AI+ Data Agent (AT 5011 Self-Paced Training)
Ziele der Schulung
This certification uniquely combines AI automation, intelligent agent design, and practical data analytics—empowering learners to unlock insights, automate analytics workflows, and drive smarter data-driven decisions using AI data agents. It is tailored for individuals seeking to understand AI-driven data handling, analytics, and autonomous systems in real-world business contexts. What Will You Learn? Participants will build foundational knowledge of AI data agents, data collection, preprocessing, machine learning models, ethics in AI, and complete a capstone project to apply practical skills.
Zielgruppe Seminar
- Data Professionals: Ideal for data analysts, engineers, and scientists looking to enhance their expertise with AI-driven automation.
- Business Strategists: Perfect for professionals aiming to leverage data intelligence for informed and strategic decision-making.
- AI Enthusiasts: Designed for learners passionate about integrating AI with data management and intelligent systems.
- Tech Innovators: Suited for individuals exploring automation, predictive analytics, and autonomous data solutions.
- Aspiring Leaders: Ideal for professionals seeking to lead AI transformation initiatives and drive data-driven innovation within their organizations.
Voraussetzungen
- 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.
Seminarinhalt
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 & Plan
- 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: Ethics, Security, and Privacy in AI Data Agents
- 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
Hinweise
Prüfung und Zertifizierung
- Duration: 90 minutes
- Passing Score: 70% (35/50)
- Format: 50 multiple-choice/multiple-response questions
- Delivery Method: Online via proctored exam platform (flexible scheduling)
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