DATA SCIENCE

DEVELOPER

TECH BOOTCAMP

The Data Science Development Bootcamp is an intensive 165 hours on-site program aimed at IT professionals with basic coding knowledge that seek to learn and apply Artificial Intelligence as Data scientists.     

This program starts with data preparation (analysis and cleaning) using Python and R. By applying different methods you will transform data into information with labels, clusters, segmentations and patterns. Finally, you will tackle complex data networks with deep learning and algorithms.

Powered by IMMUNE Coding Institute’s faculty with top IT professionals and experts in Data Science. Top up your career with a hands-on bootcamp with real-world scenarios.

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INTAKE

October 11th 2019

LOCATION

IMMUNE Campus - Madrid, Spain

Paseo de la Castellana 89

PRICE

6.500€

 

DURATION

18 weeks

Fridays 17h - 22h & Saturdays 10h - 15h

REQUIREMENTS

Basic programming knowledge *

*Access to a 80h prework if you lack experience on this field

FOR

IT Professionals that want to acquire a deep understanding of data science

Graduates in Mathematics, Statistics, Computer Science or similar

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Mónica Villas - Program Director

Ex IBM Technology Executive. Technology consultant. Founder of Additum

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Óscar Delgado, IMMUNE Academic Director

PhD Blockchain & Crypto Economy. CISSP, CISM. CTO Noisy

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FACULTY

 
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Juan Benavente

Industry 4.0 & Blockchain Expert - CEPSA

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Juan Brugera

Big Data Engineer - BBVA Data & Analytics

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Carlos Eduardo Chavez

Senior Data Scientist - Whiseathenea

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Ana Laguna

Founder of SoGooD2ata

jaime requejo

CTO Cognitive Solutions Spain, Portugal, Israel & Greece - IBM

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Daniel Villanueva

BigData Developer / Lecturer Project Manager - Indra

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rafael hernández

Data Scientist - BBVA Data & Analytics

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Cristina Soguero

PHD Assistant

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maría hernández

Senior Data Scientist - BBVA Data & Analytics. Lecturer

ACADEMIC PROGRAM

 
 

The program is hands-on, with a very practical focus to learn Artificial Intelligence with Python (90%)  and R (10%). Take an exponential leap in your career and become an expert in the most demanded and ground-breaking field.

 

1: INTRODUCTION TO AI. KEY MATHEMATICAL CONCEPTS FOR AI

This module introduces the basic concepts in AI, and the basic mathematical concepts in Algebra and Statistics which are needed to understand the rest of the topics in the course.

2: DATA MANIPULATION AND ANALYSIS (PYTHON/R)

In this module will cover the key libraries in Python and the basics in R: data access, preprocessing and exploratory analysis to understand the content of the data.

3: SUPERVISED MACHINE LEARNING. CLASSIFICATION AND REGRESSION

This type of learning requires human intervention for the creation of labels in the historical data. In this way the machine will be able to predict a result based on this data.

 

4: UNSUPERVISED MACHINE LEARNING

The objective is to find patterns and structures hidden in the data that was not labeled by humans. A common example is the customer segmentation with similar attribute for marketing campaigns.

Case Study: Applied dimensionality reduction and its effect in the classification techniques.

5: DEEP LEARNING AND NEURAL NETWORKS

Basic principles of Deep Learning ans  key algorithms required to understand the concept of a neural network.

The densely connected network, convolutional neural network (CNN)  and recurrent neural network(RNN) will be covered in this module as well as GANs and Boltzman machines.

Case Study: Audio analysis with TensorFlow.

6: DATA VISUALIZATION

Data Visualization using Python and R libraries together with a grafo visualization. This module will also cover 3D graphics usin Python.

 


7: AI LIFECYCLE & AI COMMERCIAL TOOLS

This module covers the lifecycle from the access to data, preprocessing, analysis, training to the deployment in production. The challenges such as fairness, key regulation topics and the future of AI.

Final project.


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Olga Blanco

Executive Partner Cognitive & Analytics, Data Platforms, IoT, Consulting Leader SPGI - IBM

“It is not just about learning how to use Artificial Intelligence (AI) tools, but also about understanding the key requirements of each industry. The mix of teachers with a lot of experience in technology and round tables with experts from the sector seems to be the right combination for this program”