Udemybeginneres

Domina la Ciencia de Datos con Python: Desde Cero a Experto

Master data analysis with Python! Learn Pandas, NumPy, Matplotlib & Machine Learning for data visualization and prediction. Boost your data skills.

Related:PandasNumPy
15students
8h 3m
Certificate
Uridium Finance
Uridium FinanceDesarrollador de Software

Course Content

Domina la Ciencia de Datos con Python: Desde Cero a Experto is a beginner-level Udemy course taught by Uridium Finance. It runs 8h 3m, is taught in Spanish, and includes a certificate of completion. 15 students have enrolled. It is a paid course, first published January 2025.

Master Python for Data Science: A Comprehensive 15-Week Course

Unlock the power of data! This course provides a robust foundation in Python and its applications within Data Science. Over 15 weeks, you'll gain practical skills to manipulate, analyze, and visualize data using industry-standard tools.

Here's what you'll learn:

  • Python Fundamentals: Get comfortable with the syntax and core structures of the Python programming language.
  • Data Science Introduction: Explore the core principles behind data manipulation and data analysis.
  • Data Manipulation with Pandas: Master Pandas, the leading library for working with datasets. Learn to clean, transform, and prepare data for analysis.
  • Data Visualization with Matplotlib & Seaborn: Create compelling and informative data visualizations to effectively communicate insights.
  • Statistics Essentials: Build a strong understanding of statistical concepts crucial for data analysis.
  • Exploratory Data Analysis (EDA): Develop skills to uncover patterns and relationships within your data.
  • Feature Engineering: Learn how to create new variables to enhance your machine learning models.
  • Advanced Pandas Techniques: Become proficient in advanced Pandas methods for handling large datasets.
  • Introduction to Machine Learning: Understand the fundamental concepts of machine learning algorithms.
  • Overfitting & Underfitting: Learn to diagnose and address common issues in model training.
  • Scikit-Learn Mastery: Apply advanced machine learning techniques using the powerful Scikit-Learn library.
  • Supervised Learning: Explore algorithms for making predictions using labeled data.
  • Unsupervised Learning: Analyze algorithms that identify patterns in data without human guidance.
  • Model Evaluation Metrics: Learn to assess the performance of your models and optimize their accuracy.
  • Model Selection & Hyperparameter Tuning: Improve your results by fine-tuning the key parameters of your models.

By the end of this course, you'll be equipped to effectively analyze large datasets, create impactful data visualizations, and build predictive models using Python. Start your data science journey with us and take the next step in your career!

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