What tools and technologies are covered in Data Science Fundamentals Part 2: Unit 3?

This course covers NumPy, Scipy and scikit-learn.

What career roles is Data Science Fundamentals Part 2: Unit 3 relevant for?

The skills and techniques in Data Science Fundamentals Part 2: Unit 3 are most relevant for Científico de datos positions and other data science career paths.

Data Science Fundamentals Part 2: Unit 3 | Coursera | Data Science & AI Course

Descripción

This course takes a step-by-step approach to the process of building robust models to predict real-world outcomes and uncover valuable insights from your dataLee mas.

Este recurso es ofrecido por un socio afiliado. Si paga por la capacitación, podemos ganar una comisión para respaldar este sitio.

Relevancia profesional por rol de datos

The techniques and tools covered in Data Science Fundamentals Part 2: Unit 3 are most similar to the requirements found in Científico de datos data science job advertisements.

Puntuaciones de similitud (sobre 100)

Data Science Fundamentals Part 2: Unit 3

Descripción

Relevancia profesional por rol de datos

Hechos rápidos

Estructura

Data Science Tools and Techniques Covered

Suscríbete para recibir actualizaciones

Oportunidades similares

Data Science: Inference and Modeling

Predictive Modeling, Model Fitting, and Regression Analysis

Four Rare Machine Learning Skills All Data Scientists Need

Hierarchical and Mixed Effects Models in R

Mixed Models with R

Explanatory Model Analysis

Modeling Data in the Tidyverse

Statistics with SAS

Social and Economic Networks: Models and Analysis

Seleccionar fuente de aprendizaje