Maximize your professional potential by studying a program that will help you position yourself as a data science manager” 

The program addresses data science from a technical and business perspective, and it offers all the necessary knowledge, allowing professionals to extract as much information as possible. Therefore, computer engineers or similar professionals interested in this area will be able to analyze in detail the different algorithms and platforms as well as the most modern tools used in data exploration, visualization, manipulation, processing and analysis. All of the above is complemented with the business skills required to reach an executive level profile capable of making key decisions in a company. The new multidisciplinary knowledge that students will acquire after completing the program will help them to position themselves as Data Science Officers (DSO) in companies of all sizes.

Similarly, the approach to data analysis from both perspectives makes this program a perfect educational experience that covers everything professionals that need to know in order to handle information and subsequently apply it as a fundamental asset for any organization.

The program will initially address the importance of using a good analysis system in the company, where each department can benefit. Likewise, specialized knowledge focused on the typology and life cycle of available resources will be developed, for which students will be instructed in basic statistics.

As the program progresses, students will be introduced to the models that present greater versatility and adaptability for the analysis of time series, such as the models associated to economic series. The program will lastly provide a wide variety of cases of use and cases where artificial intelligence and data science have been implemented in today's world.

With the professional master’s degree program, computer engineers will be able to specialize in Data Science, becoming the perfect opportunity to drive their professional career towards a managerial position in their respective departments. All this will be feasible thanks to a 100% online program, which adapts to the daily needs of its students. They will only require a device with an Internet connection to start developing a complete professional profile with international projection.   

If you are looking for a program that allows you to increase your skills and position yourself as a Data Science Officer (DSO) then then this is the course for you, in TECH you have found your place" 

The professional master’s degree in Data Science Management (DSO, Data Science Officer) contains the most complete and up-to-date educational program on the market. The most important features include: 

• Practical cases studies are presented by experts in Engineering in data analysis
• 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
• 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

Prepare yourself to make decisions of scientific value and implement strategies that improve company department functions” 

The program’s teaching staff includes professionals from the sector who contribute their work experience to this 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 immersive knowledge programmed to learn 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 throughout the program. You will be assisted by an innovative, interactive video system made by renowned experts with extensive experience in Data Science Management and as Data Science Officers. 

Empower your career by creating dashboards and KPIs depending on the department you work in"

Develop specialized knowledge related to data management and manipulation for Data Science processes. You will become a successful DSO"

As we find ourselves in the data era, all the emerging new systems must be understood in terms of their technological implications. For this reason, computer engineers interested in reaching senior professional management positions must have all the appropriate knowledge to maximize data processing, not only from a technical perspective, but also from a business perspective. With this in mind, TECH has devised a program focused on the different techniques, technologies and phases necessary for data analytics and knowledge and value extraction, from a comprehensive and up-to-date perspective.

Your future starts here. Train as a data analytics specialist and position yourself as a senior manager”

General objectives

• Analyze the benefits of applying data analytics techniques in each department of the company
• Develop the basis for understanding the needs and applications of each department
• Generate specialized knowledge to select the right tool
• Propose techniques and objectives in order to be as productive as possible according to the department

Specific objectives

Module 1. Data Analysis in a Business Organization

• Develop analytical skills in order to make quality decisions
• Examine effective marketing and communication campaigns
• Determine the creation of scorecards and KPIs according to the department
• Generate specialized knowledge to develop predictive analytics
• Propose business and loyalty plans based on market research
• Develop the ability to listen to the customer
• Apply statistical, quantitative and technical knowledge in real situations 

Module 2. Data Management, Data Manipulation and Information Management for Data Science

• Perform data analyses 
• Unify diverse data, achieving consistency of information 
• Producing relevant, effective information for decision making 
• Determine the best practices for data management according to its typology and uses
• Establish data access and reuse policies 
• Ensure security and availability: information availability, integrity and confidentiality 
• Examine data management tools using programming languages 

Module 3. Devices and IoT Platforms as a Base for Data Science

• Define what is meant by IoT (Internet of Things) and IIoT (Industrial Internet of Things) 
• Review the Industrial Internet Consortium 
• Analyze what is the IoT reference architecture
• Address IoT sensors and devices and their classification
• Identify communications protocols and technologies used in IoT
• Examine the different IoT Cloud platforms: general purpose, industrial, open source
• Develop data exchange mechanisms
• Establish security requirements and strategies
• Present the different IoT and IIoT application areas

Module 4. Graphical Representation of Data Analysis 

• Generate specialized knowledge in data analysis and representation 
• Examine the different types of grouped data 
• Establish the most-used graphic representations in different fields 
• Determine the design principles in data visualization 
• Introduce graphic narrative as a tool 
• Analyze the different software tools for graphing and exploratory data analysis 

Module 5. Data Science Tools

• Develop the skills to convert data into information from which knowledge can be extracted 
• Determine the main features of a dataset, its structure, components and the implications of its distribution in the modeling 
• Supporting decision making by performing comprehensive data analysis in advance 
• Develop skills to solve practical cases using data science techniques
• Establish the most appropriate general tools and methods for modeling each Dataset based on the preprocessing performed 
• Evaluate the results in an analytical way, understanding the impact of the chosen strategy on the various metrics 
• Demonstrate critical analysis of the results obtained after applying preprocessing or modeling methods 

Module 6. Data Mining: Selection, Pre-Processing and Transformation

• Generate specialized knowledge about the statistical prerequisites for any data analysis and evaluation 
• Develop the necessary skills for data identification, preparation and transformation 
• Evaluate the various methodologies presented and identify advantages and drawbacks 
• Examine the problems in high dimensional data environments 
• Implement algorithms used for data preprocessing
• Demonstrate the ability to interpret data visualization for descriptive analysis 
• Develop advanced knowledge of the different existing data preparation techniques for data cleaning, normalization and transformation 

Module 7. Predictability and Analysis of Stochastic Phenomena

• Analyze time series 
• Develop the formulation and basic properties of univariate time series models 
• Examine the methodology of modeling and prediction of real time series 
• Assess univariate models including outliers 
• Apply dynamic regression models and apply the methodology for the construction of such models from observed series 
• Address the spectral analysis of univariate time series, as well as the fundamentals related to periodogram-based inference and interpretation 
• Estimate the probability and trend in time series for a given time horizon 

Module 8. Design and Development of Intelligent Systems 

• Analyze the step from information to knowledge 
• Develop the different types of machine learning 
• Examine metrics and scores to quantify model quality 
• Implement the different machine learning algorithms 
• Identify probabilistic reasoning models 
• Lay the foundations for deep learning 
• Demonstrate the skills acquired to understand the various machine learning algorithms 

Module 9. Architecture and Systems for Intensive Use of Data 

• Determine the requirements for mass data usage systems 
• Examine different data models and analyze databases 
• Analyze the key functionalities for distributed systems and their importance in different types of systems 
• Evaluate which widely used applications use the fundamentals of distributed systems to design their systems
• Analyze the way in which databases store and retrieve information 
• Understand the different replication models and associated issues 
• Develop partitioning and distributed transactions 
• Assess batch systems and (near) real time systems 

Module 10. Practical Application of Data Science in Business Sectors 

• Analyze the state of the art of Artificial Intelligence (AI) and data analytics
• Develop specialized knowledge of the most widely used technologies 
• Generate a better understanding of the technology through use cases
• Analyze the chosen strategies to select the best technologies to implement 
• Determine the areas of application 
• Examine the actual and potential risks of the technology used 
• Propose benefits derived from the use 
• Identify future trends in specific fields

Achieve your goals and reach excellence by completing a program that will enable you to generate specialized knowledge in data representation and analytics”