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Data Science and Artificial Intelligence: Applied Training

Cross-cutting
Digital Skills

Digital Skills

Duration

200 hours

PRESENTATION

Thanks to this Data Science and Artificial Intelligence Course You'll be able to discover the world of data science in a world as vast as that of information. Upon completion, students will have the knowledge to form opinions on data-related content, as well as be familiar with more tools than they knew before taking the course. Not to mention that, thanks to the data analysis, students will learn what they should and should not do when managing them. Finally, students will have the opportunity to study the business that they run or work for, so that they can implement changes—or at least propose them—with the goal of attracting, improving services for, and retaining more customers, which is what really matters.

Objectives

  • To learn firsthand everything related to data in the data science.

  • Learn about cases in the industry, to have the opportunity to learn its strengths and weaknesses.

  • To have the opportunity to stay up to date within the industry and how they have become known.

  • Understanding the structure that must be followed to carry out the plan for data management.

  • To assimilate the online and offline activities that can be applied in this sector.

Syllabus

LESSON UNIT 1. INTRODUCTION TO DATA SCIENCE What is data science? Essential tools for the data scientist Data Science & Cloud Computing LESSON UNIT 2. RELATIONAL DATABASES Data Model Data Types Primary Keys Indexes The NULL Value Foreign Keys Views Data Definition Language (DDL) Data Control Language (DCL) TEACHING UNIT 3. NOSQL DATABASES AND SCALABLE STORAGE What is a NoSQL database? Relational Databases vs. NoSQL Databases Types of NoSQL Databases: The CAP Theorem NoSQL Database Systems LEARNING UNIT 4. INTRODUCTION TO A NOSQL DATABASE SYSTEM: MONGODB What Is MongoDB? How MongoDB Works and Its Uses Getting Started with MongoDB: Installation and Command Shell Creating Our First NoSQL Database: Model and Data Insertion Updating Data in MongoDB: SET and UPDATE Statements Working with Indexes in MongoDB for Data Optimization Querying Data in MongoDB TEACHING UNIT 5. PYTHON AND DATA ANALYSIS Introduction to Python What Do You Need? Libraries for Data Analysis in Python MongoDB, Hadoop, and Python: The Big Data Dream Team LEARNING UNIT 6. R AS A TOOL FOR BIG DATA Introduction to R What Do You Need? Data Types Descriptive and Predictive Statistics with R Integrating R with Hadoop TEACHING UNIT 7. DATA PRE-PROCESSING & PROCESSING Data Acquisition and Cleaning (ETL) Statistical Inference Regression Models Hypothesis Testing LEARNING UNIT 8. DATA ANALYSIS Business Analytics Graph Theory and Social Network Analysis Presentation of Results
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Are the Educa PHAROS courses eligible for credit?

Many courses can be credited toward the master's programs at Structuralia.
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Facts about our area

+ 1.483

Hours

+88.999

Minutes

264

Courses

Educa PHAROS is a next-generation training model that places a company’s human capital at the forefront. Through a platform that adapts to each company’s corporate identity and offers a total of more than 900 courses, it provides tailored training for each organization. The unlimited flat-rate plan provides each company with the number of courses that best suits its needs, as well as the ability to determine which employees will have access.
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