Data scientist
The program of this course is based on the Python language and its main packages oriented to statistical analysis and machine learning. Also, throughout the course, concepts related to descriptive statistics and inferential statistics are addressed in the different modules. In this way, the topics related to Exploratory Analysis are addressed first and then continue with Machine Learning models.
Required hours:168
PROGRAM EDUCATIONAL OBJECTIVES
Develop, learn the techniques and spectrum of tools that are used in the elaboration of a predictive model, using as a base the Python language and its main packages oriented to statistical analysis and machine learning.
MODULE 1
PYTHON PROGRAMMING FUNDAMENTALS
Through this module, participants will be able to code low/medium complexity pieces of software in Python language to solve a problem, according to industry best practices.
- 16 hours
MODULE 2
DATA COLLECTION AND PREPARATION
Through this module, participants will be able to apply data collection, cleaning, and preparation techniques, using imputation criteria and manipulating data structures as appropriate to meet information needs.
- 24 hours
MODULE 3
EXPLORATORY ANALYSIS AND STATISTICAL PROGRAMMING
Through this module, participants will be able to analyze data using Python language and descriptive statistics concepts for the exploration and characterization of information.
- 20 hours.
MODULE 4
STATISTICAL INFERENCE
Through this module, participants will be able to make statistical inferences to a sample, for the estimation of a population.
- 24 hours.
MODULE 5
SUPERVISED MACHINE LEARNING
Through this module, the participants will be able to elaborate a predictive model from a data set using supervised machine learning techniques, implemented in Python language to solve a problem.
- 32 hours.
MODULE 6
UNSUPERVISED MACHINE LEARNING
Through this module, the participants will be able to elaborate a predictive model from a data set using unsupervised machine learning techniques implemented in Python language to solve a problem.
- 16 hours.
MODULE 7
DEEP LEARNING FUNDAMENTALS
Through this module, the participants will be able to Elaborate a predictive model by applying neural networks and using Python language to solve a problem.
- 16 hours.
MODULE 8
FUNDAMENTALS OF BIG DATA
Through this module, participants will be able to develop a predictive model using large volumes of data to solve a problem.
- 20 hours.
REQUIREMENTS FOR APPLICATION
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- To be Chilean or foreigner with definitive permanence in the country.
- Be a technician, professional, or graduate in specific careers associated with the course to which you are applying.
- Have specific and accredited work experience associated with the type of ICT specialization to which they are applying.
- Technical, professional, or university degree in a technological, commercial, industrial, mathematical, statistical, or engineering career.
- At least 2 years of work experience.
- Test de Razonamiento Lógico.
- Test of basic knowledge of statistics and programming taken at www.becascapitalhumano.cl
- In the case of the Digital Marketing, E-Commerce, and Creative Services courses, those who are owners, partners, shareholders, and/or employees of a company may also apply.
Characteristics of Scholarship
- Talento Digital courses are online, mixing asynchronous content with synchronous distance classes, with direct assistance from the designated instructor.
- Tuition fee $210,000.
- Developed by Universidad del Desarrollo.
