StepwisePlus
Back to Courses
Artificial Intelligence in Scientific Research
New

Artificial Intelligence in Scientific Research

Boost your scientific output using AI assistants, automated literature review, and intelligent data analysis.

1 dayBeginner6 lessons
All courses
100+ graduates96% satisfaction4.8Overall Average Rating
Crossfield Society
Instructor
Crossfield Society
Interdisciplinary Science and Innovation Society
01

Graduate students and postdocs looking to optimize their research time

02

Principal investigators wanting to implement AI tools in their research groups

What You'll Learn

Skills and knowledge you will gain from this course.

Master prompt engineering specifically for scientific queries and data extraction
Automate literature reviews using specialized AI research assistants
Use AI to accelerate data analysis and create high-quality scientific visualizations
Integrate 'dry-lab' predictive tools to complement experimental 'wet-lab' work
Establish efficient AI-driven pipelines for managing research papers and notes

Participation details

Schedule, location, and access information for this course.

Training schedule

Jun20
1. Oturum
June 20, 202620:00 – 22:00TR Time
Location & Access
Online

About This Course

A comprehensive look at what this course offers.

Accelerate your research productivity by integrating modern AI tools into your workflow. This course focuses on leveraging Large Language Models (LLMs) for literature synthesis, using AI-driven data analysis tools, and implementing practical 'dry-lab' techniques to streamline scientific discovery.

Curriculum

A detailed breakdown of everything covered in this course.

3 bölüm · 9 konu

1
Introduction to LLMs in Science: Prompt Engineering for Researchers
20 dk
2
Setting Up Your Environment: Integrating AI into Everyday Workflows
25 dk
3
Smart Literature Search: Using Consensus, Elicit, and Connected Papers
35 dk
1
Scientific Writing and Article Development with AI
40 dk
2
AI for Scientific Visualization: From Raw Data to Publication-Ready Figures
35 dk
3
Introduction to Dry-Lab Basics: Predictive Tools for Lab Scientists
30 dk
1
Summarizing and Extracting Insights from High-Volume PDF Libraries
40 dk
2
Building Custom GPTs for Specific Scientific Domains
45 dk
3
AI Ethics in Publishing: Handling Hallucinations and Peer Review
30 dk

Requirements

What you need before starting this course.

  • Basic familiarity with scientific research methodologies
  • No advanced coding required; basic computer literacy is sufficient
  • Background in any scientific discipline

Who This Is For

This course is perfect for you if...

  • Graduate students and postdocs looking to optimize their research time
  • Principal investigators wanting to implement AI tools in their research groups
  • Wet-lab scientists interested in basic dry-lab and computational shortcuts

Instructor

Your guide throughout this course.

Crossfield Society

Crossfield Society

Interdisciplinary Science and Innovation Society

Crossfield Society is an elite collective of AI researchers and data scientists dedicated to bridging the gap between artificial intelligence algorithms and fundamental scientific discovery.

Course Details

Key information about this course at a glance.

LevelBeginner
Total Duration1 day
Course TypeLive Course
LanguageTürkçe
CertificateIncluded
Last Updated2026-05

Frequently Asked Questions

Find answers to the most common questions about this course.

Our platform offers both live and pre-recorded training; you can check the specific 'Course Type' at the top of the course page. Our live courses are fully interactive and conducted simultaneously with the instructor.

While many of our live sessions are recorded, this may vary depending on the specific course. If a course is recorded, you will have access to the recordings through your profile. Please check the course description for exact details.

You can ask your questions directly to the instructor during the live sessions. Additionally, you can stay in constant touch with the instructor and other participants through course-specific WhatsApp communication groups.

Yes, upon successful completion of the live training program, a personalized, verifiable certificate of completion is issued to you. You can add this certificate to your resume and LinkedIn profile with a single click.

Depending on the course, the installation of required software (Python, VS Code, etc.) is usually demonstrated step-by-step during the first session. For courses with specific hardware requirements, these are detailed in the 'Requirements' section on the course page.

To put the theoretical knowledge into practice, hands-on projects and assignments are given at the end of each week or module. You will receive instructor feedback by completing these assignments.

Student Reviews

What our graduates say about our courses

AI in Scientific Research

A very clear, example-driven course. Thank you to everyone who put in the effort.

5

Selin G.

Biology Student

Applied Genomic Data Analysis with Bioinformatics Tools

We walked through pipeline setup from start to finish. Working with real datasets helped me go beyond theory.

5

Mert K.

Industry Professional

AI in Scientific Research

I took the course to build on my basics and I'm very happy with it. It was informative, not boring, and the interactive parts were great. I liked how common AI tools for researchers were explained simply and quickly.

4

Lane Ö.

Undergraduate Student

Introduction to Bioinformatics and Omics Data Structures

Core concepts are covered in a logical order. I saw omics data structures explained clearly for the first time. Reinforcing them with examples was really useful.

5

Zeynep A.

Graduate Student

Applied Genomic Data Analysis with Bioinformatics Tools

Real-world examples made genomic data analysis click for the first time. I could take the outputs from lab sessions straight into my workflow.

5

Ahmet D.

Industry Professional

Introduction to Bioinformatics and Omics Data Structures

The instructor explained the topic in a very clear way. I understood the material much better here than when it was covered mixed together in class.

5

Yiğit Ç.

Bioinformatics Student

AI in Scientific Research

It's a packed pace but the content is well structured. You learn a concrete tool or method in each section, so you can keep going without getting lost.

4

Deniz T.

Molecular Biology Student

Applied Genomic Data Analysis with Bioinformatics Tools

I now have a much clearer sense of which tools to use and when. The step-by-step structure in genomic analysis was exactly what I was looking for.

5

Ece Y.

Data Analyst

AI in Scientific Research

As a first-time learner I struggled with some parts beyond the presentations. Still, the instructor explained everything in a very clear way. I don't have enough background on the topic to offer suggestions.

4

Hilal D.

Physiotherapy Student

Introduction to Bioinformatics and Omics Data Structures

The lessons are clear and helpful. My only suggestion is to solve more examples together during the session to understand better.

5

Arden A.

Biology Student

1 / 10
Browse All Courses
Free

Take your career one step further. Enroll now, don't miss out.