Master in Data Strategy & Analytics

Data storytelling

Strategies to connect data analysis with business objectives, develop stories that connect with different types of audiences and methods of creatively presenting data.

Data Governance & Ethics

We'll look at best practices for managing data, the full range of responsibilities that come with using data in automated decision making, including data security, privacy and transparency.

Data Strategy & Analytics

Data management to achieve analytical advantages and achieve our growth objectives.

BI Tools: Power BI, Qlikview, Tableau & Excel

We will analyze data with an excellent visualization and presentation layer in an understandable, easy and intuitive format.

Data Visualization

How to display different types of data? What techniques to use? Use of matplotlib, bokeh and seaborn among others.

Data Analytics with Python

Python as a framework for the Data Analytics specialist. Notebook development, use of pandas and numpy. Data processing from structured (CSV, REST, Logs) and unstructured (Web) sources.

Data Science Fundamentals

Introduction to fundamental data science concepts. Presentation of the general framework of reference.

Machine Learning & Deep Learning

Classification problems. How to evaluate the results? How to build the datasets? Main algorithms (knn, decision trees, support vector machines, deep neural networks, xgboost).

Data Pre-Processing

How to properly pre-process the data? Application of filters, data anonymization, attribute selection, sampling and dimensionality reduction. Preprocessing of data sources in text mode.

Final Project

The topic may be proposed by the student or selected from a list provided by MIOTI.

Databases & SQL

Master the main databases and the SQL language, learn the latest techniques for storing, manipulating and extracting data recorded in relational databases.