Onderwerp
Automatisering & ICT/IT
Communicatie
Financieel
HR
Inkoop & logistiek
Management
Secretarieel & Administratief
Marketing
Opleiding & Onderwijs
Persoonlijke Effectiviteit
Productie, techniek & bouw
Kwaliteit- & Projectmanagement
Sales
Vitaliteit & Gezondheid
Taalcursus
Zorg & Verzorging
Juridisch
Internet & Media
Arbo & Veiligheid
Hobby & Vrije Tijd
Vastgoed & Makelaardij
Abonnementen
Locatie
Niveau
Type
Keurmerk

Opleidingen

68.959 resultaten

PySpark for Big Data

Amsterdam ma 15 jun. 2026 en 9 andere data
In the course PySpark for Big Data participants learn to use Apache Spark from Python. Spark Architecture The course PySpark for Big Data discusses the architecture of Spark, the Spark Cluster Manager and the difference between Batch and Stream Processing. Hadoop After a discussion of the Hadoop Distributed File System, parallel operations and working with RDDs, Resilient Distributed Datasets are discussed in the course PySpark for Big Data. The configuration of PySpark applications via SparkConf and SparkContext is also explained. MapReduce en SQL Extensive consideration is given to the possible operations on RDDs, including map and reduce. The use of SQL in Spark is also discussed. The GraphX library is discussed and DataFrames is discussed. Iterative algorithms are also treated. Mlib library Finally the course PySpark for Big Data pays attention to machine learning with the Mlib library. Audience PySpark for Big Data The course PySpark for Big Data is intended for developers and upcoming Data Analysts who want to learn how to use Apache Spark from Python. Prerequisites training PySpark for Big Data To participate in this course, some experience with programming is beneficial for understanding. Prior knowledge of Python or big data handling with Apache Spark is not required. Realization course PySpark for Big Data The theory is treated on the basis of presentations. Illustrative demos are used to clarify the concepts discussed. There is ample opportunity to practice and alternate theory and practice. The course times are from 9.30 am to 4.30 pm. Certification course PySpark for Big Data Participants receive an official certificate PySpark for Big Data after successful completion of the course. Modules Module 1 : Python Primer Python Syntax Python Data Types List, Tuples, Dictionaries Python Control Flow Functions and Parameters Modules and Packages Comprehensions Iterators and Generators Python Classes Anaconda Environment Jupyter Notebooks Module 2 : Spark Intro What is Apache Spark? Spark and Python PySpark Py4j Library Data Driven Documents RDD's Real Time Processing Apache Hadoop MapReduce Cluster Manager Batch versus Stream Processing PySpark Shell Module 3 : HDFS Hadoop Environment Environment Setup Hadoop Stack Hadoop Yarn Hadoop Distributed File System HDFS Architecture Parallel Operations Working with Partitions RDD Partitions HDFS Data Locality DAG (Direct Acyclic Graph) Module 4 : SparkConf SparkConf Object Setting Configuration Properties Uploading Files SparkContext.addFile Logging Configuration Storage Levels Serialize RDD Replicate RDD partitions DISK_ONLY MEMORY_AND_DISK MEMORY_ONLY Module 5 : SparkContext Main Entry Point Executor Worker Nodes LocalFS SparkContext Parameters Master RDD serializer batchSize Gateway JavaSparkContext instance Profiler Module 6 : RDD’s Resilient Distributed Datasets Key-Value pair RDDs Parallel Processing Immutability and Fault Tolerance Transformation Operations Filter, groupBy and Map Action Operations Caching and persistence PySpark RDD Class count, collect, foreach,filter map, reduce, join, cache Module 7 : Spark Processing SQL support in Spark Spark 2.0 Dataframes Defining tables Importing datasets Querying data frames using SQL Storage formats JSON / Parquet GraphX GraphX library overview GraphX APIs Module 8 : Broadcast and Accumulator Performance Tuning Serialization Network Traffic Disk Persistence MarshalSerializer Data Type Support Python’s Pickle Serializer DStreams Sliding Window Operations Multi Batch and State Operations Module 9 : Algorithms Iterative Algorithms Graph Analysis Machine Learning API mllib.classification Random Forest Naive Bayes Decision Tree mllib.clustering mllib.linalg mllib.regression
€2.450
Klassikaal
max 12
3 dagen

Data Analysis with Python

Amsterdam ma 15 jun. 2026 en 9 andere data
In the course Data Analysis with Python you will learn how to use the Python language and Python libraries in Data Analysis projects. Python Overview The course Data Analysis with Python starts with a bird's eye view of the Python syntax aspects that are important in Data Analysis projects. Variables, data types, functions, flow control, comprehensions, classes, modules and packages are discussed. The operation of the Jupyter notebooks, the IPython shell and installing Python packages in Anaconda are also treated. Numpy Next the course Data Analysis with Python pays attention to the NumPy package with which large data sets can be processed very efficiently. NumPy's ndarray object and its methods are treated and attention is paid to the different array manipulation techniques with broadcasting and vectorized operations. Pandas Then use of the Pandas library for data analysis is on the schedule of the course Data Analysis with Python. The pandas library introduces two new data structures in Python that use Numpy and are therefore fast. The data structures are DataFrame and Series and extensive details are given on how to use them for data analysis when inspecting, selecting, filtering, combining and grouping data. MatPlotLib Also discussed in the course Data Analysis with Python is the MatPlotlib library, which is closely integrated with NumPy and is a very powerful tool for creating and plotting complex data relationships. Scikit-Learn Finally attention is paid to the essentials of the Scikit-Learn library for modeling. The course Data Analysis with Python uses many practical examples and shows how one- and two- and three-dimensional data sets can be visualized. Audience Course Data Analyse with Python The course Data Analysis with Python is intended for data analysts who want to use Python and the Python libraries in Data Analysis projects. Prerequisites training Data Analyse with Python To participate in this course knowledge of and experience with any programming language or package such as SPSS, Matlab or VBA is desirable. The course starts with a discussion of the principles of the Python programming language. Realization course Data Analyse with Python The theory is discussed on the basis of presentation slides. Illustrative demos clarify the concepts. The theory is interchanged with exercises. The Anaconda distribution with Jupyter notebooks is used as a development environment. Course times are from 9:30 to 16:30. Official Certificate Data Analysis with Python After successful completion of the course participants receive an official certificate Data Analysis with Python. Modules Module 1 : Python Language Syntax Python Features Running Python Anaconda Distribution IPython Shell Interactive and Script Mode Python Data Types Numbers and Strings Sequences and Lists Sets and Dictionaries Python Flow Control Exception Handling Module 2 : Functions and Modules Pass by Value and Reference Scope of Variables EFAP principle What are comprehensions? Lambda Operator Filter, Reduce and Map List comprehensions Set and Dictionary comprehensions Creating and Using Modules import Statement from…import Statement Module 3 : Classes and Objects Creating Classes Creating and Using Objects Accessing Attributes Property Syntax Constructors and Destructors Encapsulation Inheritance super Keyword Checking Relationships issubclass and isinstance Overriding Methods Module 4 : Numpy NumPy Numerical Types Data Type objects dtype attributes Slicing and Indexing Array comparisons Manipulating array shapes Stacking and Splitting arrays any(),all(), slicing, reshape() Manipulating array shapes Methods of ndarray Views versus copies ravel(),flatten(),transpose() Module 5 : Pandas Pandas DataFrame Import Data Inspect Data Data Visualization DataFrame Data Types Indexing and selection Data operations in pandas Missing Data Hierarchical Indexing Plotting with Pandas Combining Datasets Exploratory Data Analysis Module 6 : Data Manipulation Indexing Data Frames .loc and .iloc Accessor Slicing and Indexing a Series Filtering with Boolean Series Zeros and NaNs all and any Nonzeros Using map Function Hierarchical Indexing Rearranging Data Reshaping by Pivoting Transformation and Aggregation Grouping Data Module 7 : MatplotLib Simple Plots Plot format String Subplots Histograms Logarithmic Plots Scatter plots Fill between Legend and Annotations Three Dimensional Plots Contour Plots Transformations Projections Module 8 : Time Series Indexing Pandas Time Series Reading and Slicing Times Using a DatetimeIndex Reindexing the Index Separating and Resampling Rolling mean and Frequency Resample and Roll with it Manipulating Time Series Method chaining and Filtering Missing values and Interpolation Time Zones and Conversion Plotting Time Series Module 9 : SciKitLearn Essentials SkiKit Learn library Machine learning essentials Supervised and Unsupervised Feature matrix Target array Estimator API Hyperparameters Fit method Predict method Model Selection Linear Regression Logistic Regression
€2.650
Klassikaal
max 12
4 dagen

Data Analysis with R

Amsterdam ma 29 jun. 2026 en 9 andere data
In the course Data Analysis with R you will learn programming in the R language and how you can use R for data analysis and visualization. R Intro The course Data Analysis with R starts with the installation of R and the R Studio development environment. The basic syntax of R and the installation of R packages are also discussed. Plotting in R Next you will learn how you can quickly gain insight into the data with the ggplot2 package by means of plots. The different plot types, themes and layouts are discussed as well. Transformations Then it is time for the dplyr package with which common data transformation problems such as filtering, sorting, summation and grouping can be solved. Data Cleaning Presenting data with the rmarkdown package is also covered. As well as tidying raw data with the tidyr package, where columns become variables and rows become observations. Date and Times Time series occur in many data sets. The processing of these time series is addressed with the lubridate package that has many useful functions for processing dates and time. Data Import Part of the course program is also the import of data from CSV files and file formats from other statistical packages such as SPSS or SAS. Reading from and writing to databases is also treated. Statistical Analysis Finally the course Data Analysis with R deals with statistical analysis models such as linear and non-linear models, variable transformations and regressions. All this is supported with many practical examples and can also be applied to cases that are brought along by the students. Audience Course Data Analysis with R The course Data Analysis with R is intended for Big Data analysts and scientists who want to use R to analyze their data and to make static analyzes. Prerequisites Data Analysis with R Experience with programming is beneficial to good understanding but is not required. Realization Training Data Analysis with R The theory is discussed on the basis of presentations and examples. The concepts are explained with demos. Then there is time ample to practice with it yourself. R-Studio is used as a development environment. Course times are from 9:30 am to 16:30 pm Certification Course Data Analysis with R After successful completion of the course the participants receive an official certificate R Programming. Modules Module 1 : Intro R Overview of R History of R Installing R The R Community R Development R Studio R Console R Style Using R Packages Cheatsheets R Syntax R Objects Module 2 : Graphics and Plots ggplot2 Graphics Devices and Colors High-Level Graphics Functions Low-Level Graphics Functions Graphical Parameters Controlling the Layout Changing Plot Types Quick Plots and Basic Control Aesthetics Changing Plot Types Labels Themes and Layout Module 3 : Transformations dplyr R Functions Functions for Numeric Data Scoping Rules mutate arrange group by summarize select filter joining dataframe Module 4 : Presentation rmarkdown Reproducible research Reporting Sharing results Repetitive Tasks Family of apply Functions apply Function lapply Function sapply Function tapply Function Module 5 : Data Cleaning tidyr spread gather seperate unite Logical Data Missing Data Character Data Duplicate Values NA’s Module 6 : Date Times Time and Date Variables lubridate Setting a datetime Getting values from a datetime strftime Command strptime Command as.Date function Datetimes Calculations difftime Command Time Series Analysis Module 7 : Data Import R Datasets Data.Frames Importing CSV Files Import from Text Files Import from Excel Import from Spss or SAS Connecting to a database Connecting to a cluster Databases and ODBC dbplyr Module 8 : Linear Models What is a model? Statistical Models in R How to evaluate a model? How to use a model? Simple Linear Models logistic regression linear regression R squared p values confidence intervals Module 8 : Non-Linear Models Decision Trees random forest boosting overfitting Optional material : Interactive dashboards with Shiny Web Scraping Writing packages Spark Functional programming
€2.650
Klassikaal
max 12
4 dagen

Database Design

Amsterdam do 25 jun. 2026 en 9 andere data
In the course Database Design participants learn the techniques and considerations for creating a well-structured database. Intro Database Management Systems The course Database Design starts with a discussion of the basic architecture of Database Management Systems. Attention is paid to the Database Schema and the differences between the conceptual, logical and physical model. The role of SQL, Data Definition Language (DDL) and Data Manipulation Language (DML) is also discussed. Database Design Subsequently the phases of Database Design and the components of a database are treated. The ERD Model and the UML Model are covered here. Possible design errors and the application of constraints are also reviewed. ER Modeling In the ER Modeling section participants learn how to discover the entities and their relationships and map them to tables. They learn the principles of Entity Relationship Modeling. Also treated is how to find and model attribute domains. Table Mapping Then attention is paid to how entities and their relations can be translated into tables in a relational database. The different mapping strategies for hierarchies of entities are also covered such as table per class, table per hierarchy and the use of discriminator columns. UML Modeling Next to the use of Unified Modeling Language UML for database design is treated. The UML syntax is discussed as well as UML elements such as interfaces, associations, composition, generalization and dependencies. Normalization and Optimization The process of normalization, the different normal forms and the removal of duplicate data are explained by means of practical examples. Finally, a number of optimization techniques, such as the use of indexes, that can improve the speed of databases are discussed. Audience Course Database Design The course Database Design in intended for Web developers, web application developers, database administrator, webmasters and web project managers. Prerequisites Course Database Design To join the course Database Design no specific skills or knowledge is required. General knowledge of system design is helpful to a proper understanding. Realization Training Database Design The theory is treated using presentation slides. Demos are used to clarify the theory. There is ample opportunity to practice. The course material is in English. The course times are from 9.30 up and to 16.30. Certification Database Design Participants receive an official certificate Database Design after successful completion of the course. Modules Module 1 : Intro DBMS What is a DBMS? DBMS Abstraction Levels Data Independence Database Model Types of Databases Database Schema Conceptual Model Logical Model Physical Model SQL Language DDL and DML Language Application Interfaces Transactions DBMS Architecture Module 2 : Database Design What is Database Design? Database Design Phases Benefits of Phases Conceptual Data Model Entity Relationship Model UML Model Structuring the Model Design Errors Data Errors Constraints Database Constraints Naming Schema Elements Data Interpretation CASE Tools Module 3 : Entity Relationship Modeling E-R Model Components Identification Guidelines Entities versus Entity Classes Attributes Entities versus Attributes Classification of Attributes Attribute Domains Relationships Degree of relationships Relationship Cardinalities Notation of Cardinalities Removing M:N relations Requirement Analysis Resulting ER Diagram Module 4 : Advanced Er Modeling Weak Entity Set Generalization and Specialization Design Constraints Total and Partial Participation Disjoint Constraints Overlapping Constraints Aggregation ER Design Decisions Mapping ERD to Tables Composite Attributes Multivalued Attributes Redundancy As Tables Module 5 : Mapping ERD to Tables Entity Set Table Translation Relationship Table Translation Mapping Key Constraints Map Relationship Set to Table Combine Relationship and Entity Set Weak Entity Sets Mapping Weak Entity Sets Mapping Subclasses Table per Subclass Table per Hierarchy Discriminator Columns Joining Tables Module 6 : UML Modeling What is UML? Structural Modeling? Core Elements Core Relationships Structural Diagrams Classes and Objects Class Diagrams Interfaces Associations Composition Generalization Dependencies Module 7: Normalization What is Normalization? Unnormalized form Moving towards 1NF First Normal Form Moving to 2NF Second Normal Form Third Normal Form Other Normal Forms Benefit of Normalization Relationship Cross Tables Module 8: Database Optimization Optimization Process Use Ranges Denormalize Denormalization Issues Combine Tables Store Derived Data Add Indexes Index Operation Sorting Clustered Indexes
€1.499
Klassikaal
max 12
2 dagen

Design Patterns

Amsterdam wo 17 jun. 2026 en 9 andere data
In the course Design Patterns you will learn how design patterns can be applied to the object oriented design of systems. Design Patterns Intro After an introduction about the role that design patterns play and how they can be used to realize the non-functional requirements of systems, attention is paid to how design patterns are described and cataloged. Architectural Role Also the role of design patterns in the architecture of applications is discussed and the various categories of design patterns that are distinguished. Creational Patterns In the module Creational Patterns the Factory patterns and the Builder, Prototype and Singleton pattern are discussed. You learn out of which classes, relationships, responsibilities and cooperations a typical design pattern solution can consist. Structural Patterns Next in the module the Structural Patterns the Adapter, Composite, Bridge, Decorator, Proxy and Flyweight pattern are discussed. You will learn the consequences of applying the patterns, the benefits and possible disadvantages in terms of time and space considerations and how to decide on the use of a particular pattern. Behavioral Patterns Next in the module Behavioral Patterns the Chain of Responsibility, Interpreter, Iterator, Mediator, State and Strategy patterns are discussed. Architectural Patterns Finally the module Architectural Patterns considers certain patterns that are involved in the architectural structure of software including Operating Systems and Frameworks. This module focuses on the Layer pattern, the Micro Kernel pattern and the Model View Controller (MVC) pattern. Audience Course Design Patterns The course Design Patterns is intended for experienced developers and software architects with knowledge of object oriented programming and systems analysis who want to apply Design Patterns when designing these systems. Prerequisites Course Design Patterns Knowledge of an object-oriented programming language like C++, C#, or Java and experience with object oriented analysis and design with UML is required. Realization Training Design Patterns The concepts are treated according to presentation slides. The theory is illustrated with demos of patterns in C++, C# and Java. There are exercises in design problems where patterns are applied. The course material is in English. The course times are from 9.30 up and to 16.30. Certification Design Patterns Participants receive an official certificate Design Patterns after successful completion of the course. Modules Module 1 : Intro Design Patterns What is a design pattern? Describing design patterns Reuse through design patterns Structure of patterns Classification of patterns Catalog of Design Patterns Creational Patterns Structural Patterns Behavioral Patterns Sample design patterns Selecting Design Patterns Solving problems with design patterns Module 2 : Creational Patterns Factory Patterns Factory Method Pattern Connect parallel class hierarchies Abstract Factory Pattern Concrete Class Isolation Promoting Consistency Builder Pattern Controlling the build process Prototype Dynamic configuration Singleton Pattern Controlled access Module 3 : Structural Patterns Adapter Pattern Pluggable Adapters Composite Pattern Sharing Components Decorator Pattern Lots of little objects FaÇade Pattern Reducing client-subsystem coupling Flyweight Pattern Reducing number of instances Proxy Pattern Copy-on-write Module 4 : Behavioral Patterns Chain of responsibility Command Pattern Interpreter Pattern Iterator Pattern Mediator Pattern Memento Pattern Observer Pattern State Pattern Strategy Pattern Template Pattern Module 5 : Architectural Patterns Architectural patterns versus design patterns Patterns for real-time software Layers Pipes and Filters Blackboard Broker Model-View-Controller Presentation-Abstraction-Control Microkernel Reflection
€1.999
Klassikaal
max 12
3 dagen

Development with Maven

Amsterdam ma 22 jun. 2026 en 9 andere data
In the course Maven Development participants will learn the skills and knowledge needed to use Maven as an automated build and dependency management tool. Maven Intro The course starts with an overview of the problems in project and dependency management, how Maven works and the role of Maven repositories. Explained is how Maven compares to the automatic build tool Ant. Maven Projects Next the directory structure of Maven projects and the standard life cycle are discussed. Maven projects can be created using predefined archetypes that have a certain project structure built in from the start. The role of Maven goals and plugins is also covered. Project Object Model Then the Project Object Model (POM) with pom.xml is treated. The meaning of the main entries therein such as Group, Artifact and Version are discussed and also a more complex structure with multiple pom files and pom inheritance. Archetypes The Maven Archetypes are also part of the program of the course Maven Development. Attention is paid to a number of commonly used archetypes. Also discussed is how you can create archetypes yourself with the Maven Archetype plugin and which are provided with a prototype POM and prototype files. Repositories Furthermore Maven Repositories such as the Maven Central repository, Enterprise Repositories, the Local Developer Repository and Remote Repositories are treated. The order in which Maven searches the repositories is discussed and Plugin Repositories are covered as well. Build Automation Finally attention is paid to the role of Maven in performing tests, to continuous integration and to release management with Bamboo, Team City or Jenkins. Audience Development with Maven Course The course Maven Development is intended for developers who use Maven for dependency management and for the automatic building and deployment of projects. Prerequisites Course Using Maven To participate in the course Maven Development knowledge of and experience with Java and XML is required. Realization Training Using Maven The theory is discussed on the basis of the presentation slides and is interspersed with exercises. Demo projects in Maven are used to clarify the concepts. The course material is in English. The course focuses on Maven version 3. Certification Development with Maven Participants receive an official certificate Development with Maven after successful completion of the course. Modules Module 1 : Maven Intro Java Build Tools Intro Desired Features Ant + Ivy Build.xml Build File with Ivy Ivy Dependency Management Maven Build Lifecycle pom.xml Gradle Results Matrix Tools Comparison Module 2 : Core Concepts What is Maven? Why Maven? Convention over Configuration Maven Directory Structure Project Object Model Maven Project Coordinates POM Structure POM Sections Plugins Archetypes Catalog File Dependencies Module 3 : Build Lifecycle What is Build Lifecycle? Standard Lifecycles Key Lifecycle Phases Build Phases and Goals Clean Lifecycle Default or Built Lifecycle Default Lifecycle Phases Site Generation and Reporting Site Lifecycle Site Website Customizing the Lifecycle Package-specific Lifecycles Module 4 : Profiles Environment variables User-defined properties Filtering Resources Build Profiles What is a Build Profile? Project Configuration with Profiles Profile Activation Explicit Profile Activation Activation via Maven Settings Activation via Environment Variables Activation via Operating System Activation via Files Module 5 : Plugins and Goals What are Maven Plugins? Plugin Types Goals and Plugins Key Plugin Concepts Maven Antrun Plugin Maven Compiler Plugin Exec Maven Plugin Jetty Maven Plugin Eclipse Maven Integration Maven Checkstyle Plugin Findbugs Maven Plugin Maven PMD Plugin Module 6 : Archetypes What is an Archetype? Different Archetypes Archetype Generate Command Maven Archetype Archetype Maven Archetype WebApp Simple J2EE Project Maven Archetype Simple Site Creating Archetypes Maven Archetype Plugin Archetype Descriptor Prototype POM Prototype Files Module 7 : Repositories What is a Maven Repository? Enterprise Repositories Local Repository Central Repository Repositories in Super POM Remote Repository Maven Search Sequence Plugin Repositories Repository Management Deploying to Nexus with Maven Performing a Staged Release Module 8 : Dependency Management What is Dependency Management? Searching Dependencies Transitive Dependencies Dependency Terminology Dependency Scope Optional Dependencies Version Ranges Project Versions Visualizing Dependencies Dependency Conflicts Excluding Transitive Dependencies Module 9 : Build Automation Handling Rapid Changes What is a Snapshot? Snapshot Dependency Build Automation Using Snapshots Release Management The Maven Release Plugin Developer Release Workflow Integration with Source Control Continuous Integration Deployment Automation
€1.499
Klassikaal
max 12
2 dagen

Django Web Development

Amsterdam wo 22 jul. 2026 en 9 andere data
In the course Django Web Development participants learn how to use this Web Application Framework for developing Python Web Applications. Django Architecture The course starts with an overview of the architecture of the Framework, how it can be installed and how the Admin application can be used. MVT Pattern and Model Mapping Next the MVT pattern is treated and how Models are mapped to the database. Also the various Field types and the data access API are discussed. Views, URL's and Templates Next attention is paid to views and URLs and it is shown how regular expressions are used in the mapping to views. Also the use of templates in the construction of views is discussed. Django Forms Then the focus of the course turns to the creation of Forms used to collect input from the user. Attention is also paid to the validation of Forms and the use of the so-called Model Forms derived from Model classes. Object Relational Mapping and performance optimization when accessing the database is discussed as well. Advanced Topics Finally some more advanced topics are on the program such as authentication in Django, working with the REST Services and Unit Testing. By the end of the course the participants will have built a complete Application that includes a REST interface.   Audience Django Web Development Course The Django Web Development course is designed for developers who want to use the Framework for creating Web Applications in Python. Prerequisites Course Django Web Development To participate in this course knowledge of Web Applications and knowledge of and experience with programming in Python is required. Realization Training Django Web Development The theory is treated on the basis of presentation slides. Demos are used to clarify the concepts further. During the course there is ample opportunity to practice. The course material is in English. The course times are from 9.30 up and to 16.30. Certification Course Django Web Development Participants receive an official certificate Django Web Development after successful completion of the course. Modules Module 1 : Django Intro What is Django? Django History Framework Features Python CGI Script MVC Design Pattern Creating Projects Project Settings Project URL’s Running Project Testing Project Admin Application Setup Databases Activate Admin Site Module 2 : Django Models Mapping Models Create Application Create Models Migrations SQL for Models Three Step Migration Practice Data Access API String Representation Fields Creating and Accessing Objects Enabling Admin Interface Customize Admin Form Adding Related Objects Module 3 : Views and URL's View Basics URL Mapping Django MVT Pattern URL Arguments URL Utility Functions Non-Named Group Matching Named Groups View Functions Mapping to Views HTTP Request Object HTTP Response Object redirect Shortcut get_object_or_404 Module 4 : Django Templates The Template System Template Variables render_to_repsonse Shortcut render Shortcut Context Variable Lookup List in Template Template Tags If and For Tag Filters Template Inheritance Child Templates Autoescape Loading Templates Class Based Views Specialized Views Module 5 : Django Forms Form Objects Using Form in View Processing Form Data Display Form using Template Display using Paragraphs Display using Table Validating Forms Customize Form Template Rendering Error Messages Looping over Form Fields Rendering Forms Core Fields Argument ModelForms Model and Form Customize Model Forms Module 6 : Django Security Web Security Essentials Bad Practices Web Security Security Features Cross Site Scripting XSS Protection Cross Site Request Forgery CSRF Protection Clickjacking Protection SQL Injection Protection Cookies and Files Email Header Injection Django Authentication Authenticating Users Permissions and Authorization Authentication in Web Requests Module 7 : Django REST What is REST? REST Services REST Examples Resource URI’s REST challenges Django Solutions Includes Installing DRF Core Components Django Counterparts Building our Demo API Customizing Resources Module 8 : Advanced Topics Sessions Session Support Messages Framework Using Messages Sending Email Emitters Testing Unit Testing ORM advanced Aggregation and annotation Reporting/Data analysis application Database performance profiling Signals to denormalise
€1.999
Klassikaal
max 12
3 dagen

Docker Containers

Amsterdam ma 15 jun. 2026 en 9 andere data
In the course Docker Containers participants learn how to use Docker containers in application development. Docker Intro The course Docker Containers starts with an explanation of how Docker containers work. The participants learn to create and run Docker containers. Unlike virtual machines, Docker uses resource isolation so that several independent containers can run in an operating system instance. The containers can be created, started, and stopped just like processes. Docker Commands The various Docker commands such as run, pull, push, build and search are covered. Attention is also paid to hosting Docker containers, such as hosting in the registry or hosting in web applications Docker Images Next attention is paid to Docker Images, in which the difference between Base and Child images is discussed, among other things. A Docker image is a runtime environment and the image is created with the instructions in a Dockerfile. The content of a Docker file is also explained. Cloud Deployment Cloud Deployment on various cloud platforms such as AWS, Azure and Google App Engine is also on the program of the course Docker Containers. Docker machines are local or remote computers with an IP address on which the Docker service runs. Typically these are also present in cloud environments such as AWS, Amazon Web Services. Multi Container Environments Finally attention is paid to the use of Docker containers in a Microservices Architecture, the use of multiple containers side by side and in a cluster in combination with the Kubernetes cluster orchestration system. Audience Course Docker Containers The course Docker Containers is intended for developers who want to use Docker containers for application development. Prerequisites Course Docker Containers To participate in the course Docker Containers the participants should have experience with the development of applications and related matters. Realization Training Docker Containers The theory is explained on the basis of presentations. The concepts are illustrated with demos. The theory is interspersed with exercises. The course times are from 9.30 to 16.30. Official Certificate Course Docker Containers Participants receive an official certificate Docker Containers after successful completion of the course. Modules Module 1 : Docker Intro What is Docker? Packaging Applications Containers versus Virtual Machines Cloud Deployment Amazon Web Services Docker Hub Installing Docker Running Docker Docker Daemon Docker Hub and Registry Docker Images Docker Client Module 2 : Docker Commands pull Command run Command Container ID's ps Command docker container prune docker rm docker search Hosting in registry Hosting WebApps Publishing Ports Detached Mode Snapshots Module 3 : Docker Images Base Images Child Images Official Images User Images Creating Images onbuild Version Using a Dockerfile FROM Keyword EXPOSE Keyword CMD Keyword docker build Development Workflow Module 4 : Cloud Deployment Docker on AWS Elastic Beanstalk docker push Heroku Google App Engine AWS Console cmd for EB Dockerrun.aws.json Upload and Deploy Configuration Monitoring and Alarms Module 5 : Multi Container Environments Multiple Services Multiple Containers Decoupling Application Tiers Microservice Architecture Scalability Adding Containers Tweaking Base Images Custom Dockerfiles ADD command package.json Preparing Images Module 6 : Docker Network Exposing IP Address Bridge Network Default Network docker network Command network create Command Automatic Service Discovery Docker Compose docker-compose.yml Docker Machine Docker Swarm Kubernetes
€1.399
Klassikaal
max 12
2 dagen

Dojo Toolkit Programming

Amsterdam ma 8 jun. 2026 en 9 andere data
The course Dojo Toolkit Programming provides an overview of the operation and possibilities of the Dojo Toolkit and deals with how dynamic web applications can be created with Dojo. Dojo's Module System In the first place attention is paid to the Dojo Architecture and the Dojo Toolkit libraries, with a prominent place being taken by Dojo's Module System. The participants learn how modules work and how they can be loaded asynchronously via AMD, Asynchronous Module Definition. DOM Interaction and Event Handling Next interaction with the page via DOM and Dynamic HTML is discussed. This includes event handling. Dijit Widgets Dojo GUI interfaces with the Dijit widgets are also on the course program. The different types of widgets such as command and text controls and containers are treated. Classes and Objects Object-oriented programming with Classes and Objects in Dojo is discussed and attention is paid to how Ajax functionality can be implemented in Dojo applications. Routing In line with this URL mapping in Dojo, defining routes as well as back button handling and bookmarking are treated. Dojo and Rest Next the Dojo and Rest module discusses how a Dojo Application can access a Rest Service and how the Dojo store is used for storing and querying data. Dojo Mobile Finally attention is paid to the use of Dojo Mobile for applications for mobile devices. Audience Course Dojo Toolkit Programming The course Dojo Toolkit Programming is intended for Web Developers who want to learn how to use the Dojo Toolkit to develop dynamic web applications. Prerequisites Dojo Toolkit Programming To participate in this course knowledge and experience with JavaScript, HTML, CSS and Web applications is required. Realization Training Dojo Toolkit Programming The theory is discussed on the basis of presentation slides. The concepts are illustrated with demos and the theory is interspersed with exercises. The course times are from 9.30 to 16.30. Official Certificate Dojo Toolkit Programming Participants receive an official Dojo Toolkit Programming certificate after successful completion of the course. Modules Module 1 : Dojo Intro What is Dojo? Benefits of Dojo Features of Dojo JS Foundation Dojo Usage Dojo Architecture Dojo Base and Core Asynchronous Module Definition Defining Modules Loading Modules Configuring Dojo Modules Loading Modules Locating Packages Dojo Build System Module 2 : Dojo DOM Access DOM Manipulation DOM Retrieval DOM Creation DOM Placement DOM Destroy Dojo Query Restricting Queries Advanced Selections NodeList Foreach Connecting to Events Dojo Event Handling On Method Event Delegation Publish and Subscribe Module 3 : Dijit and Forms What is Dijit? Dijit Registry Dijit Attributes Dijit Events Dijit Widget Types Menu Widgets Layout Widgets Tree Widgets CheckBoxes and RadioButtons on Change Events NumberTextBox DateTextBox ValidationTextBox Form Validation Module 4 : Classes and Objects Classes and Objects Encapsulation Prototype Based OOP Adding to Prototype Dojo Object Orientation Named Classes Anonymous Classes Using Mixins Object Sharing Using Statics Single and Multiple Inheritance Call Superclass Methods Constructor Chaining Module 5 : Ajax Interaction Ajax Term Explained Classic Web Application Model Ajax Web Application Model Classic Synchronous Interaction Ajax Asynchronous Interaction XMLHttpRequest Object Methods Sending the Request Listening for Response Ajax in Dojo Dojo Request Request GET and POST JSON Request JSON with Padding Module 6 : Routing URL Modification Bookmarkable Pages dojo/hash module Back Button Handling Single Page App Topic Responses Dojo Router Route Parts Router Properties Router Callback Register Function Router Responses Router Configuration Module 7 : Dojo and REST What is REST? RESTFull Web Services ID and Links Multiple Representations Stateless Communications Content Negotation Simple Root Resource Container Item Pattern Map, Key, Value Pattern Dojo Clients DojoX and Comet Module 8 : Dojo Stores Creating Stores dojo/stores Memory Store query Method Query Engine QueryResults Stateful Modeling Object Data Binding DataGrid Cells and Rows Views Module 9 : Dojo Mobile dojox/mobile Dojo Bootstrap Configuration Dojo Mobile Template Views and Widgets Base Widgets FeedView Settings View Build Profile Minimize Dependencies Layers and Features Building with Node.js
€1.999
Klassikaal
max 12
3 dagen

Drupal Web Development

Amsterdam do 11 jun. 2026 en 9 andere data
In the course Drupal Web Development participants learn to use newest version of the Drupal Content Management System, CMS, to set up a complete web site. Drupal Intro The course starts by installing Drupal and a first site is built and the associated modules are chosen. Next it is discussed how a typical site is built in Drupal and how the Drupal page model works. Drupal Components Participants learn the meaning and use of the various components in Drupal such as fields, views, modules, nodes, blocks and pages. Blocks en Regions The course then continues with the layout with blocks and regions and also default blocks and custom blocks are discussed. The content types in Drupal including PAGES and ARTICLES on which fields of different types can be placed are discussed. Taxonomies Participants also learn what taxonomies are and how you can work with views, themes and input forms. Web Services Finally attention is paid to some advanced topics such as web services with XML-RPC. After completing this course participants can independently build a web site with Drupal. Drupal API To develop a Web Site in Drupal virtually no programming knowledge is required. Developers however can develop even more functional applications with the Drupal API.   Audience Drupal Web Development Course This course targets persons that want to use Drupal for the design of a Web site or Web Application. Prerequisites Course Drupal Web Development No specific knowledge is required to participate in this course. General knowledge of Web applications and experience with computers is desired. Realization Training Drupal Web Development The theory is discussed on the basis of presentation slides. Demo's are used to clarify the treated concepts. In a number of subsequent exercises participants create a Drupal Website with often used functionality. Certification Drupal After successful completion of the course the participants receive an official certificate Drupal Web Development. Modules Module 1 : Drupal Intro What is Drupal? CMS Systems Drupal terminology Content Management Framework Web Application Framework Modules and Themes Nodes and Blocks Drupal Workflow Bootstrap Hooks and Callbacks Installing Drupal Module 2 : Drupal Core Admin Interface Creating and Managing Content Site Building and Configuration User Management Out of the Box Modules Core Required Core Optional-enabled Core Optional-disabled User Contributed Modules Popular Modules Module selection and evaluation Module 3 : Layout and Files Layouts in Drupal Blocks and Regions Default Blocks Custom Blocks Configuring Blocks Enabling Default Blocks Controlling the Front Page File System Download Methods File Module Image Module Module 4 : Fields Module Custom Content Types The PAGE and the ARTICLE Input Filters Field Permissions Adding Fields to Content-Types Text and Numeric Fields Link and Image Fields Field Groups Node Reference Manage Display Settings Module 5 : Taxonomies What is taxonomy? Working with Taxonomy Vocabularies Required Vocabulary Controlled Vocabulary Single and Multiple Terms Adding Terms View Content by Term Storing Taxonomies Module-Based Vocabularies Module 6 : Drupal VIEWS Overview of VIEWS VIEW Types Default Views Overridden Views Normal Views Displays Basic Settings Display Types Basic Settings Fields vs Node Module 7 : Themes Theme System Architecture Theme Templates The .info file Theme Engine Hooks Creating a Theme Theme Inheritance Modifying Base Themes Custom Stylesheets Overriding Theme Behavior Module 8 : Forms Forms with Webforms module The Form API Form Processing Validation Form Submission Redirection Creating Basic Forms Custom Module Basics Enabling Custom Form Module Form API Properties Module 9 : Advanced Topics Rules with the Rules module Common Functions Relationships XML-RPC What is XML-RPC? XML-RPC Client XML-RPC Server REST Server JSON and REST Filters and Arguments
€1.499
Klassikaal
max 12
2 dagen