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HarvardX: Introduction to Data Science with Python

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Learn the concepts and techniques that make up the foundation of data science and machine learning.

8 semanas
3–4 horas por semana
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Comienza el 11 dic

Sobre este curso

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Every single minute, computers across the world collect millions of gigabytes of data. What can you do to make sense of this mountain of data? How do data scientists use this data for the applications that power our modern world?

Data science is an ever-evolving field, using algorithms and scientific methods to parse complex data sets. Data scientists use a range of programming languages, such as Python and R, to harness and analyze data. This course focuses on using Python in data science. By the end of the course, you’ll have a fundamental understanding of machine learning models and basic concepts around Machine Learning (ML) and Artificial Intelligence (AI).

Using Python, learners will study regression models (Linear, Multilinear, and Polynomial) and classification models (kNN, Logistic), utilizing popular libraries such as sklearn, Pandas, matplotlib, and numPy. The course will cover key concepts of machine learning such as: picking the right complexity, preventing overfitting, regularization, assessing uncertainty, weighing trade-offs, and model evaluation. Participation in this course will build your confidence in using Python, preparing you for more advanced study in Machine Learning (ML) and Artificial Intelligence (AI), and advancement in your career.

Learners must have a minimum baseline of programming knowledge (preferably in Python) and statistics in order to be successful in this course. Python prerequisites can be met with an introductory Python course offered through CS50’s Introduction to Programming with Python, and statistics prerequisites can be met via Fat Chance or with Stat110 offered through HarvardX.

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  • Idioma: English
  • Transcripciones de video: اَلْعَرَبِيَّةُ, Deutsch, Español, Français, हिन्दी, Bahasa Indonesia, Português, Kiswahili, తెలుగు, Türkçe, 中文
  • Habilidades asociadas:Python (Programming Language), Matplotlib, NumPy, Data Science, Scientific Methods, R (Programming Language), Artificial Intelligence, Algorithms, Parsing, Machine Learning, Pandas (Python Package), Scikit-learn (Machine Learning Library)

Lo que aprenderás

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  • Gain hands-on experience and practice using Python to solve real data science challenges
  • Practice Python programming and coding for modeling, statistics, and storytelling
  • Utilize popular libraries such as Pandas, numPy, matplotlib, and SKLearn
  • Run basic machine learning models using Python, evaluate how those models are performing, and apply those models to real-world problems
  • Build a foundation for the use of Python in machine learning and artificial intelligence, preparing you for future Python study

Plan de estudios

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Course Outline:

  1. Linear Regression
  2. Multiple and Polynomial Regression
  3. Model Selection and Cross-Validation
  4. Bias, Variance, and Hyperparameters
  5. Classification and Logistic Regression
  6. Multi-logstic Regression and Missingness
  7. Bootstrap, Confidence Intervals, and Hypothesis Testing
  8. Capstone Project

¿Quién puede hacer este curso?

Lamentablemente, las personas residentes en uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.

Este curso es parte delprograma Learning Python for Data Science Professional Certificate

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Instrucción por expertos
3 cursos de capacitación
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6 meses
3 - 6 horas semanales

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