Learn from the best, the essential data analysis techniques to bring to your company the capabilities of this type of work"

This Postgraduate diploma will give the student a complete vision of the latest technologies used in Data Science and Artificial Intelligence. A very complete compilation of advances, novelties and work tools that will take students through the most intensive path, to prepare them for the current star profile.

Throughout this program you will learn everything necessary to analyze data, with the development of the various existing techniques. In addition, TECH will show how to capture the information and how to store it properly in each case.

Learn from the best with the most innovative educational system and with the security and solvency of the best online university right now. 

A complete update that will provide you with the working capacity of a specialist in the field”

This Postgraduate diploma in Data Analysis Techniques  contains the most complete and up-to-date educational program on the market. The most important features of the program include:

• Practical case studies presented by experts 
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where self-assessment can be used to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

All aspects necessary to use data visualiazation techniques, in a high quality training course" 

The program’s teaching staff includes professionals from sector who contribute their work experience to this training program, as well as renowned specialists from leading societies and prestigious universities. 

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide an immersive training program designed to train in real situations.
 
This program is designed around Problem Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year. For this purpose, the professional will be assisted by an innovative interactive video system created by renowned and experienced experts.  

This training has the best teaching material available online or downloadable, to facilitate your study and effort management"

A very complete program, created with a strong focus on quality and bringing our students to the highest level of skill"

The syllabus of the Postgraduate diploma is configured as a complete tour through each and every one of the knowledge necessary to understand and assume the ways of working in this field. With an approach focused on practical application that will help you grow as a professional from the very first moment of training. 

A comprehensive syllabus focused on acquiring knowledge and converting it into real skills, created to propel you to excellence"

Module 1. Data Analysis and Interpretation

1.1. Introduction to Statistics
1.2. Measures Applicable to the Processing of Information
1.3. Statistical Correlation
1.4. Theory of Conditional Probability
1.5. Random Variable and Probability Distribution
1.6. Bayesian Inference
1.7. Sample Theory
1.8. Confidence Intervals
1.9. Hypothesis Testing
1.10. Regression Analysis

Module 2. Data and AI Analysis Techniques

2.1. Predictive Analytics
2.2. Evaluation Techniques and Model Selection
2.3. Lineal Optimization Techniques
2.4. Monte Carlo Simulations
2.5. Scenario Analysis
2.6. Machine Learning Techniques
2.7. Web Analytics
2.8. Text Mining Techniques
2.9. Methods of Natural Language Processing (NLP)
2.10. Social Network Analytics

Module 3. Data Analysis Tools

3.1. Data Science R Environment
3.2. Data Science Python Environment
3.3. Static and Statistical Graphs
3.4. Data Processing in Different Formats and Different Sources
3.5. Data Cleaning and Preparation
3.6. Exploratory Studies
3.7. Decision Trees
3.8. Classification and Association Rules
3.9. Neural Networks
3.10. Deep Learning

Module 4. Database Management and Data Parallelization Systems

4.1. Conventional Databases
4.2. Non-Conventional Databases
4.3. Cloud Computing: Data Distribution Management 
4.4. Tools for the Ingestion of Large Volumes of Data
4.5. Types of Parallels
4.6. Data Processing in Streaming and Real Time
4.7. Parallel Processing: Hadoop
4.8. Parallel Processing: Spark
4.9. Apache Kafka

4.9.1. Introduction to Apache Kafka
4.9.2. Architecture
4.9.3. Data Structure
4.9.4. APIs Kafka
4.9.5. Case Uses

4.10. Cloudera Impala

A unique, key and decisive experience to boost your professional development"