AI as Your Research Assistant
Transforming Your Scientific Skills with Generative Tools
Course Overview
Academic research is often bottlenecked by manual literature reviews, data overload, and “writer’s block.” This course transforms Generative AI from a novelty into a rigorous research partner. It moves beyond basic interaction to teach a methodological approach: using AI to synthesize vast amounts of literature, visualize citation networks, and structure complex arguments. Participants will learn to treat AI not as an author, but as a tireless research assistant that accelerates the path from hypothesis to publication while maintaining strict academic integrity.
Who Should Attend?
Early-Career Researchers & PhD Candidates seeking to increase publication velocity.
- Academic Faculty looking to integrate new digital tools into their methodology.
- R&D Professionals who need to conduct rapid, evidence-based literature reviews.
Prerequisites:
- Basic understanding of the scientific method and academic writing standards.
- Familiarity with citation principles (APA/MLA/Chicago).
Course Details
Instructor
Nabil Odeh
Mode
In-Person
Days / Hours
2 Days / 8 Hours
Course Code
RES-METH-AI
Learning Objectives
By the end of this course, participants will be able to:
- Evaluate the capabilities and ethical limits of major Generative AI models (GPT-4, Claude, Gemini) in an academic context.
- Execute deep literature mapping and consensus verification using specialized tools like ResearchRabbit and Consensus.app.
- Construct advanced prompt chains (Chain-of-Thought, Persona Patterns) to simulate peer reviews and refine arguments.
- Formulate a “Grounded Knowledge Base” using NotebookLM to organize citations and prevent hallucinations.
Course Content
Module 1: Foundations, Prompting & Ethics
1.1: GenAI Deconstructed: How LLMs work, major models, and their limitations.
1.2: Engineering the Prompt: Core principles (Context, Task, Constraints) for academic output.
1.3: Research Ethics: Plagiarism, bias detection, and disclosure standards.
Activity: “The Hallucination Stress Test” – Participants challenge models with false premises to identify verification failures.
Module 2: Prompt Patterns for Research
2.1: The Persona Pattern: Simulating “Peer Reviewer” to critique your work.
2.2: Cognitive Verifier Pattern: Forcing the AI to ask clarifying questions before generating text.
2.3: Chain-of-Thought Prompting: Breaking down complex analytical reasoning into steps.
Module 3: Advanced Literature Review & Discovery
3.1: Scientific Consensus: Using Consensus.app to extract evidence-based answers.
3.2: Network Mapping: Visualizing paper connections and authors with.
3.3: Gap Analysis: Synthesizing themes to identify missing links in current research.
Activity: Build a “Citation Graph” for a specific hypothesis and extract a consensus summary from 10+ papers.
Module 4: Drafting, Structuring & Synthesis
Topic 4.1: Structural Ideation: Using GAI as a “Thinking Partner” to outline papers and chapters.
Topic 4.2: Contextual Analysis: Deploying GenAI to interrogate your own PDF library.
Topic 4.3: The First Draft: Overcoming “Blank Page” syndrome without compromising voice.
Activity: “The Reverse Outline” – Feed a rough abstract to AI and ask it to expand it into a full methodological framework.
What’s Included
4.5 Hours of On-Demand Video Lessons
3 Downloadable Written Guides
Interactive Quizzes & Assignments
5 Practice Datasets and AI Prompts
Certificate of Completion
Prerequisites
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No prior coding experience required
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Basic understanding of computers and internet usage
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A free or trial account on ChatGPT, Midjourney, or other AI platforms (optional)
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Curiosity and a desire to learn how AI is shaping the world
Launch Yourself Into The Future.
