AI-ML for Research and Industry Applications

The “AI-ML for Research and Industry Applications” workshop targets PhD scholars, researchers, and professionals, offering a comprehensive three-day program. It covers AI and ML basics, practical applications, hands-on model building, and sector-specific AI implementation in academia and various industries, enhancing practical understanding and skills application.

The aim of the “AI-ML for Research and Industry Applications” workshop is to equip PhD scholars, researchers, academicians, and industry professionals with a fundamental understanding and practical skills in artificial intelligence and machine learning. This workshop seeks to bridge theoretical knowledge with real-world applications, emphasizing hands-on experience in building and implementing AI models. By exploring various types of machine learning, data preprocessing techniques, and industry-specific AI applications, participants will gain the ability to enhance their research capabilities and solve complex problems in their respective fields, thereby fostering innovation and efficiency in both academic and industrial settings

• Equip participants with a solid foundation in AI and ML concepts.
• Facilitate practical experience with data preprocessing and model building.
• Highlight real-world applications of AI in diverse industries.
• Promote innovation and problem-solving through practical case studies.
• Enhance research capabilities using advanced AI tools.
• Prepare participants for technological advancements in their careers.
• Foster a network of professionals skilled in AI and ML applications.

Day 1: Introduction to AI & Machine Learning Session 1: Overview of AI and ML: Definitions, History, and Trends

•  Key concepts: Artificial Intelligence, Machine Learning, Deep Learning
•  AI/ML in real-world applications (industry, healthcare, etc.)

Session 2: Types of Machine Learning

• Supervised, Unsupervised, and Reinforcement Learning
•  Practical use cases of each type in research and industry

Day 2: Hands-on AI & ML for Research Session 1: Data Preprocessing and Feature Engineering

•  Data collection, cleaning, and feature selection techniques
• Tools like Pandas, NumPy, and Scikit-learn

Session 2: Building Machine Learning Models

•  Step-by-step hands-on demonstration of building models using Python
•  Use of algorithms such as Linear Regression, Logistic Regression, Decision Trees

Day 3: AI in Real-World Applications Session 1: AI in Scientific Research and Academia

•  How AI is transforming research (data analysis, automation, predictions)
•  Applications of AI-ML in scientific research.

Session 2: AI for Industry Professionals

•  Applying AI to solve business problems
•  Industry-specific applications: manufacturing, finance, healthcare, and logistics

• PhD scholars interested in AI and ML advancements.
• Researchers seeking practical applications of AI in their fields.
• Industry professionals exploring AI for business solutions.
• Technologists seeking to upgrade their skills in machine learning.
• Data analysts looking to expand their expertise in AI applications.
• Managers and decision-makers needing to understand AI impacts.
• Software developers interested in AI-driven programming techniques.