AI+ Researcher™ - eLearning (exam included)
275,00 EUR
- 15 hours
The AI+ Researcher Certification equips researchers with the skills to integrate Artificial Intelligence (AI) into their work, starting with foundational concepts like Machine Learning (ML) and Deep Learning (DL).
Key Features
Language
Course and material in English
Level
Beginner-Intermediate level (Category: AI+ Professional)
Access
1 year access to the platform 24/7
8 hours of video lessons & multimedia
15 hours of study time recommendation
Material
Video, PDF Material, audio eBook, Podcasts, quizzes and assessments.
Exam
Online Proctored Exam with One Free Retake
Certificate
Certification of completion included
Tools You’ll Master
TensorFlow, Scikit-learn, AI Fairness 360, Zotero
About the course
Harness AI to Accelerate Discoveries
- Research Transformation: Master AI tools for market analysis, data interpretation, and academic writing
- Data Expertise: Develop proficiency in managing datasets, applying ethical standards, and generating AI-powered insights
- Innovation Catalyst: Use AI to fuel scientific and academic advancements
- Field Leadership: Equip yourself to lead cutting-edge research with a strong ethical AI foundation
The program explores AI's transformative role in market research, scientific discovery, and academic pursuits, enhancing data analysis and fostering innovation across fields. Ethical considerations, such as data privacy and algorithmic bias, are emphasized throughout. Further, the certification also covers AI's application in research design and methodology, ensuring researchers can incorporate AI effectively into their processes. By blending technical knowledge with an ethical framework, the AI+ Researcher Certification prepares participants to lead in research innovation and stay ahead in their fields.
Master AI-Powered Research Methods
Gain expertise in designing, testing, and refining AI models for both academic and industry research.
Learning Outcomes
At the end of this course, you will be able to:
Data Preparation and Management
Learn methods for cleaning, structuring, and preparing datasets to maintain accuracy and reliability in AI research
Advanced Data Analysis
Use sophisticated statistical models to interpret AI-driven data, delivering accurate and actionable results.
Machine Learning Model Creation
Build, train, and assess AI models designed to address specific research objectives
AI-Driven Scholarly Publishing
Utilize AI tools to optimize research dissemination and boost the reach and impact of academic work
Course timeline
Introduction to Artificial Intelligence (AI) for Researchers
Lesson 1
- 1.1 Understanding AI, Machine Learning, and Deep Learning
- 1.2 Overview of AI Tools and Technologies
- 1.3 AI’s Impact on Research
AI in Market Research
Lesson 2
- 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
Leveraging AI for Scientific Discovery
Lesson 3
- 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
AI for Academic and Scholarly Research
Lesson 4
- 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
Enhancing Research with AI Tools
Lesson 5
- 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
AI for Research Design and Methodology
Lesson 6
- 6.1 Innovating Research Design with AI
- 6.2 AI in Survey Design and Implementation
- 6.3 Operational Efficiency and AI
Ethical and Responsible Use of AI in Research
Lesson 7
- 7.1 Ethical Considerations in AI Research
- 7.2 Data Privacy and AI
- 7.3 Developing and Implementing Ethical AI Guidelines
Future of AI in Research
Lesson 8
- 8.1 Emerging Trends in AI Research
- 8.2 Preparing for the AI-Driven Research Future
Optional Module: AI Agents for Researcher
Optional
- 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
Industry Expansion
Driving Breakthroughs in Academic and Corporate Research
- Rapid Industry Growth: AI research is forecasted to grow at a CAGR of 38.1% by 2026, driven by the rising demand for AI-powered solutions across sectors (Source: MarketsandMarkets).
- Advanced Algorithm Development: Designing AI models for real-world applications to improve efficiency and effectiveness in industries like healthcare and finance.
- Ethical AI Practices: Promoting transparency, fairness, and accountability to build trust in AI technologies.
- Scientific Breakthroughs: Leveraging AI for innovations in drug discovery, climate research, and genomics, advancing healthcare and environmental science.
- Business Intelligence: Applying AI to market forecasting, risk assessment, and decision-making to drive smarter strategies across industries.
Who Should Enroll in this Program?
Scholars & Researchers: Strengthen your research skills by integrating AI tools for data analysis and deeper insights.
Market Research Analysts: Use AI to refine research strategies, uncover actionable insights, and enhance decision-making.
Data Scientists: Employ AI techniques to process large datasets, enabling faster analysis and scientific discoveries.
Academic Leaders: Foster innovation in your institution by leveraging AI to boost research efficiency and output.
Students & Recent Graduates: Stand out in the research field by mastering AI-driven tools and methods for advanced studies.
More Details
Prerequisites
- Basic knowledge of AI concepts, with no need for prior technical expertise.
- A readiness to explore innovative and unconventional problem-solving approaches in AI and research.
- Interest in discovering new insights and tools that emerge from integrating AI with research methods.
- Commitment to thoughtfully addressing ethical challenges and considerations surrounding the use of AI in research.
Exam Details
- Duration: 90 minutes
- Passing :70% (35/50)
- Format: 50 multiple-choice/multiple-response questions
- Delivery Method: Online via proctored exam platform (flexible scheduling)
- Language: English
Licensing and accreditation
This course is offered by AVC according to Partner Program Agreement and complies with the License Agreement requirements.
Equity Policy
AVC does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.
Frequently Asked Questions
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