The large amount of data that we generate in our jobs and our lives, make Data Science one of the most demanded skills and with greater professional projection today and in the near future.
According to the World Economic Forum “Jobs of Tomorrow”, it will experience 40% annual growth and more than 250,000 job opportunities per year.
The Global Impact in Data Analytics program allows participants to acquire these skills by working with real-world data and learning from industry experts. Participants will learn to extract, cleanse, structure, analyze and visualize data in a high-impact, hands-on approach.
On campus: 2 intensive weeks
Upon completion of the program, participants will be able to:
- Obtain a global vision of the key elements of Data Science: business intelligence, business analytics and machine learning.
- Apply the new skills through the complete analysis of a real data set: extraction, transformation, loading, modeling, visualization and effective communication, which helps decision making.
- Obtain a differentiating skill differentiator that is applicable and extremely useful in any profession.
- Launch or drive the professional career towards digital jobs related to data science.
This program is designed to help participants to obtain in the short term a complete vision of the world of data science, either because they want to launch or boost their career towards these digital professions, or because they wish to obtain a differentiating skill applicable and extremely useful in any profession.
Thanks to its progressive training design, it is perfectly valid for profiles with or without previous knowledge.
This intensive program (6 weeks with live classes two days a week in the Online version or 2 weeks of classes in the Presecial version) combines high-impact teaching sessions, with the realization of a real project to apply the learning and additional material to deepen the different areas of interest.
The methodology, based on practical and interactive classes, allows participants to acquire knowledge and exchange ideas and experiences while fostering the creation of new professional contacts.
The evaluation, based on the development of a real data analysis project with mentoring and coaching, allows participants to put into practice the knowledge and resources acquired during the classes and develop their skills in reasoning, analysis and interpretation of data.
|MODULE 1. Extraction||ETL Fundamentals: Data extraction, transformation and loading.|
|MODULE 2. Modeling||Exploratory Data Analysis (EDA): Description, distribution and types of data.
Supervised Machine Learning: Linear regression and classification models.
Unsupervised Machine Learning: Cluster analysis.
|MODULE 3. Visualization||Data visualization: Notions and tools.
Data visualization in R: Using R to visualize quantitative and qualitative data.
|Real data analysis with guided mentoring|