OVERVIEW
The Data Science Expert program is designed to offer the necessary knowledge in the treatment and advanced analysis of data.
Its main objective is to train professionals in the management of preprocessing techniques that allow determining the quality of the data and validating the possibility of addressing automatic learning tasks for the detection and prediction of patterns.
Students will learn to preprocess and clean data, regardless of its source. They will acquire techniques to streamline the steps required for implementing advanced analytics projects. Additionally, they will gain knowledge of various machine learning techniques, including supervised, unsupervised, and reinforcement learning. This approach will enable them to apply these techniques themselves after preparing the data for this purpose.
BENEFITS
- You will train with the best specialists in the field of science and data mining.
- You will identify the appropriate techniques to measure or achieve the desired data quality 2. regardless of the environment you are in and the source of the data.
- You will get a global reference view to address preprocessing tasks within advanced analytics and machine learning projects.
- You will learn about the most used machine learning techniques today, going through the context of supervised, unsupervised and reinforcement learning.
- You will develop data analyst skills capable of executing advanced analytics projects within the area of data science.
PARTICIPANT PROFILE
This course is aimed at students who have a degree related to the area of knowledge (Graduate in Computer Engineering, Bachelor of Computer Science, Engineer or Technical Engineer in Computer Science, Graduate in Telematics Engineering, Engineer or Technical Engineer in Telecommunications, Bachelor / Graduate in Mathematics, Bachelor / Diploma / Graduate in Statistics, etc.) or when you have demonstrable professional experience, with no less than two years of experience performing tasks related to the field of knowledge.
METHODOLOGY
ONLINE
- Methodology of the Proeduca group, leader in online education. Flexible, personalized and effective study method.
- 100% online. Study where and when you want, manage your time and combine your training with your personal and professional life.
- Based on live classes to interact live with the teacher and classmates, online activities and a large amount of additional content and resources at your disposal to deepen your knowledge of the topics covered.
- Follow-up with a personal tutor who accompanies you throughout the program. With your effort and our support you will achieve your academic goals!
CURRICULUM SCHEDULE
| Title |
|---|
| MODULE 1. Data Handling -Descriptive data analysis -Data normalization and transformation -Mining, transformation, and uploading data |
| MODULE 2. Automatic Learning I -Data handling for machine learning -Algorithm optimization -Temporal series. |
| MODULE 3. Automatic Learning II -Scanning and cataloging -Metasploit y Post-exploitation -Malware analysis fundamentals |