Course Overview
TOPThe AI+ Data Agent™ course focuses on how intelligent data agents use AI to automate data collection, integration, and analysis. It highlights real-world applications in streamlining workflows, improving data accuracy, and enabling predictive decision-making. The course demonstrates how AI-driven automation enhances efficiency across business and technical environments. It also explores data governance, ethics, and compliance in AI-based systems.
Scheduled Classes
TOP| 01/26/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 02/23/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 03/23/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 04/20/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 05/18/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 06/22/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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What You'll Learn
TOP- Understand the role of AI agents in modern data ecosystems
- Apply AI for automating data collection, cleansing, and transformation
- Use intelligent systems for predictive analytics and decision-making
- Explore ethical and compliance considerations in data automation
- Integrate AI-based tools to enhance business intelligence and reporting
Outline
TOPIntroduction 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
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
Data Collection and Acquisition for AI Data Agents
- Steps in AI Data Collection Structure & Plan
- Methods of Data Collection
Data Pre-processing and Feature Engineering
- Data Cleaning and Transformation
- Feature Engineering for AI Models
- No-Code AI Data Agent for Preprocessing & Feature Engineering
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
Ethics, Security, and Privacy in AI Data Agents
- Ethical Considerations in AI Data Agents
- Security and Privacy Concerns
Capstone Project
- Problem Statement
- Practical Implementation
- Evaluation and Optimization
- No-Code AI and Machine Learning Models for Data Agents
Prerequisites
TOP- Familiarity with data handling, including collection, cleaning, and preprocessing .
- Basic knowledge of data science, algorithms, and decision-making principles.
- Suitable for professionals or enthusiasts looking to expand their knowledge in AI agent technology and data-driven decision-making.
- No prior coding experience required (hands-on with no-code tools).
Who Should Attend
TOP- Data Analyst
- Data Engineer
