AI+ Data Agent™

AI+ Data Agent™ Certification – Course Outline

Program Overview

This curriculum offers a comprehensive learning path for developing AI data agents, focusing on their role in AI systems, data collection, preprocessing, and machine learning. The program covers both theoretical foundations and hands-on applications using no-code platforms to build AI models. Learners will explore the architecture, ethical considerations, and practical implementations of AI data agents across various industries such as healthcare, agriculture, and retail. Through a series of modules and a capstone project, participants will gain the skills needed to create and deploy intelligent, autonomous data agents capable of making real-time decisions in dynamic environments.

Course Duration

 • Recommended Duration: 35–40 Hours
 • Delivery Mode: Instructor-led (Classroom / Virtual) + Hands-on Labs
 • Assessment: Practical assignments + Final project (AI Data Agent build)

Learning Outcomes

 • Understand AI agents and data-driven automation systems
 • Design and deploy AI data agents for business use cases
 • Work with structured and unstructured data
 • Build automated data pipelines for AI systems
 • Integrate APIs and tools with AI agents
 • Apply prompt engineering for agent optimization
 • Use AI agents for analytics, reporting, and decision support
 • Evaluate performance and ethical considerations of AI systems

Assessment Methods

 • Quizzes after each module
 • Case study evaluations
 • Practical AI tool demonstrations
 • Final capstone project
 • Participation in simulations

Target Audience

 • Data Analysts and Business Analysts
 • IT Professionals
 • AI Beginners and Intermediates
 • Automation Specialists
 • Digital Transformation Teams
 • Trainers and Educators in AI/Data Fields

Certification

 • AI+ Data Agent™ Certificate of Completion
 • Optional practical evaluation badge (based on performance)

Course Modules

Module 1: Introduction to AI Agents

 • What is an AI Agent?
 • Components of AI Agents
 • Types of AI Agents
 • Hands-on: No-Code AI and Machine Learning Models for Data Agents

Module 2: Data Agents and Their Role in AI Systems

 • AI Data Agents
 • AI vs. AI Data Agent
 • Components of AI Data Agents
 • Types of AI Data Agents
 • Existing AI Data Agents in Trend

Module 3: Data Collection and Acquisition for AI Data Agents

 • Steps in AI Data Collection Structure & Plan
 • Methods of Data Collection

Module 4: Data Pre-processing and Feature Engineering

 • Data Cleaning and Transformation
 • Feature Engineering for AI Models
 • No-Code AI Data Agent for Preprocessing & Feature Engineering

Module 5: AI and Machine Learning Models for Data Agents

 • Introduction to Machine Learning Models for Data Agents
 • Model Selection and Training
 • Hands-on: No-Code AI and Machine Learning Models for Data Agents

Module 6: Ethics, Security, and Privacy in AI Data Agents

 • Ethical Considerations in AI Data Agents
 • Security and Privacy Concerns

Module 7: Capstone Project

 • Problem Statement
 • Practical Implementation
 • Evaluation and Optimization
 • No-Code AI and Machine Learning Models for Data Agents