Attribute

Detail

Format

Recorded Lectures (Self-Paced)

Level

Intermediate

Duration

3 Days (60-90 Minutes each Day)

Certification

e-Certification + e-Marksheet

Tools

Python, Google Colab, Pandas, Scikit-learn, Excel

About the Materials Discovery Course

This course explores the integration of machine learning and data science in materials research, equipping participants with methodologies to analyze complex datasets, predict material properties, and drive innovation in next‑generation materials development.

Program Highlights

• Comprehensive coverage of Data from fundamentals to advanced applications

• Hands-on projects and real-world case studies in AI

• Expert-curated curriculum aligned with current industry standards

• Access to recorded lectures and e-LMS platform for flexible, self-paced learning

• e-Certification and e-Marksheet upon successful completion

• Dedicated mentor support and interactive doubt-clearing sessions

• Practical experience with tools: Python, Google Colab, Pandas, Scikit-learn

• Career-oriented training for academic and professional growth in AI

Course Curriculum

Module 1: Foundations & Data Understanding

Understand materials data and load a real‑world dataset in Google Colab
Clean and preprocess data using Pandas
Convert composition into machine‑learnable features

Module 2: Machine Learning for Property Prediction

Build regression models (Linear Regression, Random Forest) for property prediction
Engineer features tailored to materials datasets
Evaluate models using R², MAE and visual diagnostics

Module 3: Optimization, Interpretation & Research Output

Improve model performance with tuning and validation techniques
Analyze feature importance and interpret results
Generate publication‑ready plots and export a complete case study

Tools, Techniques, or Platforms Covered

Python
Google Colab
Pandas
Scikit-learn
Excel

Real-World Applications

Apply Data skills directly to academic research, thesis work, and publications
Build a professional portfolio showcasing practical AI competencies
Solve industry-relevant problems using Data methodologies and tools
Contribute to open-source projects and collaborative research in AI
Prepare for competitive examinations, interviews, and professional certifications in AI

Who Should Attend & Prerequisites

Students pursuing degrees in AI, science, engineering, or related disciplines
Working professionals seeking to upskill or transition into AI roles
Researchers and academicians looking to adopt modern techniques in AI
Entrepreneurs, freelancers, and self-learners interested in practical AI knowledge

Prerequisites: Some familiarity with basic concepts in AI will be helpful but is not mandatory. A willingness to learn and engage with hands-on exercises is essential.

Frequently Asked Questions

1. What is the format of this Data-Driven Materials Discovery Using Machine Learning course?

This is an Recorded Lectures (Self-Paced) course delivered via our e-LMS platform. You will have access to pre-recorded video lectures, reading materials, assignments, quizzes, and hands-on projects that you can complete at your own pace.

2. Will I receive a certificate after completing this course?

Yes! Upon successful completion of all modules, assignments, and assessments, you will receive an e-Certification along with an e-Marksheet from NanoSchool (NSTC) that you can showcase on your CV and LinkedIn profile.

3. What are the prerequisites for this course?

Learners should have a foundational understanding of AI concepts. Familiarity with basic tools and programming is recommended.

4. How long will I have access to the course materials?

You will have access to all course materials for the duration of 3 Days (60-90 Minutes each Day). The self-paced format allows you to learn according to your own schedule through our online learning management system.

5. Is mentor support available during the course?

Yes, dedicated mentor support is available throughout the course. You can reach out for doubt-clearing sessions, project guidance, and career advice related to AI. Our mentors are industry experts and experienced professionals.

Enroll in Data-Driven Materials Discovery Using Machine Learning today and take the next step in your professional journey. With expert-curated content, practical projects, and industry-recognized certification, this course is your gateway to mastering AI skills that matter.

Brand	NSTC
Format	Recorded Lectures
Duration	3 Days (60-90 Minutes each Day)
Level	Intermediate
Domain	AI
Hands-On	Yes – Practical projects with industrial datasets
Tools Used	Python, Google Colab, Pandas, Scikit-learn, Excel

Achieve Excellence & Enter the Hall of Fame!

Elevate your research to the next level! Get your groundbreaking work considered for publication in prestigious Open Access Journal (worth USD 1,000) and Opportunity to join esteemed Centre of Excellence. Network with industry leaders, access ongoing learning opportunities, and potentially earn a place in our coveted

Hall of Fame.

Achieve excellence and solidify your reputation among the elite!