TOPIC
Infrastructure and platforms for Data Science
SUBTOPIC
Data Science/Big Data application design
LANGUAGE
Spanish
ENROLL
On Demand
DURATION
6 days (24 h)
TRAINER
ITI
In this course, a tour of the use of language will be made, from the syntactic base to an advanced functionality oriented towards data analysis, providing tools with which the student can, on their own, enrich and specialize their own repertoire.
Program:
Unit 1. Introduction to Python (1h)
Unit 2. Basic use of Python (3h)
Unit 3. Introduction to “Data Science” (1h)
Unit 4. Exploratory Data Analysis (AED) (3h)
Unit 5. Data processing (4h)
Unit 6. Introduction to Machine Learning (ML) (2h)
Unit 7. Machine Learning (ML) in Python (10h)
Program:
Unit 1. Introduction to Python (1h)
Unit 2. Basic use of Python (3h)
Unit 3. Introduction to “Data Science” (1h)
Unit 4. Exploratory Data Analysis (AED) (3h)
Unit 5. Data processing (4h)
Unit 6. Introduction to Machine Learning (ML) (2h)
Unit 7. Machine Learning (ML) in Python (10h)
Keywords:
Data Analytics, Data Science, Exploratory Data Analytics, Machine Learning, Statistical methods
LEARNING OUTCOMES
Familiarity with Python, its grammar and syntax. Use and preparation of Python code modules, including the main Machine Learning libraries. Preparation and statistical analysis of raw data of any format. Correct graphical representation of data. Informed application of the most common and contemporary Machine Learning models: k-Neighbors, hierarchical clustering, decision trees, neural networks.
PRE-REQUISITES
Programming, Mathematics, statistics
TARGET AUDIENCE
Professional Data Science
COURSE TYPE
Lecture and Hands-on
MATERIALS
Slides, practical exercises
