Machine Learning Intro for Everyone
The course's topics including the distinction between deep learning, machine learning, and artificial intelligence, the process of developing machine learning models, the difference between supervised and unsupervised learning, and the use of metrics for evaluating classification models.
Description for Machine Learning Intro for Everyone
Features of Course
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 21
Offered by: On Coursera provided by IBM
Duration: 3 weeks at 2 hours a week
Schedule: Flexible
Pricing for Machine Learning Intro for Everyone
Use Cases for Machine Learning Intro for Everyone
FAQs for Machine Learning Intro for Everyone
Reviews for Machine Learning Intro for Everyone
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Machine Learning Intro for Everyone
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.
Develop generative AI capabilities for data analytics. Learn about generative AI to advance your career as a data analyst! No prior experience is required.
Achieve a professional status as an AI Engineer. Acquire the knowledge necessary to develop next-generation applications that are propelled by generative AI, a skill that is indispensable for startups, agencies, and large corporations.
Enhance your Product Manager career with Gen AI. Boost your Product Manager career in under two months by developing hands-on, in-demand generative AI skills. No prior experience is required to initiate the process.
Delve into the historical evolution of Generative AI and AI, exploring diverse models and their applications in business contexts for optimized decision-making and innovation.
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.
Explore the evolution and business implications of generative AI, emphasizing data significance, governance, transparency, and practical applications in modernization and customer service in this course.
Improve your cybersecurity career by incorporating AI. In three months or less, acquire the necessary credentials for your cybersecurity profession and develop in-demand generative AI skills. There is no prerequisite for a degree or prior experience.
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.
Featured Tools
Join us on a transformative voyage with our Generative AI for NLP Specialization, which is specifically designed to enhance your comprehension of AI-driven language models, from the fundamental concepts to the most advanced applications. While investigating the architecture and applications of large language models, enhance your proficiency in Python programming, machine learning, NLP, and Generative AI techniques.
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.
Learn to use Generative AI for creating compelling logos and establishing a strong brand identity that fosters customer loyalty.
The course outlines the learning objectives for understanding XGBoost algorithm theory, performing exploratory data analysis, and implementing XGBoost classifier models using Scikit-Learn.
Explore healthcare data mining methods, theoretical foundations of key techniques, selection criteria, and practical applications with emphasis on data cleansing, transformation, and modeling for real-world problem solving.