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Data Science

Industry-Specific
Digital Skills

Schedule

Duration

130 hours

PRESENTATION

Thanks to this Certificate in Data Science You'll gain in-depth knowledge, ranging from the fundamentals of data science to the practical application of key tools. The focus on databases relational and NoSQL data, along with data analysis in Python and R, provides a balanced perspective. The inclusion of MongoDB and the use of programming languages programming languages such as Python and R enhances practical applicability. In addition, the focus on data preprocessing and processing, with an emphasis on ETL (Extraction, Transformation, and Loading) and hypothesis testing will thoroughly prepare you for the challenges you’ll face in your data science projects. In addition, you’ll have a faculty team that specializes in the subject.

Objectives

  • Understanding the basics of Data Science and the essential tools.

  • Learn More in relational databases, addressing models, keys, and indexes.

  • Explore NoSQL databases, by comparing the relations and applying the CAP theorem.

  • Gain practical skills with MongoDB, from installation to advanced troubleshooting.

  • Using Python for data analysis and to understand its integration with MongoDB and Hadoop.

  • Mastering R as a tool for Big Data, exploring data types and predictive statistics.

  • Learn preprocessing techniques and data processing, including ETL and hypothesis testing.

Syllabus

TEACHING UNIT 1. INTRODUCTION TO DATA SCIENCE 1. What is data science? 2. Tools needed by a data scientist 3. Data Science & Cloud Computing TEACHING UNIT 2. RELATIONAL DATABASES 1. Data model 2. Data types 3. Primary keys 4. Indexes 5. The NULL value 6. Foreign keys 7. Views 8. Data Definition Language (DDL) 9. Data Control Language (DCL) LEARNING UNIT 3. NOSQL DATABASES AND SCALABLE STORAGE 1. What Is a NoSQL Database? 2. Relational Databases vs. NoSQL Databases 3. Types of NoSQL Databases: The CAP Theorem 4. NoSQL Database Systems LEARNING UNIT 4. INTRODUCTION TO A NoSQL DATABASE SYSTEM: MongoDB 1. What is MongoDB? 2. How MongoDB Works and Its Uses 3. Getting Started with MongoDB: Installation and Command Shell 4. Creating Our First NoSQL Database: Model and Data Insertion 5. Updating Data in MongoDB: SET and UPDATE Statements 6. Working with Indexes in MongoDB for Data Optimization 7. Querying Data in MongoDB TEACHING UNIT 5. PYTHON AND DATA ANALYSIS 1. Introduction to Python 2. What Do You Need? 3. Libraries for Data Analysis in Python 4. MongoDB, Hadoop, and Python: The Big Data Dream Team TEACHING UNIT 6. R AS A TOOL FOR BIG DATA 1. Introduction to R 2. What do you need? 3. Data types 4. Descriptive and Predictive Statistics with R 5. Integrating R with Hadoop TEACHING UNIT 7. DATA PRE-PROCESSING & PROCESSING 1. Data Acquisition and Cleaning (ETL) 2. Statistical Inference 3. Regression Models 4. Hypothesis Testing COURSE UNIT 8. DATA ANALYSIS 1. Business Analytics 2. Graph Theory and Social Network Analysis 3. 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.
Specialized Courses Catalog

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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