Probability and Statistics in Data Science using Python

Alon Orlitsky, UCSanDiegoX

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data.

The job of a data scientist is to glean knowledge from complex and noisy datasets.

Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.

In this course, part of the Data Science MicroMasters program, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a hands-on experience of applying this theory to actual data using Jupyter notebooks.

Concepts covered included: random variables, dependence, correlation, regression, PCA, entropy and MDL.

What will you learn

  • The mathematical foundations for machine learning
  • Statistics literacy: understand the meaning of statements such as “at a 99% confidence level”

Сессии:
  • 24 апреля 2018
Характеристики онлайн курса:
  • Бесплатный:
  • Платный:
  • Сертификат:
  • MOOC:
  • Видеолекции:
  • Аудиолекции:
  • Email-курс:
  • Язык: Английский Gb

Отзывы

Пока никто не написал отзыв по этому курсу. Хотите быть первым?

Зарегистрируйтесь, чтобы оставить отзыв

Ещё курсы на эту тему:
6.00.2x_computational_thinking_course_tile262x136_verified 6.00.2x: Introduction to Computational Thinking and Data Science
An introduction to using computation to understand real-world phenomena. About...
6922fad4-4a1b-4064-8644-48030e5bbbc7-098558fd6e34.small Data Science Essentials
Explore data visualization and exploration concepts with experts from MIT and...
2102f79d-9a44-41e9-9d92-884bec46dc65-b2dccc093c53.small Statistics and Probability in Data Science using Python
Using Python, learn statistical and probabilistic approaches to understand and...
20e2ce7f-0e98-43eb-a956-ac820d822afd-ee53d1294f1f.small Introduction to Computational Thinking and Data Science
6.00.2x is an introduction to using computation to understand real-world phenomena...
Ещё из рубрики «Математика и статистика»:
4315ba0c-a4cf-4f88-badd-fd8a3027fac3-cbedef1b2ec7.small Introduction to Data Analytics for Managers
Explore data science and analyze business data with Microsoft Azure through...
096b151e-35f7-43a1-b31e-614216a183ca-edf8b45c30a9.small Sparse Representations in Image Processing: From Theory to Practice
Learn about the deployment of the sparse representation model to signal and...
8271fcc2-ba0c-4889-86d8-c03c50b55263-218fc513f1ca.small High Performance Finite Element Modeling – Part 2
Learn how to make cutting-edge adaptive FEM supercomputing simulations of aerodynamic...
1cac89b9-58b6-4f8b-8cee-0a2f7feded60-a4bfeccd8ab2.small Introduction to Analytics Modeling
Learn essential analytics models and methods and how to appropriately apply...
1e2cae8c-1c67-4067-a3c0-360543e6a9b8-6c87f931c00e.small Data Analytics for Business
Learn to apply your analytics skills in business by working through a real-world...
Ещё от edX:
06152bda-1945-43a4-8c77-e4ef2de48625-db3f92ee07ba.small Rethink the City: New Approaches to Global and Local Urban Challenges
How do you plan future cities? Explore alternative theories and innovative solutions...
4315ba0c-a4cf-4f88-badd-fd8a3027fac3-cbedef1b2ec7.small Introduction to Data Analytics for Managers
Explore data science and analyze business data with Microsoft Azure through...
840a303a-0c7f-424b-abff-d6c76dbfcb04-bb0ba79082df.small Identifying Community Needs for Public Library Management
Learn how to conduct research, surveys, and interviews as well as how to analyze...
096b151e-35f7-43a1-b31e-614216a183ca-edf8b45c30a9.small Sparse Representations in Image Processing: From Theory to Practice
Learn about the deployment of the sparse representation model to signal and...
14337485-76d7-4051-a636-16f294688037-3a3edb6dea4d.small Electricity and Magnetism: Magnetic Fields and Forces
Learn how charges create and move in magnetic fields and how to analyze simple...

© 2013-2017