Master IT
Management UCM

Purpose of the course

IT management ensures that all technological resources and associated employees are used not only correctly but also in a way that provides value for an organization. Effective IT management enables an organization to optimize resources and staffing, improve business and communication processes, and apply best practices. The Master’s Degree in IT Management is, therefore, intended for graduates and professionals who want to expand and renew their knowledge in the new challenges that the new market concept entails and its impact on the world economy. Besides, this Master seeks to teach the most innovative digital tools, cybersecurity, digital transformation of the company and digital marketing, to meet the needs of potential customers, without neglecting the profitability and sustainability of the company.

Total Credits: 60

Couse Credits: 48

Credits of Master’s Thesis: 12

Price of the degree: 8,500€

Potential students of the course

Graduates who want to continue their university studies or professionals with great experience within the area of computer science and who want to expand their knowledge.
IT management ensures that all technological resources and associated employees are used not only correctly but also in a way that provides value for an organization. Effective IT management enables an organization to optimize resources and staffing, improve business and communication processes, and apply best practices.

Modules of the Master


  • The nature of strategic management.
  • External analysis of the company.
  • Internal analysis of the company.
  • Formulation of strategies.
  • Evaluation and selection of strategies.
  • Implementation of strategies.
  • Strategic management of technology and innovation.
  • The innovation process.
  • Strategies for exploiting technological potential.
  • Open innovation. 


Course materials

Students will attend the online course so all teaching materials will be available on the virtual platform.


Specific competences

  • Know how to apply the strategic management model of the company.
  • Apply external strategic analysis tools to detect opportunities and threats.
  • Know how to perform an internal strategic analysis to detect strengths and weaknesses of the organization.
  • Know how to formulate strategies at different levels: corporate, competitive and functional.
  • Know the problems and implications of the implementation of the strategy.
  • Distinguish between science, technology, innovation and R&D about its main characteristics and the different typologies of technology and innovation, as well as its impact on the economy and the company.
  • Know the Strategic Management of Technology and Innovation model as an instrument for the formulation and implementation of technological strategies.
  • Know the basic components of national innovation systems and the main tools for the analysis of the technological environment and the technological potential of the company.
  • Know what legal tools there are to protect creativity and innovations and how they work and what other strategies can be followed to take advantage of those property rights or fight against those of the competition.
  • Know how to identify the technological strategies of exploitation and obtaining that companies can follow, what advantages and disadvantages they have and in what circumstances they are more appropriate.


  • Marketing off-line y marketing digital.
  • SEO / SEM strategies
  • Social media.
  • Analítica web / Inbound marketing.
  • Marketing automation.
  • Mobile marketing.
  • CRM management.
  • User experience.
  • Google ads, WordPress, Google Analytics.


Specific competences

  • Apply the tools and strategies of Online Marketing to the business world.
  • Design and develop a Digital Marketing Plan.
  • Use digital tools to position the company.


  • Threats, cybercrime and security.
  • Computer forensics.
  • Reverse engineering processes and tools.
  • Concepts and tools on network management for cyber defense.
  • Types and characteristics of malware and persistent threats.
  • Vulnerability management at a level of software, network and web.


Specific competences

  • Know the risks of computer vulnerabilities.
  • Know techniques for the analysis and preservation of evidence on a computer device, particularly after an attack.
  • Manage the most common cyber defense tools.
  • Manage techniques to detect malware and advanced persistent threats.


  • Cleaning and manipulation of data.
  • API and web scraping.
  • Git, SQL and Python.
  • The use of Python in the fundamentals of business intelligence.
  • Machine learning workflow.
  • Fundamentals of machine learning algorithms.


Specific competences

  • Know, identify and select the appropriate sources of information for analysis
  • Know the techniques for the extraction of information, prepare and debug the available information for subsequent data analysis.
  • Perform data analysis with real data sets.
  • Visualize and analyze data with the appropriate techniques.
  • Develop models to make predictions about new data.


  • Digital transformation vs. Business transformation.
  • Innovative business models.
  • Consumer behavior in digital markets.
  • The legal framework in digital markets.
  • Automation and robotics.
  • Human Machine Interaction
  • Cyberphysical Systems
  • Additive Manufacturing
  • Smart Materials Technology
  • Advanced maintenance
  • Modelling, simulation and virtualisation of processes


Specific competences

  • Understand what digital transformation entails and how it impacts the business.
  • Know the consumer purchase processes arising from the digital economy.
  • Know the legal context of digital markets and businesses.
  • Be able to design disruptive business models.
  • Know the technologies linked to productive transformation.
  • Know the possibilities of the application of artificial vision, programmable automata and collaborative robotics in industrial manufacturing.


  • Control of technology and databases, such as SQL or PL/SQL.
  • Programming skills and control of programs such as R.
  • Administration of distributed storage systems.
  • Design of reporting systems for data visualization, especially in business intelligence.
  • Control of Hadoop tools, such as Hive or Pig.
  • Ability in the management of software tools in data structure systems.
  • Data manipulation language instructions, such as data wrangling, data munging or data tyding.
  • Lead scoring.
  • Models based on dynamic pricing.


Specific competences

  • Discover patterns of behavior in large volumes of data.
  • Apply Data Science to solve a real problem through the different steps of: identifying the information, designing the study, analyzing data and building the appropriate model, interpreting the results and issuing technical reports.
  • Identify the usefulness and potential of statistical techniques and data analysis acquired in the different areas of use and know how to apply them properly to draw relevant conclusions. Manage the most important big data tools and software in this area of knowledge with both specific software and R.


Criterion and procedures of the evaluation for all the modules)

  • The evaluation system is based on a continuous evaluation model.
  • The student must pass this module, whose evaluation will have the following proportion
  • 60% exams or homework
  • 40% continuous evaluation

Specific competences

  • The following specific competences will be developed individually or in association:
  • Incorporate technological innovation at the base of the business strategy.
  • Apply knowledge of the new rules of digital business.
  • Apply trends in manufacturing through automation processes.
  • Apply the analysis of large amounts of data to solve business problems.


Steering and tracking system

  • The Master’s thesis will be directed by professors of the Master.
  • All students will be explained what the Master’s Final Project consists of both in the formal and methodological aspects and its presentation before the court.
  • The coordination of the master’s degree will assign a tutor to each student or group of students, depending on the proposals presented by the students and the teaching load of the teachers.

Criterion and procedures of course evaluation

The evaluation system is based on a continuous evaluation model as this Master is formed by six evaluable modules. Each of the modules will consist of one or two subjects of 24 hours.

The student must pass each of the modules and its evaluation will have the following proportion:

  • 60% exams or homework
  • 40% continuous evaluation


In addition to successfully completing the course, the student must accomplish a Master’s Thesis.

The evaluation of the master’s thesis has the following proportion:

  • 50% written facts
  • 50% writing and defending


Students will obtain a final grade of the Master that will be conformed according to the following criterion:

  • 60% corresponding to the average grade of the six modules.
  • 40% corresponding to the grade obtained in the Master’s thesis.

Learning plan


ModuleCreditsTeaching Hours

Strategic Management

Management of technological innovation

2Digital marketing624,0
4Data Analytics and Visualization624,0
5Business Transformation / Industry 4.01248,0
6Big Data and Data Science624,0
7Master’s thesis (Only Master)1240
 Total60 232


Are you interested?