This beginner-friendly certificate serves as the perfect entry point for those eager to master data-driven AI concepts and modern automation tools.  By exploring the foundations of AI data handling and business analytics, the course empowers curious learners to transform raw information into smarter, real-world decisions.

Recommended Prerequisites:

• Familiarity with data handling, including collection, cleaning, and preprocessing (beneficial but not mandatory).
• No prior coding experience required (hands-on with no-code tools).
• Basic knowledge of data science, algorithms, and decision-making principles (recommended).
• Suitable for professionals or enthusiasts looking to expand their knowledge in AI agent technology and data-driven decision-making.

Course Outline:

Lesson 1: Introduction to AI Agents

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

Lesson 2: Data Agents and Their Role in AI Systems

• 2.1 AI Data Agents
• 2.2 AI vs. AI Data Agent
• 2.3 Components of AI Data Agents
• 2.4 Types of AI Data Agents
• 2.5 Existing AI Data Agents in Trend

Lesson 3: Data Collection and Acquisition for AI Data Agents

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

Lesson 4: Data Pre-processing and Feature Engineering

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

Lesson 5: AI and Machine Learning Models for Data Agents

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

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

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

Lesson 7: Capstone Project

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

All necessary course materials are included.