Introducción a SQL

4 horas

41 capítulos

Principiante

Este curso es ideal para principiantes que desean explorar el mundo de SQL. Ya sea que estés comenzando en la gestión de bases de datos o busques utilizar SQL en tus proyectos de desarrollo de aplicaciones, este curso cubre los aspectos esenciales. Aprenderás rápidamente a aprovechar todo el potencial de SQL, desde la consulta y gestión de datos hasta su integración en aplicaciones del mundo real. Al finalizar el curso, contarás con la confianza y las habilidades necesarias para resolver problemas prácticos con SQL y mejorar tu proceso de desarrollo.

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SQL Intermedio

3 horas

25 capítulos

Intermedio

Este curso es para ti si ya tienes conocimientos básicos de SQL, pero quieres aprender cosas más avanzadas para crear consultas más potentes. En el curso, se familiarizará con la agrupación de datos, el filtrado de datos agrupados. También aprenderá a trabajar con varias tablas de la base de datos al mismo tiempo, combinándolas. Conozca los diferentes tipos de uniones de tablas, aprenda a utilizarlas en la práctica.

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Primeros Pasos con Pandas

4 horas

33 capítulos

Intermedio

Pandas es una biblioteca extremadamente fácil de usar para el análisis de datos. También está diseñada para manejar grandes conjuntos de datos, utilizando estructuras de datos como DataFrame y Series. Esto la convierte en una herramienta invaluable para la Ciencia de Datos. En esta guía, te familiarizarás con una variedad de funciones estadísticas, incluyendo cómo encontrar correlaciones, modas, medianas y valores máximos y mínimos dentro de un conjunto de datos. También aprenderás a manejar valores faltantes y manipular valores específicos, así como a eliminarlos.

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Conducting Exploratory Data Analysis of Nobel Prizes

1 hora

6 capítulos

Intermedio

We will delve into the concept of Exploratory Data Analysis (EDA) and explore its critical role within every Data Analysis process, particularly focusing on the analysis of Nobel Prizes. EDA serves as a foundational step that enables data scientists and analysts to uncover patterns, anomalies, and insights from data through visual and statistical methods.

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Extracting Text Meaning using TF-IDF

2 horas

12 capítulos

Intermedio

This project focuses on the design and implementation of a robust text summarizer, built using Python. By harnessing the capabilities of Python’s Natural Language Toolkit (NLTK), participants will gain hands-on experience in processing and analyzing textual data. The project covers a range of NLP techniques essential for text summarization. Participants will develop skills in parsing text and extracting meaningful content, learning how to filter essential information from large volumes of text.

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Recognizing Handwritten Digits

2 horas

10 capítulos

Avanzado

In this project, our primary objective will be to delve into the identification of handwritten digits through the application of machine learning algorithms. This endeavor aims to harness the power of machine learning to effectively interpret and understand handwritten digits, showcasing the potential of these algorithms in processing and analyzing complex visual information.

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Advanced Techniques in pandas

4 horas

33 capítulos

Intermedio

This course contains a lot of useful functions for a future data analyst. You will learn different ways of extracting data and even set conditions on it. After it, you will be familiar with the methods of grouping data. Also, you will learn how to preprocess data. Each section has its data set so that the course will be gripping.

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Ultimate NumPy

3 horas

27 capítulos

Intermedio

Unlock the full potential of Python's most essential library for numerical computing, NumPy. This comprehensive course is designed to take you from a beginner's understanding to an advanced level of proficiency in NumPy. Whether you're a data scientist, engineer, researcher, or developer, mastering NumPy is essential for efficient data manipulation, scientific computing, and machine learning.

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Introduction to Neural Networks

4 horas

25 capítulos

Avanzado

Neural networks are powerful algorithms inspired by the structure of the human brain that are used to solve complex machine learning problems. You will build your own Neural Network from scratch to understand how it works. After this course, you will be able to create neural networks for solving classification and regression problems using the scikit-learn library.

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Identifying the Most Frequent Words in Text

1 hora

11 capítulos

Principiante

In this project, we will be utilizing the capabilities of the Natural Language Toolkit (NLTK), a versatile and comprehensive library in Python designed for working with human language data. Our focus will encompass several core areas of natural language processing: tokenization, stemming, tagging and parsing. These NLTK features will form the backbone of our text processing and analysis tasks, making it an essential tool in our project for handling and extracting meaningful insights from language data.

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Relational Database and Normalization

1 hora

12 capítulos

Principiante

This course delves into the theory behind relational databases. You'll learn what they are and see how they differ from non-relational databases. Throughout the course, we'll walk you through the ins and outs of database design and familiarize you with various types of relationships. Additionally, you'll explore the concepts of normalization and normal forms, equipping you with the knowledge to craft efficient and optimized databases.

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ML Introduction with scikit-learn

4 horas

32 capítulos

Intermedio

Machine learning is now used everywhere. Want to learn it yourself? This course is an introduction to the world of Machine learning for you to learn basic concepts, work with Scikit-learn – the most popular library for ML and build your first Machine Learning project. This course is intended for students with a basic knowledge of Python, Pandas, and Numpy.

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