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- COURSE
AI+ Data Agent
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The AI for 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.
All students receive:
- One-Year Subscription (with all updates)
- High-Quality E-Book
- Al Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Exam Study Guide
- AI Agents Module
- Hands on Labs (in applicable courses)
- Proctored Exam with one Free Retake
Upcoming Class Dates and Times
All Sunset Learning courses are guaranteed to run
Course Outline and Details
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.
Target Audience
- Data Analyst
- Data Engineer
Course Objectives
- 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
Course Outline
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