Data & Analytics · Self-paced
AI+ Data Agent™
Build AI Agents that Automate Data Analysis, Reporting, and Insights.
Executive summary
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.
Built for these roles
Before you start
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.
One-time price
$110
8 hours, self-paced. Lifetime access, certificate included.
Certification exam included (limited attempts).
Secure checkout via Stripe. Instant access after payment.
Curriculum
What you'll cover.
8 hours of self-paced content. Work through it in order, on your schedule.
Module 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
Module 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
Module 3: Data Collection and Acquisition for AI Data Agents
3.1 Steps in AI Data Collection- Structure & Pan
3.2 Methods Of Data Collection
Module 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
Module 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
Module 6: AI in Compliance & Ethics
6.1 Ethical Considerations in AI Data Agents
6.2 Security and Privacy Concerns
Module 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
Ready to get certified?
Start today, learn at your own pace, and add a globally recognised credential to your name.
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