Mathematics for ML & Data Science Specialization
Master the AI and machine learning toolkit. Mathematics for Machine Learning and Data Science is a Specialization that is accessible to beginners. In this program, you will acquire the basic mathematics tools of machine learning, including calculus, linear algebra, statistics, and probability.
Description for Mathematics for ML & Data Science Specialization
Features of Course
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by DeepLearning.AI
Duration: 3 months at 5 hours a week
Schedule: Flexible
Pricing for Mathematics for ML & Data Science Specialization
Use Cases for Mathematics for ML & Data Science Specialization
FAQs for Mathematics for ML & Data Science Specialization
Reviews for Mathematics for ML & Data Science Specialization
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Mathematics for ML & Data Science Specialization
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.
Develop and evaluate machine learning models using regression, trees, and unsupervised techniques to address various business challenges.
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.
Featured Tools
Master Apache Spark's scalable machine learning techniques for optimizing performance and managing large datasets.
The course highlights the curriculum focused on statistics and machine learning, covering descriptive statistics, data clustering, predictive model development, and analysis capability development.
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.
Gain practical skills and foundational knowledge of generative AI, along with insights from AWS AI practitioners on how companies leverage cutting-edge technology for value generation.
Learn to construct and implement prediction functions, understand overfitting and error rates, and grasp machine learning techniques like classification trees and regression.
Compare & Review AI Tool Directory AI Course Marketplace
AI Tool Categories
AI Productivity ToolsAI Image GeneratorsAI Text GeneratorsAI Video GeneratorsAI Audio GeneratorsAI Art GeneratorsMisc AI ToolsAI Code GeneratorsFree AI Tools
Aimed Labs