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AI+ Researcher Practitioner™

Course code: NPAP430

Formerly known as AI+ Researcher™

Empower Discoveries with Artificial Intelligence

  • Research Evolution: Master AI tools for market research, analytics, and scholarly writing.
  • Data Mastery: Build competence in dataset handling, ethics, and AI-driven insights.
  • Innovation Engine: Drive academic and scientific breakthroughs using AI.
  • Domain Leadership: Lead advanced research fields with ethical AI practices.
75 EUR

91 EUR including VAT

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

Data Preprocessing and Management

Develop skills in cleaning, organizing, and augmenting datasets to improve the quality and reliability of AI-driven research.

Machine Learning Model Development

Gain expertise in designing, training, and evaluating machine learning models tailored to specific research problems.

Advanced Statistical Analysis

Apply advanced statistical techniques to interpret AI-generated data, ensuring robust and valid research conclusions.

AI-Enhanced Scholarly Publishing

Proficiency in using AI tools to improve the scholarly publishing process.

Course structure

Course Overview

Module 1: Introduction to Artificial Intelligence (AI) for Researchers

  • 1.1 Understanding AI, Machine Learning, and Deep Learning
  • 1.2 Overview of AI Tools and Technologies
  • 1.3 AI’s Impact on Research

Module 2: AI in Market Research

  • 2.1 Introduction to AI in Market Research
  • 2.2 Audience Analysis and Persona Creation Using AI
  • 2.3 Using AI for Branding and Marketing Insights

Module 3: Leveraging AI for Scientific Discovery

  • 3.1 AI in Data Science and Analysis
  • 3.2 Machine Learning Models in Scientific Research
  • 3.3 AI for Drug Discovery and Advanced Research

Module 4: AI for Academic and Scholarly Research

  • 4.1 Integrating AI into Academic Workflows
  • 4.2 Ethical Considerations in Academic AI Use
  • 4.3 AI Tools for Enhancing Academic Research and Writing

Module 5: Enhancing Research with AI Tools

  • 5.1 AI for Qualitative and Quantitative Research
  • 5.2 AI Tools for Data Visualization and Analysis
  • 5.3 Case Studies of AI in Research

Module 6: AI for Research Design and Methodology

  • 6.1 Innovating Research Design with AI
  • 6.2 AI in Survey Design and Implementation
  • 6.3 Operational Efficiency and AI

Module 7: Ethical and Responsible Use of AI in Research

  • 7.1 Ethical Considerations in AI Research
  • 7.2 Data Privacy and AI
  • 7.3 Developing and Implementing Ethical AI Guidelines

Module 8: Future of AI in Research

  • 8.1 Emerging Trends in AI Research
  • 8.2 Preparing for the AI-Driven Research Future

Optional Module: AI Agents for Researcher

  • 1. What Are AI Agents
  • 2. Key Capabilities of AI Agents in Research
  • 3. Applications and Trends for AI Agents in Research
  • 4. Benefits of AI Agents in Research
  • 5. How Does an AI Agent Work
  • 6. Core Characteristics of AI Agents
  • 7. Types of AI Agents

Prerequisites

  • Basic awareness of AI concepts; no technical background required.
  • Openness to exploring creative and unconventional problem-solving approaches.
  • Enthusiasm for discovering new tools and insights at the intersection of AI and research.
  • Willingness to critically engage with ethical considerations surrounding AI in research.

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