Description for ML Algorithms with R in Business Analytics
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by Illinois
Duration: 14 hours (approximately)
Schedule: Flexible
Pricing for ML Algorithms with R in Business Analytics
Use Cases for ML Algorithms with R in Business Analytics
FAQs for ML Algorithms with R in Business Analytics
Reviews for ML Algorithms with R in Business Analytics
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML Algorithms with R in Business Analytics
Use AI skills to advance your engineering career. Acquire practical knowledge regarding deep learning methodologies for computer vision.
Learn to describe and implement various machine learning algorithms in Python, including classification and regression techniques, and evaluate their performance using appropriate metrics.
Learn to build and train supervised machine learning models for binary classification and prediction tasks using Python with NumPy and scikit-learn libraries.
Accelerate your career in data analytics. In this certificate program, you will acquire skills that are in high demand at your own tempo, regardless of your degree or experience.
Begin your professional journey as an AI engineer. Master the art of generating business insights from large datasets by employing deep learning and machine learning models.
Construct the gradient descent algorithm, execute univariate linear regression with NumPy and Python, and create data visualizations with matplotlib.
Learn regression analysis, build prediction functions, and develop public data products.
Learn to construct and implement prediction functions, understand overfitting and error rates, and grasp machine learning techniques like classification trees and regression.
Gain expertise in Bayesian statistics, Bayesian inference, and R programming through comprehensive courses, active learning, and a culminating real-world data analysis project.
Gain expertise in leveraging machine learning for marketing transformation, applying unsupervised models like PCA and K-Means, understanding the theory behind k-means clustering and PCA, and determining the optimal number of clusters using the elbow method.
Featured Tools
Begin your vocation in generative AI data engineering. Obtain the necessary skills to secure a position as a data engineer by acquiring an understanding of generative AI. No prior experience is required.
Begin your professional journey as an AI Product Manager. Develop generative AI and product management skills that are in high demand to be job-ready in six months or less.
Unlock and capitalize on the capabilities of generative AI. Discover how the capabilities of generative AI can be leveraged to improve your work and personal life.
This learning path provides a thorough overview of generative AI. This specialization delves into the ethical considerations that are essential for the responsible development and deployment of AI, as well as the foundations of large language models (LLMs) and their diverse applications.
This course will provide you with an understanding of the technical underpinnings and essential terminology associated with generative artificial intelligence (AI).
Compare & Review AI Tool Directory AI Course Marketplace
