Machine Learning Models in Science
Gain mastery in machine learning algorithms and their implementation specifically for scientific research, enhancing data analysis
Gain mastery in machine learning algorithms and their implementation specifically for scientific research, enhancing data analysis
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full AI for Scientific Research Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
3.9
(11 ratings)
1,712 already enrolled
Instructors:
English
Powered by
What you'll learn
Implement advanced ML models
Analyze scientific datasets
Apply PCA and data preprocessing
Optimize model performance
Compare different ML approaches
Skills you'll gain
This course includes:
1.1 Hours PreRecorded video
5 quizzes
Access on Mobile, Desktop, Tablet
FullTime access
Shareable certificate
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 4 modules in this course
This course covers advanced machine learning models for scientific applications. Students learn to implement neural networks, random forests, and other algorithms using Python for analyzing scientific data.
Before the AI: Data Preprocessing
Module 1 · 2 Hours to complete
Foundational AI Algorithms
Module 2 · 3 Hours to complete
Advanced AI: Neural Networks
Module 3 · 3 Hours to complete
Course Project: Model Comparison
Module 4 · 2 Hours to complete
Fee Structure
Instructors
Head of Data Science, Machine Learning Solutions
Rajvir Dua is the Head of Data Science at LearnQuest, where he combines his expertise in data science with a strong interest in supply chain management. With experience as a teaching and research assistant, he has been actively involved in the data science and consulting startup space. His academic interests are particularly focused on economic problems related to game theory and optimization, which inform his approach to data-driven decision-making in supply chain contexts.On Coursera, Rajvir offers a variety of courses designed to enhance learners' understanding of data science and its applications. His courses include Advanced AI Techniques for the Supply Chain, Fundamentals of Machine Learning for Supply Chain, and Demand Forecasting Using Time Series. These courses aim to equip students with practical skills in machine learning and data analysis, preparing them for challenges in modern supply chain management. Rajvir's commitment to education and his extensive knowledge in data science make him a valuable resource for those looking to advance their careers in this dynamic field.
Co-founder and CEO, Machine Learning Solutions
Neelesh Tiruviluamala is a math professor and the co-founder and CEO of Machine Learning Solutions, with over ten years of consulting experience in the machine learning domain. He has a keen interest in supply chain problems, appreciating the rich data sets that allow for the application of various quantitative tools. His expertise bridges the gap between theoretical mathematics and practical machine learning applications, making him a valuable asset in the field.On Coursera, Neelesh offers a range of courses that focus on advanced machine learning techniques and their applications in supply chain management. His courses include Advanced AI Techniques for the Supply Chain, Demand Forecasting Using Time Series, and Introduction to Data Science and scikit-learn in Python. Through these courses, he aims to equip learners with the skills needed to leverage data science effectively in real-world scenarios, particularly within the context of supply chain optimization. Neelesh's commitment to education and his extensive experience make him an influential figure in the intersection of mathematics and machine learning.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
3.9 course rating
11 ratings
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.