Maestría en Ciencia de Datos e Inteligencia Artificial 2025 - De Python a Inteligencia Artificial Generativa

Resumen

Master Data Science and AI:

Learn Python, EDA, Stats, SQL, Machine Learning, NLP, Deep Learning and Gen AI What you'll learn:

Build a solid foundation in Python programming to effectively implement AI concepts and applications.Learn how Machine Learning & Deep Learning worksLearn how transformer models revolutionize NLP tasks, and how to leverage them for various applications.Gain hands-on experience with Retrieval-Augmented Generation (RAG) and Langchain for building advanced AI applications.Learn how to utilize vector databases for efficient storage and retrieval of embeddings in AI projects.Understand the complete pipeline of Natural Language Processing, from data preprocessing to model deployment.Explore the essentials of Large Language Models (LLMs) and their applications in generative tasks.Develop skills in crafting effective prompts to optimize model performance and achieve desired outputs. Welcome to Data Science & AI Masters 2025 - From Python To Gen AI!

This comprehensive course is designed for aspiring data scientists and AI enthusiasts who want to master the essential skills needed to thrive in the rapidly evolving field of data science and artificial intelligence. Whether you're a beginner or looking to enhance your existing knowledge, this bootcamp will guide you through every step of your learning journey.What You Will LearnIn this bootcamp, you will gain a solid foundation in key concepts and techniques, including:

Python Programming:

Start with the basics of Python, the most popular programming language in data science, and learn how to write efficient code.Exploratory Data Analysis (EDA):

Discover how to analyze and visualize data to uncover insights and patterns.Statistics:

Understand the statistical methods that underpin data analysis and machine learning.SQL:

Learn how to manage and query databases effectively using SQL.Machine Learning:

Dive into the world of machine learning, covering algorithms, model evaluation, and practical applications.Time Series Analysis & Forecasting:

Explore techniques for analyzing time-dependent data and making predictions.Deep Learning:

Get hands-on experience with neural networks and deep learning frameworks.Natural Language Processing (NLP):

Learn how to process and analyze textual data using NLP techniques.Transformers and Generative AI:

Understand the latest advancements in AI, including transformer models and generative AI applications.Real-World Projects:

Apply your skills through engaging projects that simulate real-world data challenges.Course StructureThe bootcamp is structured into modules that build upon each other, ensuring a smooth learning experience.

Each module includes video lectures, hands-on exercises, and quizzes to reinforce your understanding. By the end of the course, you will have a robust portfolio of projects showcasing your skills and knowledge.ConclusionJoin us in The Complete DS/AI Bootcamp and take the first step towards a rewarding career in data science and artificial intelligence.

With the demand for data professionals on the rise, this course will equip you with the skills needed to excel in this exciting field. Enroll now and start your journey to becoming a proficient data scientist and AI expert!

Programa

• **Programación en Python**
Introducción a Python
Estructuras de Datos y Algoritmos
Escritura de Código Eficiente y Limpio
• **Análisis Exploratorio de Datos (EDA)**
Recolección y Limpieza de Datos
Técnicas de Visualización de Datos
Identificación de Patrones y Conclusiones
• **Estadísticas para Ciencia de Datos**
Estadísticas Descriptivas
Distribuciones de Probabilidad
Pruebas de Hipótesis y Estadísticas Inferenciales
• **SQL para Gestión de Datos**
Diseño y Gestión de Bases de Datos
Escritura de Consultas SQL
Manipulación y Agregación de Datos
• **Aprendizaje Automático**
Aprendizaje Supervisado vs No Supervisado
Evaluación y Optimización de Modelos
Aplicaciones Prácticas y Estudios de Caso
• **Análisis y Pronóstico de Series Temporales**
Características de Datos de Series Temporales
Técnicas de Pronóstico
Análisis de Estacionalidad y Tendencias
• **Aprendizaje Profundo**
Introducción a Redes Neuronales
Técnicas de Entrenamiento y Optimización
Uso de Marcos de Aprendizaje Profundo Populares
• **Procesamiento de Lenguaje Natural (NLP)**
Preprocesamiento de Texto y Tokenización
Análisis de Sentimientos y Clasificación de Texto
Despliegue de Modelos de NLP
• **Transformadores e IA Generativa**
Visión General de la Arquitectura de Transformadores
Aplicaciones en NLP y Más Allá
Conceptos y Casos de Uso de IA Generativa
• **Aplicaciones Avanzadas de IA**
Generación Aumentada por Recuperación (RAG)
Langchain para Soluciones Complejas de IA
Uso de Bases de Datos Vectoriales para Gestión de Embeddings
• **Modelos de Lenguaje de Gran Escala (LLMs)**
Exploración de LLMs en Varios Contextos
Ingeniería de Prompts Efectiva
Personalización de LLMs para Tareas Específicas
• **Proyectos de Integración**
Desafíos de Datos del Mundo Real
Desarrollo Práctico de Proyectos
Creación de un Portafolio de Soluciones de IA

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Impartido por

Satyajit Pattnaik and Zep Tech Solutions

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Materias

Data Science