Machine Learning in Research: From Fundamentals to Advanced Applications
Empowering Researchers with Machine Learning for Advanced Data Analysis and Discovery
Virtual (Google Meet)
Mentor Based
Moderate
4 Days
6 -January -2025
5 PM IST
About
This workshop bridges the gap between theoretical ML knowledge and its application in academic research. Participants will learn about supervised and unsupervised learning, deep learning, and advanced ML algorithms, with hands-on projects tailored for research applications. By the end of the course, participants will be able to effectively use ML tools to analyze complex datasets, automate research workflows, and derive meaningful insights.
Aim
This workshop provides a comprehensive understanding of machine learning (ML) techniques for academic research. It covers essential to advanced ML concepts, equipping participants with practical skills to implement and interpret ML models in various research domains.
Workshop Objectives
- Understand and apply ML algorithms across diverse research fields.
- Develop skills in advanced ML and deep learning models for research applications.
- Master data preprocessing and feature engineering for improved model accuracy.
- Implement ML-based research projects with hands-on experience.
- Enhance data-driven research by integrating ML insights and automations.
Workshop Structure
- Machine Learning Foundations
- Overview of ML for academic research
- Types of learning: Supervised, Unsupervised, and Reinforcement Learning
- Data Preparation for ML
- Data transformation, normalization, and feature selection
- Handling imbalanced datasets
- Core Algorithms for Research Applications
- Linear regression, decision trees, k-nearest neighbors, support vector machines (SVM)
- Model evaluation techniques: Precision, Recall, F1 Score
- Model Optimization
- Hyperparameter tuning and model selection
- Cross-validation techniques
- Deploying ML Models for Research
- Practical tools for deploying models in research
- Hands-on experience with model deployment
Day wise Schedule:
- Day 1: Introduction to Machine Learning and Data Preparation
- ML concepts for research applications
- Hands-on data preparation: Feature selection, data cleaning
- Day 2: Machine Learning Algorithms and Applications
- Practical session: Applying core ML algorithms on research datasets
- Day 3: Model Optimization and Hyperparameter Tuning
- Hands-on: Tuning models for optimal research outcomes
- Day 4: Model Deployment in Research
- Deploying ML models for real-world research using Python (Flask, Streamlit)
Participant’s Eligibility
PhD scholars, academic researchers, data scientists, and professionals in scientific research.
Important Dates
Registration Ends
2025-01-06
Indian Standard Timing 1:00 pm
Workshop Dates
2025-01-06 to 2025-01-09
Indian Standard Timing 5 PM
Workshop Outcomes
- Proficiency in using ML models to support academic research.
- Ability to preprocess data and build advanced ML models for complex datasets.
- Practical experience in applying ML to real-world research problems.
- Enhanced analytical and technical skills to advance data-driven research.
Fee Structure
Student
INR. 1999
USD. 55
Ph.D. Scholar / Researcher
INR. 2599
USD. 60
Academician / Faculty
INR. 3999
USD. 70
Industry Professional
INR. 6499
USD. 100
List of Currencies
Key Takeaways
- Access to Live Lectures
- Access to Recorded Sessions
- e-Certificate
- Query Solving Post Workshop
Future Career Prospects
- Machine Learning Research Scientist
- Data Scientist in Academia
- Research Analyst with ML Specialization
- Scientific Research Consultant
- AI/ML Engineer in Research Labs
- Academic Lecturer/Professor in ML
Job Opportunities
- Research institutions implementing ML in scientific studies.
- Universities seeking ML expertise in various research departments.
- Tech companies and research labs exploring ML applications in scientific research.
Country
Profession
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