ML & Human Learning
Explore the intersection of human and machine learning, covering supervised and unsupervised techniques, AI's impact on education, and applications in learning management systems, designed for educators and AI enthusiasts.
Description for ML & Human Learning
Features of Course
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Illinois
Duration: 36 hours to complete
Schedule: Flexible
Pricing for ML & Human Learning
Use Cases for ML & Human Learning
FAQs for ML & Human Learning
Reviews for ML & Human Learning
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML & Human Learning
The AI tool empowers non-programmers to construct and deploy AI, featuring data transformation, insights generation, identification of critical drivers, and prediction and forecasting functionalities to enhance business decision-making and planning processes.
Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world
Utilize Generative AI to optimize marketing creativity. Explore the potential of Generative AI to revolutionize and influence your marketing organization.
Learn the significance, use cases, history, and pros and cons of generative AI in a business context, with a focus on its relationship to machine learning and services at Amazon.
Acquire practical skills to build a generative AI application by constructing a retrieval augmented generation (RAG) system using data, Qdrant, and LLMs.
The "Introduction to Vertex AI" course provides a four-hour, practical, and fundamental overview of Vertex AI, ideal for professionals and enthusiasts aiming to leverage AI effectively.
Investigate the field of artificial intelligence and machine learning. While investigating the transformative disciplines of artificial intelligence, machine learning, and deep learning, enhance your Python abilities.
Learn to describe and implement various machine learning algorithms in Python, including classification and regression techniques, and evaluate their performance using appropriate metrics.
Featured Tools
Learn to distinguish between different types of machine learning, prepare data for model development, build and evaluate Python-based models for both supervised and unsupervised learning, and choose the right model and metric for a given algorithm.
Understand the core concepts of data analytics, its primary phases, key data roles, various data structures, file formats, and the comprehensive data analysis process.
Learn to analyze meeting recordings for improving plans and team coordination, utilize Microsoft 365 Copilot effectively, and develop personalized marketing content using Generative AI.
Acquire practical skills in fundamental machine learning models and their applications using PyTorch, as utilized by leading tech companies.
Acquire practical skills to build a generative AI application by constructing a retrieval augmented generation (RAG) system using data, Qdrant, and LLMs.