360€
306€
-15% (hasta el 30/04/2026)
* Becas y descuentos no aplicables a formación programada
- Presentación
- Temario
- Metodología
- Titulación
Descripción
¿A quién va dirigido?
The Course in Data Science and Mining is designed for professionals and graduates in the field keen on broadening or refreshing their expertise. Ideal for those interested in harnessing data-driven insights and exploring practical applications in their careers, this course offers a comprehensive yet accessible approach to contemporary data methodologies.
Objetivos
- Understand data science principles and their real-world applications. - Develop skills to analyse datasets and extract insights effectively. - Learn to use statistical methods for data interpretation and analysis. - Master data visualisation techniques to present findings clearly. - Acquire knowledge of machine learning algorithms and their uses. - Explore data mining techniques to uncover hidden patterns. - Gain proficiency in using Python for data science tasks.
Salidas Profesionales
- Data Analyst in various industries - Business Intelligence Analyst - Machine Learning Engineer - Data Mining Specialist - Statistical Analyst - Predictive Modeller - Data Consultant - Operations Research Analyst - Data Engineer - Big Data Analyst - Marketing Analyst - Risk Analyst - Healthcare Data Analyst
Temario del Course in Data Science and Mining
UNIT 1. INTRODUCTION TO DATA SCIENCE
- What is data science?
- Tools Necessary for the Data Scientist
- Data Science & Cloud Computing
- Legal Issues in Data Protection
UNIT 2. RELATIONAL DATABASES
- Introduction
- The relational model
- Structured Query Language (SQL)
- 4.MySQL. A relational database
UNIT 3. NOSQL DATABASES AND SCALABLE STORAGE
- What is a NoSQL database?
- Relational Databases vs NoSQL Databases
- NoSQL Database Types: CAP Theorem
- NoSQL Database Systems
UNIT 4. INTRODUCTION TO A NOSQL DATABASE SYSTEM, MONGODB
- What is MongoDB?
- How to Operate and Use MongoDB
- First Steps with MongoDB: Installation and Shell Commands
- Creating our first NoSQL database: Model and data insertion
- Data Updates in MongoDB: Set and Update Statements
- Operating with Indexes in MongoDB for Data Optimisation
- Data query in MongoDB
UNIT 5. WEKA AND DATA MINING
- What is WEKA?
- Data Mining Techniques in Weka
- Weka interfaces
- Attribute Selection
UNIT 6. PYTHON AND DATA ANALYSIS
- Introduction to Python
- What Is Needed?
- Libraries for data analysis in Python
- MongoDB, Hadoop and Python: Big Data Dream Team
UNIT 7. R AS A TOOL FOR BIG DATA
- Introduction to R
- What Is Needed?
- Data types
- Descriptive and Predictive Statistics with R
- Integrating R into Hadoop
UNIT 8. DATA PREPROCESSING AND DATA PROCESSING
- Data collection and cleaning (ETL)
- Statistical inference
- Regression models
- Hypothesis testing
UNIT 9. DATA ANALYSIS
- Business Analytical Intelligence
- Graph theory and social network analysis
- Presentation of results
Metodología
EDUCA LXP se basa en 6 pilares
Item
Titulación del Course in Data Science and Mining
Degree Issued and Endorsed by INESEM Business School. “Non-Official Education and Not Leading to the Award of an Official Degree or Certificate of Professionalism”.
INESEM Business School se ocupa también de la gestión de la Apostilla de la Haya, previa demanda del estudiante. Este sello garantiza la autenticidad de la firma del título en los 113 países suscritos al Convenio de la Haya sin necesidad de otra autenticación. El coste de esta gestión es de 65 euros. Si deseas más información contacta con nosotros en el 958 050 205 y resolveremos todas tus dudas.
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Course in Data Science and Mining
360€
306€
360€
306€