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Accelerate research with AI tools for literature reviews, data analysis, hypothesis generation, and scientific writing.
Enroll For
(Excl. VAT)
Hurry up course is Coming Soon
Do you want to be a certified professional?
Certificate of completion 
Downloadable resources 
Virtual-F2F
8Hrs 
Market Analysis
Enroll For
(Excl. VAT)
Hurry up course is Coming Soon
Do you want to be a certified professional?
Certificate of completion
Downloadable resources
Virtual-F2F
8Hrs
Market Analysis
AI+ Researcher™ by AI CERTs® is a specialized certification designed for researchers, academics, and analysts who want to integrate Artificial Intelligence into their research workflows. It enables faster, more efficient, and higher-quality research outcomes across disciplines.
What You'll Learn:
• AI for Research
How AI is transforming academic and applied research
• Literature Review Automation
Using AI to discover, summarise, and organise research papers
• Data Analysis with AI
Applying AI for qualitative and quantitative analysis
• Hypothesis Generation & Research Design
Using AI to identify patterns and structure studies
• Research Ethics & AI Integrity
Responsible and ethical use of AI in research and publishing
Who This Course Is For
• Academic researchers and scholars
• Data scientists and analysts
• Postgraduate students
• Policy and insights professionals
Prerequisites
• Background in research or analytics
• Foundational AI knowledge (AI+ Foundation™ recommended)
Course Outcome
By completing this course, you will:
• Use AI tools to accelerate research workflows
• Automate literature reviews and data analysis tasks
• Generate insights and structured research outputs efficiently
• Improve research quality and productivity
• Apply AI ethically in academic and professional research
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1.1 Overview of AI and Its Impact on Academic and Applied Research
1.2 Key AI Technologies: NLP, Machine Learning & Knowledge Graphs
1.3 Introduction to AI Research Tools and Platforms
1.4 Use-Case, Case Study & Hands-On Activity
2.1 Automated Discovery and Retrieval of Research Papers
2.2 AI Tools for Summarising and Synthesising Literature
2.3 Citation Analysis and Research Gap Identification
2.4 Use-Case, Case Study & Hands-On Activity
3.1 AI Methods for Quantitative Data Analysis
3.2 AI Methods for Qualitative and Mixed-Methods Research
3.3 Data Visualisation and Pattern Recognition with AI
3.4 Use-Case, Case Study & Hands-On Activity
4.1 Leveraging AI to Identify Research Gaps and Generate Hypotheses
4.2 AI-Assisted Study Design and Methodology Selection
4.3 AI Tools for Academic Writing and Report Generation
4.4 Use-Case, Case Study & Hands-On Activity
5.1 Academic Integrity and Responsible AI Use in Research
5.2 Plagiarism Detection and AI-Generated Content Policies
5.3 Open Science, Reproducibility and AI Transparency
5.4 Emerging AI Trends: Autonomous Research Agents
5.5 Use-Case, Case Study & Hands-On Activity
