMAI Methodology Phase III: Data Preparation

Methodical procedure for gathering trustworthy, high-quality data for the creation of AI models.

Machine Learning Development Tools & Platforms

An overview of the top development environments and technology platforms for AI applications.

CPMAI Methodology Phase IV: Model Development

Methodical approach to the creation of sophisticated machine learning models.

Model Evaluation and Testing

Comprehensive methods for evaluating and verifying the performance of machine learning models.

CPMAI Methodology Phase V: Model Evaluation

rigorous methodology for evaluating and improving the critical model.

Model Operationalization

Realistic methods for implementing and incorporating machine learning models into operational processes.

CPMAI Methodology Phase VI: Model Operationalization

A methodical strategy to growing and deploying AI solutions in various organisational settings.

Trustworthy AI Concepts

Investigation of responsible AI development concepts, bias reduction, and ethical issues.