AI+ Data Agent

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

1. 1

   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
2. 2

   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
3. 3

   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
4. 4

   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
5. 5

   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
6. 6

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

   • 6.1 Ethical Considerations in AI Data Agents
   • 6.2 Security and Privacy Concerns
7. 7

   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