Catálogo Tokioschool

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  • Presentation
  • Methodology
  • Your classes
  • Online platform
  • Contents overview​
  • Digital teachers
  • Internships
  • Certifications
  • We are Tokio
  • Contact
  • Presentation
  • Methodology
  • Your classes
  • Online platform
  • Contents overview​
  • Digital teachers
  • Internships
  • Certifications
  • We are Tokio
  • Contact
  • Presentation
  • Methodology
  • Your classes
  • Online platform
  • Contents overview​
  • Digital teachers
  • Internships
  • Certifications
  • We are Tokio
  • Contact
  • Presentation
  • Methodology
  • Your classes
  • Online platform
  • Contents overview​
  • Digital teachers
  • Internships
  • Certifications
  • We are Tokio
  • Contact

COURSE

Front-end

Development

Discover Tokio School

Presentation

The Internet is an essential part of our daily lives, reaching almost absolute levels in Spain and the rest of the world (80% of households and 93% of mobile users have an Internet connection). For this reason, web design and development has become one of the most important professions in recent years and one with the best job opportunities. Becoming an expert in the use of programming languages such as HTML5, CSS3 or JavaScript is a great attraction on any CV. Learn to master these languages to be able to work in a software development company or manage an internal app for a large company, for example. So, if you are looking for a dynamic profession with an unbeatable future, this is the training you have been looking for.

Objectives

Learn useful techniques in the world of programming
Separate content between structure and style
Create a customised web page
Design and structure web applications
Learn how to handle HTML5, CSS3 and JavaScript
Know frameworks such as NodeJS

Salary

United Kingdom / Javascript

The wage for JavaScript developers in London is 32% higher than the national average, at £66k ($88k) per year. If we talk about the lower and upper wages in London, it is £22k ($29k) and £132k ($177k) respectively.

Average salary for JavaScript developers in the UK per year:

  • Junior: $55k (£41k);
  • Middle: $76k (£57k);
  • Senior: $94k (£71k).
Belgium / Javascript

According to the salary survey conducted by The Economic Research Institute annual compensation data can be ranked as follows:

  • Junior: $64k (€54k);
  • Middle: $90k (€76k);
  • Senior: $111k (€94k).

 

Based on the above data, it can be concluded that the hourly rate in Belgium averages about $44 (€37).

Netherlands / Javascript

According to the data provided the salary level by experience looks like this:

  • Junior: $64k (€54k);
  • Middle: $90k (€76k);
  • Senior: $112k (€94k).

 

By 2025, the average wage level is expected to grow by 11% to $100k (€84k) instead of $90k (€76k).

A JavaScript engineer in the Netherlands makes €15 per hour. If you look at the level of annual salaries by cities, the figures available for Amsterdam are €58k.

Denmark / Javascript

The annual salary scale for JavaScript developers in Copenhagen, depending on their experience:

  • Junior: $82k (DKK 518k);
  • Middle: $116k (DKK 727k);
  • Senior: $143k (DKK 899k).

 

Based on this data, the hourly rate can be calculated. In Copenhagen it is $56 (DKK 350), while in the whole of Denmark it is $52 (DKK 328).

For Denmark as a whole, the average annual pay should increase by 10% and reach $119k or DKK 747k in 5 years. Average annual JS developers salaries in Denmark by experience are as follows:

  • Junior: $78k (DKK 486k);
  • Middle: $109k (DKK 682k);
  • Senior: $134k (DKK 843k).

Career opportunities

Front-end developer
Front-end developer
UX/UI Designer
UX/UI Designer
Web application developer
Web application developer
I have finished my training in Python and I am going to specialise in the profession of the future: Artificial Intelligence. I repeat with Tokio because my level of satisfaction, especially with the teacher, is 120%.
Oriol MarcoPython Programming
Oriol Marco
I look for two things in training: content and attention and I have had that in Tokio. After two engineering degrees and a master's degree in data analysis, in just two months I have completed the training that will allow me to return to my passion: programming.
Nayra BlancoJava Programming
Nayra Blanco
My main objective is to reorient my career and I looked for a course that would open doors for me. What I like most about Tokio is the richness of the teaching material and, above all, the follow-up given to the student.
Carles RoigFront-End Programming
Carles Roig

Methodology

Tailor-made method
Digital teachers
Personalised tutoring
Practical training
Online classes
Tailor-made method

Our courses do not have a start and end date. With Tokio’s 100% online training programme, you decide your pace, circumstances and capabilities and we follow you. Ours is «tailor-made» learning.

Digital teachers

They are your teachers, experts with real knowledge that will help you to improve your knowledge of this profession.

Personalised tutoring

Our educational advisors will accompany you throughout your training. They will help you achieve your goals through realistic objectives, organisation and motivation for tokiers!

Practical training

Self-assessment questionnaires, final exams, exercises, case studies… Learning by doing! You will learn by doing. In addition, you will have up to 300 hours of quality professional internships in companies in the sector.

Online classes

You will have live classes. And if you have not been able to attend, no problem! We’ll upload them to the virtual platform so you can watch them as many times as you want.

Final project
Soft Skills
Job Orientation
Employment Observatory
Final project

You’re almost there! To conclude your training, you’ll have to demonstrate everything you’ve learned through a project.

Soft Skills

You will receive extra training to improve your skills (communication, leadership, teamwork…) thanks to our short courses.

Job Orientation

We will give you all the keys to succeed in any selection process.

Employment Observatory

We put at your disposal, on the student platform, an Employment Observatory where you will find the best job opportunities according to your preferences and your sector.

Your classes

Live
You can connect live to the classes with your specialist teacher. The online classes will follow the syllabus and raise new questions and information that goes beyond the theoretical content of the books. At the end of each class you can ask your questions so that the teacher can answer them live.
On a recorded basis
If you can’t attend a class live, don’t worry! All classes are recorded and uploaded to your platform so that you can access them whenever you want.
Doubt resolution
The digital teachers will dedicate the whole class to solve your doubts, exercises or practical cases. It is an excellent opportunity to interact with the specialist teacher, ask your questions and learn from the doubts of other classmates.
Masterclass

You will be able to attend online masterclasses given by renowned professionals in the sector who collaborate with Tokio School by sharing their experience. These sessions will also be participative and you will be able to ask them your questions.

Online platform

Our methodology is designed so that you become

the protagonist of the learning process.

Content overview

Module 1: Introduction to HTML5

Unit 1. Knowing HTML5 and the document structure

  • Brief history of HTML5 
  • Installing Visual Studio Code as an IDE
  • Basic structure of an HTML5 document

Unit 2. Semantic and text containers

  • Types of semantic containers
  • Types of text containers

Unit 3. Semantic format of the text

Unit 4. Links and tables

Unit 5. Forms

Unit 6. Images and multimedia

  • HTML5 tags and attributes
  • Multimedia tags in HTML5
Module 2: Getting to know CSS3

Unit 1. Style sheets.

  • Brief history of CSS3
  • Using style sheets with Visual Studio Code
  • Writing in CSS

Unit 2. CSS properties for text, lists and tables.

  • Font-family, Font-style, Font-weight and Font-size.
  • Customised bullets
  • Vertical menus

Unit 3. Format and layout.

Unit 4. Responsive design.

  • Media Queries
  • View Meta Tag

Unit 5. Template design: Bootstrap 4.

  • Using Bootstrap 4
  • Components and colours

Unit 6. Good practices in HTML5 and CSS3.

Unit 7. Design with mockups.

Unit 8. Design with templates: Bootstrap 4.

Unit 9. Content Management Systems (CMS).

Module 3: Introduction to JavaScript

Unit 1. JavaScript language.

Unit 2. General concepts: Variables and operators.

  • Conditional processes
  • Iterative structures
  • Single and multidimensional tables
  • Procedures, functions and argument passing

Unit 3. Conditional structures.

Unit 4. Iterative structures.

  • Loop While
  • Loop do-while
  • Loop for

Unit 5. Tables.

Unit 6. Object-oriented programming in JavaScript.

Unit 7. Objects in JavaScript.

Unit 8.  Data forms.

  • Basic properties of forms and elements
  • Form utilities
  • Validating a form

Unit 9. DOM model.

  • Introduction.
  • Procedures.
  • Functions
  • Methods

Unit 10. XML Stream Browsing via DOM.

Module 4: Advanced JavaScript

Unit 1. Cookie management in JavaScript.

Unit 2. Local storage.

  • LocalStorage and sessionStorage
  • Implementation

Unit 3. Remote storage.

  • XML format
  • JSON format

Unit 4. Geolocalization in JavaScript.

Unit 5. Design and graphics.

  • Canvas: Explanation and uses 
  • Libraries for making graphics in JavaScript

Unit 6. First steps with React.

  • Introduction and create-react-app
  • Directory structure
  • JSX

Unit 7. Components and properties in React.

  • Components
  • Props
  • Hello world

Unit 8. Advanced events and routes in React.

Unit 9. Good practices with JavaScript.

Sukiru: habilidades para samuráis digitales

Tu formación incluye nuestro Curso Scrum Manager para que te conviertas en todo un experto en la aplicación de esta metodología de trabajo a nivel de equipos y puedas conseguir la certificación oficial Scrum Master

Conoce todos los detalles de este curso

Sukiru: soft skills for digital samurai

You will receive extra training to improve your skills (communication, leadership, teamwork…) thanks to our short courses.

#alwaysforward

Digital teachers

Zac is a Training and Web Development professional who loves helping students to build their dreams with code. He has almost a decade of experience working with some of the worlds largest e-commerce and gaming platforms.
Zac WarnerSensei
Zac-Warner

Time to get on the tatami

Do you want to show what you’re worth? At Tokio School we have agreements with more than 3,000 companies in the technology and digital sector. You can do up to 300 hours of optional internships while expanding your network and your CV. Where would you like to do an internship? Suggest companies! You will be part of Tokio Net, our network of students and alumni.

Certifications

Once you have finished your training you will receive the following qualifications:

diploma-frontend

Front-end development course

*Training not officially recognised for academic purposes.

We are Tokio

We’re not the kind of people who like to pin medals on themselves, but if others do…

excellence-2022_A-_Tokio_best_training_center_esports-2

TOP Educational Agreements

Contact

Do you have any questions? We are at your disposal for whatever you need.

+353 (1) 9026926

+31 (20) 3694593

+44 (20) 38079342

+32 (2) 7810204

+45 (7) 0890272

The content of this catalogue is subject to change at the discretion of the centre's management. The information not related to the centre contained in this catalogue is subject to the decision of the administration or competent authority.

Training is not approved for official academic purposes.

#alwaysforward

Módulo de Metodologías ágiles

Consigue la Certificación de Scrum Master

Al igual que evolucionan la tecnología y los lenguajes de programación, las metodologías de trabajo también cambian con el tiempo. Las organizaciones y empresas buscan constantemente formas de agilizar procesos, reducir costes y acelerar la producción para obtener mayores beneficios y es aquí donde la figura del Scrum Master es clave para gestionar de forma efectiva esos proyectos y alcanzar los resultados esperados. 

Nuestro curso en metodologías ágiles con Certificación Scrum te permitirá dominar esta metodología y convertirte en Scrum Master, una de las titulaciones y profesiones más demandadas actualmente. Además, te permitirá entender y aplicar otras metodologías Agile como Kanban, cada vez más en vigor en un mercado tan dinámico como el actual.

Salidas laborales

Scrum master
Scrum master
Consultor de proyectos ágiles
Consultor de proyectos ágiles
Consultor transformación Agile
Consultor transformación Agile
Módulo 1. Introducción a la gestión ágil

Agilidad

  • Gestión predictiva 
  • Gestión ágil
  • Manifiesto ágil: valores y principios
  • Scrum

Desmontando la gestión de proyectos

  • Desarrollo, Trabajo y Conocimiento
  • Ingeniería secuencial, concurrente y agilidad

Diferenciando las prácticas de los principios y valores Scrum

  • Scrum técnico
  • Scrum avanzado
Módulo 2. El ciclo Scrum I

Roles

  • Propietario del producto
  • Equipo
  • Scrum Master

Artefactos

  • Pila del producto
  • Pila del sprint
  • Incremento

Eventos

  • Sprint
  • Reunión de planificación del sprint
  • Scrum diario
  • Revisión del sprint
  • Retrospectiva del sprint

Medición y estimación

Módulo 3. Principios y valores de Scrum II

Principios y valores

  • Las personas y sus roles
  • Artefactos
  • Eventos

Prácticas para flexibilizar Scrum

  • Gráfico burn down
  • Estimación de póquer
  • Kanban
  • Técnicas a prueba de errores
  • …
Módulo 4. La certificación Scrum Máster

Certificación vs Acreditación

  • Scrum Manager y Scrum Máster

Puntos de Autoridad. PDAs

  • Actualización de la Certificación

El examen

Certificación

Una vez realices este curso troncal, podrás presentarte al examen oficial de Scrum Manager. Si lo apruebas, recibirás el certificado de Scrum Master:

Machine Learning

Machine Learning was born from pattern recognition, but today it allows us to develop applications that improve their performance by «learning» from data collected in past situations. In this Python specialisation you will be able to apply Machine Learning to real projects, including preparation and related tasks, deployment in production and the lifecycle of a model.

MODULE 1: INTRODUCTION TO MACHINE LEARNING

Unit 1: Introduction to Big Data and Machine Learning

  • Introduction to Machine Learning
    • The theory of gravity
    • The scientific method
    • Mathematical models
    • Scientific method applications
    • Data science
    • Introduction to Big Data
    • Introduction to Machine Learning
    • The equation of the straight line
    • Model training
    • Working with Machine Learning models
    • Machine Learning applications
    • AlphaGo
  • Linear algebra
    • Relationship to the areas of big data, machine learning and artificial intelligence
    • Elements
    • Operations and properties

Unit 2: Work environment

Unit 3: Python and Scikit-learn numeric libraries

MODULE 2: SUPERVISED LEARNING

Unit 1: Linear regression 

  • Simple
    • Model equation
    • Graphical representation
    • Types of variables
  • Multivariable
    • Data modelling
    • Curve modelling
    • Analytical resolution
    • Cost function
    • Solving by iterative methods
    • Resolution algorithm

Unit 2: Gradient descent optimisation

  • Gradient descent
  • Convergence
  • Local and global minima
  • Learning ratio
    • Learning ratio choice
  • Training algorithm

Unit 3: Standardisation, regularisation and validation

  • Standardisation
    • Problem
    • What is standardisation?
    • Updated training algorithm
  • Regularisation
    • Deviation and variance
    • Regularisation
    • Regularised cost function
  • Cross-validation
    • Resolution methods
    • Dataset subdivision
    • K-fold
    • Updated training algorithm

Unit 4: Bayesian models and model evaluation

  • Example: carcinogenic cells’ classification
  • Sensitivity and specificity

Unit 5: Classification

  • Decision trees
    • Representation
    • Main concepts
    • Categorical and continuous target variables
    • Node splitting
    • Advantages and disadvantages of decision trees
    • Limitations on tree size
    • Tree pruning
    • Decision trees vs. linear models
    • Bootstrapping
    • Training algorithm
  • Logistic regression
    • Data modelling
    • Binary and multi-class classification
    • Hypothesis
    • Activation function: sigmoid
    • Cost function
    • Training algorithm: binary classification
    • Training Algorithm: multiclass classification
  • Classification by SVM
    • Logistic regression vs. SVM
    • Hypothesis
    • Kernels and landmarks
    • Hypothesis transformation
    • Types of kernels available
    • Cost functions
    • Regularisation parameter
    • Training algorithm: multiclass classification

Unit 6: Introduction to neural networks 

  • Natural neurons
  • Artificial neurons
  • Perceptron
  • Multi-layer or deep neural networks
    • Propagation of predictions
    • Cost function
    • Training
    • Multi-class classification
    • Training algorithm: binary classification
MODULE 3: UNSUPERVISED LEARNING

Unit 1: Optimisation by randomisation

  • Problem: local minima
  • Multiple initialisations
  • Implementation

Unit 2: Clustering

  • Differences between clustering and classification
  • K-means 
  • Other clustering algorithms
MODULE 4 – SEMI-SUPERVISED LEARNING

Unit 1: Anomalies detection

  • The problem
  • Anomalies in supervised vs. unsupervised and semi-supervised learning
  • Model representation
  • Choice of features
  • Normal or Gaussian multivariate distribution
  • Training algorithm

Unit 2: Recommendation systems

  • Linear regression recommendation systems
  • Recommendation systems approach
  • Cost function
  • Training algorithms
  • Prediction performance
  • Similarity between examples

Unit 3: Genetic algorithms

  • Natural evolution
  • Natural evolution of behaviour
  • Main concepts
  • Algorithms applied to optimisation
  • Examples
MODULE 5: AUTOMATIC LEARNING SYSTEMS DEVELOPMENT

Unit 1: ML systems approach

  • Initial approach
    • Data cleansing and transformation
    • Large-scale implementation

Unit 2: Feature engineering

  • Definition and characteristics
  • Creation of characteristics
  • Problems and solutions
  • Data quality

Unit 3: Principal Components Analysis (“PCA”)

  • Variables representation
  • Dimensionality reduction
  • Definition and applications
  • Visual representation

Unit 4: Assemblies

  • Definition and applications
  • Types of errors
  • Assembly techniques
  • Bagging
  • Max voting
  • Mean and weighted mean
  • Random forest
  • Boosting and adaptive boosting or AdaBoosting
  • Stacking

Unit 5: Models’ evaluation and improvement

  • Deviation and variance
  • Evaluation metrics: linear regression
  • Evaluation metrics: classification
  • Deviation and variance avoidance
  • Error analysis and evaluation of results 

Unit 6: Operations in ML

  • ML Engineering 
  • Operations in ML