Programming XI Courses Online

Live Instructor Led Online Training Programming XI courses is delivered using an interactive remote desktop! .

During the course each participant will be able to perform Programming XI exercises on their remote desktop provided by Qwikcourse.


How do I start learning Programming XI?


Select among the courses listed in the category that really interests you.

If you are interested in learning the course under this category, click the "Book" button and purchase the course. Select your preferred schedule at least 5 days ahead. You will receive an email confirmation and we will communicate with trainer of your selected course.

Programming XI Training


Fundamentals of PBASIC Programming

About

This course is about PBASIC programming using the Parallax BasicStamp family of microcontrollers.

Content

  • Introduction
  • History
  • Hardware and Development Kits
  • PBASIC Editor

Computer Arithmetic

  • Data Types
  • Variables and Constants
  • Basic Arithmetic

Branching and Control Flow

  • Labels and GOTO
  • Branches
  • Loops
  • Subroutines

Port I/O

  • Input and Output
  • Serial Communications
  • PULSIN and PULSOUT
  • RCTIME

Advanced Arithmetic

  • Trigonometry Functions
  • Other Functions

7 hours

$1,990

Explore Programming Mac OS X with Cocoa for Beginners

About

This course aims to provide beginners with an introduction to the programming of Mac OS X Apps using Cocoa, and XCode, the free developer tools provided by Apple, Inc. Examples of Mac apps are: iTunes, Safari, Mail, iCal, Address Book, Microsoft Word, Microsoft Excel, etc. Using Objective-C, Cocoa and XCode as taught in This course will start your education in how to develop Mac apps. Many of the skills that you learn in This course can be used to build apps for iOS but there are some differences between Mac OS X apps and iOS apps. This course focuses on Mac OS X apps. Some knowledge of another programming language, preferably Objective-C. The following link is a link to a wikibook that covers Objective C Programming. Apple has a Mac App Store where it can sell your Mac apps for you and they will pay you 70% of the proceeds. The Mac App Store is available for users of Mac OS X, 10.6 and later by choosing from the Apple menu "App Store...". In general, this text is written to be followed in order from start to finish except that if you have experience in C, C++, Java or Python, you are encouraged to look at the relevant section of the Appendix to orient you to developing for Mac OS X and Cocoa.

Content

  • Contents
  • What Is Cocoa?
  • Building a Simple Mac App
  • Building Blocks of Mac OS X Apps
  • Building More Complex Mac Apps
  • More About the Cocoa Framework
  • Model-View-Controller (MVC) Design Pattern
  • More Cocoa Classes
  • Other Application Types
  • Managing Source Code
  • The Wikidraw App

7 hours

$1,990

Learn Visual Basic .NET

About

Visual Basic .NET is a multi-paradigm, high-level programming language,from Microsoft that is suitable for most development needs. The language is designed with Rapid Application Development in mind, providing several tools to shorten development time. This course introduces Visual Basic .NET language fundamentals and covers a variety of the base class libraries (BCL) provided by the .NET Framework. GDI+ is a way to draw simple graphics and strings on a Form. 


14 hours

$3,980

Learn Annotations of The Art of Computer Programming Volume 1

About

The purpose of these annotations is to encourage and help people to read one of the most influential scientific books of the 20th century. The annotations in This course apply to Volume 1 of The Art of Computer Programming, by Don Knuth. Please keep annotations succinct, clear, helpful, and professional. Annotations are marked with the edition number, page number and section number. Related equations, theorems, or otherwise numbered items should also be marked. Use bold for the numbering, for example Annotations must be presented in the correct order. Defer to the third edition of the course in case of conflict. TAOCP is copyrighted. Any quotes must respect the rules of copyright and/or specific instructions from the publisher.

7 hours

$1,990

Learn Computer Programming Principles

About

Computer Programming is the process of writing, testing, troubleshooting, debugging and maintaining of a computer program. Good programming practices mix art, craft and engineering discipline. This course will teach you the basic principles of computer programming and good programming practices. What This course will not do is teach you to use a specific programming language. This course may also be useful as part of a course on computer theory, computer engineering, or software engineering, along side learning a programming language, or as part of an advanced programming course.

7 hours

$1,990

Basics of GNU Data Language

About

GNU Data Language (GDL) is a free software (GDL - GNU Data Language). A free IDL (Interactive Data Language) compatible incremental compiler (i. e. runs IDL programs). IDL is a registered trademark of ITT Visual Information Solutions. Features Full syntax compatibility with IDL up to version 7.1 (for 8.0 and later see below). ALL IDL language elements up to IDL version 7.1 are supported, including: Supported IDL 8.0 language elements: The file input output system is fully implemented (Exception: For formatted I/O the C() sub-codes are not supported yet) netCDF files are fully supported. HDF files are partially supported.


7 hours

$1,990

Know Q3Map2

About

Q3Map2 has now been integrated with the GtkRadiant Project. Windows, Mac and Linux binaries for both 32-bit and 64-bit systems can be download from the project page. The Q3Map2 source code is now available through the GtkRadiant GitHub Repository. Official Support Forum @Splashdamage Current stable version is 2.5.17 Q3Map2 is a BSP compiler for games based on the id Tech 3 engine. It compiles .map files, which are editable with an editor, into .bsp files, which are binary files for the game and are not editable. It currently supports the following platforms: Q3Map2 was designed to replace the Q3Map.exe that comes with QERadiant, GtkRadiant and GMAX Tempest. However, there are significant enhancements that require a little twiddling to use, such as faster lighting and enhanced surface production. Fun Facts: Q3Map2 is a command-line utility. In general, users make use of Q3Map2 in one of three ways:

7 hours

$1,990

Learn Scribunto: An Introduction

About

Scribunto: An Introduction is a course for people who want to learn how to program using Scribunto. Scribunto enables users to embed the Lua programming language into wikis that use MediaWiki, the software that powers Wikipedia. This course covers how to get started, basic programming techniques, and how to use some of the Lua libraries that are unique to Scribunto. It is aimed at beginners to programming, particularly those who have some familiarity with the MediaWiki software, but may also be useful to experienced programmers who are new to Scribunto.

7 hours

$1,990

Explore BrainJam Tricky Mathematical Brain Training Game

About

BrainJam Tricky Mathematical Brain Training Game

BrainJam's challenging and interactive Math Problems helps you to sharpen and train your brain. BrainJam offers different kind of Math puzzles for everyone which tests your accuracy, aptitude and quick-thinking skills. Start exercising your brain now! Don't let your brain jam!

Screenshots


7 hours

$1,990

Work around SMDL

About

Submodular Batch Selection for Training Deep Neural Networks

IJCAI 2019 Mini-batch gradient descent based methods are the de facto algorithms for training neural network architectures today. We introduce a mini-batch selection strategy based on submodular function maximization. Our novel submodular formulation captures the informativeness of each sample and diversity of the whole subset. We design an efficient, greedy algorithm which can give high-quality solutions to this NP-hard combinatorial optimization problem. Our extensive experiments on standard datasets show that the deep models trained using the proposed batch selection strategy provide better generalization than Stochastic Gradient Descent as well as a popular baseline sampling strategy across different learning rates, batch sizes, and distance metrics.


7 hours

$1,990

Know Msgraph Training Microsoftflow

About

Microsoft Graph Training Module - Create a Microsoft Graph JSON Batch Custom Connector for Microsoft Flow & Azure Logic Apps

This module will introduce you to working with the Microsoft Graph JSON Batching REST API to access data in Office 365. You will learn how to create and configure a custom connector for Flow, access the the Microsoft graph JSON Batch API, and use the custom connector in a Flow to create a Microsoft Team.

Lab - Create a Microsoft Graph JSON Batch Custom Connector for Microsoft Flow & Azure Logic Apps

In this lab you will leverage the Microsoft Graph JSON Batching REST API to create a Custom Connector and Flow application.

Contributors

Version history


7 hours

$1,990

Explore GhostContactBook

About

Android Essential Training

GhostContactBook App

GhostContactBook is android application we will develop along with our training session. We will start from stretch with blank app and cover following milestones to take it to the Play Store eventually.

  • Hello World App (App Structure)
  • Understanding Activity and its UI builder. Navigating to other Activity.
  • Putting Recycler View & showing local data to RecyclerView
  • Developing Network Layer with Retrofit2
  • Fetching data from Rest API
  • Saving data to local database using GreenDAO ORM
  • Showing live data to our RecylerView
  • Getting ready to publish
  • Publishing on Play Store
  • Party!! (Recap and Wrap up)

7 hours

$1,990

Discover Master List

About

Master list of PhysiCell Training Modules

A list of modules in development for PhysiCell training Add a DONE after each once created

  1. What you need
  2. What is PhysiCell?
    1. Complex systems biology
    2. PhysiCell : microenvironment + cells
    3. Chemical microenvironment (via BioFVM)
      1. Reaction-diffusion
      2. cell sources / sinks
    4. PhysiCell agents
      1. State
      2. Phenotype
      3. Custom data
      4. Functions
    5. Training overview
  3. Introduction to agent-based modeling (optional / general)
    1. What is an agent?
    2. Off lattice vs on lattice
    3. Cell states
  4. Introduction to diffusion in biology (optional / general)
    1. Diffusion, decay, and length scales
    2. Neumann Conditions
    3. Dirichlet conditions
  5. PhysiCell

7 hours

$1,990

Basics of RT Programming

About

RT_programming

A tool for generating a range of styles of appropriate resistance training programs for strength. Edit 1RM, monthly volume, and set flags to the program you would like to have generated. Existing constants other than 1RM and volume are based on hypothetically correct values for squat programming described in the Joe Rogan Experience ep. 1399


7 hours

$1,990

Explore Hyper Manager

About

hyper_manager

This UI tool is meant to assist with hyperparameter search when training neural networks. It invokes an external process to do the training, expecting that process to checkpoint its work and eventually exit. Different hyperparameters are tracked based on the command-line options to the training program required to set them up. The rate of training progress is evaluated based on Tensorboard log files emitted by the external process, and at each interval a hyperparameter set is randomly selected for additional training, weighted based on configurable parameters such as convergence rate or total training time. Hyperparameter sets may be selected for plotting of the loss curves, or interactively inhibited from additional training. Additional hyperparameters may be manually added at any time.

Dependencies

In addition to Tensorflow, this tool depends on PySide2 and matplotlib to function:

  • pip3 install matplotlib
  • pip3 install PySide2 If you have Tensorflow in a virtual env, all three packages must be in the same env, and the tool must be run from that environment.

    Instructions to use

    To begin, invoke File/New Session. You will be prompted for some properties of the session:

  • "Session name" is the name of the new session to create. A new folder will be created at the specified path to contain the session settings and training progress.
  • "Session path" is an existing folder to put the new session in.
  • "Training executable" is the tool to invoke to perform a training iteration.
  • "Training options" is a space-separated list of command-line options to be provided to the tool, common to all hyperparameters. This might be invariant things such as a dataset file location, configuration of a common metric to use, and training duration. NOTE: it is important that the training process exit on its own after a period of time (e.g. five minutes or so); probably, these options should configure that interval.
  • "Checkpoint subdir" is the location of the checkpoints (e.g. saved weights) emitted by the training process, relative to the working directory of the process. Every distinct hyperparameter set is invoked in its own subdirectory of the session folder, and this directory is expected to be found under that. When resuming training, the manager will look for json files in this folder, identify the most recent one lexicographically, and pass it to the training process with a '--resume-from' argument.
  • "Logs subdir" is the location of log data emitted by the training process, relative to the working directory of the process. Error stats and plots will be based on scraping the Tensorboard logs found here. If there is a single metric in the log, that will be used as the 'error'; with no metrics, the loss will be used. Multiple metrics are not currently supported. Once the session is created, sets of hyperparameters to test can be added via the Set menu, and the training session can be started from the Run menu. The TTZ column can be used to estimate which hyperparam sets will reach lower error values sooner. It is based on a linear fit to the error curve, and the time for that projected line to intersect zero ("Time To Zero"). Obviously, no training process follows a linear progression indefinitely, so this should not actually be treated as a meaningful unit of time, only as a relative ranking between sets taking into account current error and error rate. This column is also the default metric used to weight random selection when picking a set to train for a new interval. Individual hyperparam sets, or groups of sets, may be enabled and disabled manually by selecting them and right-clicking, or using the Sets menu. Additionally, a threshold on the variance can be configured to automatically disable sets if the validation error becomes substantially worse than the training error.

7 hours

$1,990

Learn Data Training For Machine Learning

About

This course was developed using the concept of Machine Learning and the programming language Python 3. Machine learning is the study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. The main focus of this course is to monitor how increasing the amount of data training for a machine learning algorithm can recognize handwritten digits that increases the accuracy of the algorithm.


7 hours

$1,990

Discover Training And Placement Website

About

Training-and-Placement-Website

Training and Placement Cell is a total management and informative system, which provides the up-to date information of all the students in a particular college. TPC helps the colleges to overcome the difficulty in keeping records of hundreds and thousands of students and searching for a student eligible for recruitment criteria from the whole thing. It helps in effective and timely utilization of the hardware and the software resources. The home page contain various links such as links to login, various services like Events happened, achievements and recruiter details etc.,. The administrator will create the users and the users will use the accounts created by administrator. When the user enteres into his respective page he can update his details, and the details are to be approved by the administrator. All the users have some common services like changing password, updating details, searching for details, checking the details, mailing to administrator, and reading the material uploaded by admin if the user is a student. Administrator has the services to add events and achievements and he can reply to the mails sent by users. He can upload materials, search for student details, and he has the right to approve the students. This package is developed in windows platform. The programming language used is JSP with three tier architecture. Oracle 8i is used as backend database for the details to be stored.


7 hours

$1,990

Explore Tuxcap

About

TuxCap

TuxCap is a program for buffering a series of photos and capturing the time before, during and after some trigger event using a raspberry pi and a USB webcam. The captures can be stored as a folder of jpegs or as an mp4 video, depending on your size limitations and quality requirements. The command line interface is basic, and accepts the following commands:

  • h, help, ?: Show Help
  • q: quit
  • show: Show number of images in buffer
  • cap: save current buffer to disk when the time comes This was developed at the request of the University of Cape Town for a penguin conservancy project, in order to provide a large amount of photo data on penguins. With some adaptation it could really be useful for any situation where you have a trigger line and the need to capture buffered still images.

    Dependencies and Installation

    TuxCap is written for Python 3. Requirements are updated and can be found in the requirements.txt file. It depends on OpenCV for camera handling and Numpy because OpenCV depends on it. If you intend to create video captures, ffmpeg should be installed. You can install all dependencies on x86-64 debian with: pip3 install -r requirements.txt sudo apt install ffmpeg On the Raspbian, dependencies are not all available through pip. Instead, run the following to install the relevant packages: pip3 install opencv-python sudo apt install ffmpeg libatlas3-base libcblas3 libjasper1 libqt4-test libgstreamer1.0-0 libqt4-dev-bin libilmbase12 libopenexr-dev rpi.gpio You may need to add the user running the program to the video group, using usermod -aG video


7 hours

$1,990

Know Aldohonen

About

aldohonen

This is a simple tool to visualize a Kohonen Network with color training. Colors represent neurons weight. So, when training with an constant input color set, network learn from this pattern, then self organize to represent this pattern. The more iterations executed, the more the network will look like the input.

Authors

Luiz Eduardo Pizzinatto & Bruno Martins Crocomo

Execution

python Main.py

Examples

Below are shown 4 screenshots from a simple training process. Starting with a random image, every training step (activate and backward) turn the network more organized, culminating in organized colors (i.e. organized neurons).

Infos

  • pybrain works only with numpy 1.11.0.
  • This is a single thread approach.

7 hours

$1,990

Learn Ccpbiosimbase

About

= The CCPBioSim base container

This container forms the basis of our cloud based training platform. It is designed to be very minimal such that it only provides basic system utilities and tools along with the JupyterHub server for serving multiuser Jupyter notebooks. This particular container does not contain any Jupyter based training material, but simply sets up and configures the JupyterHub server and a number of basic system utilities that will enable this container to function as a reliable base container for specific workshop courses.


7 hours

$1,990

Know Managing Spam On A Site

About

Managing Spam On A Site

Description

Learn why spam is a problem for all WordPress sites, why you should control it and how and learn tips to manage it.

Objectives

  • Students will understand the problems that spam comments may have on a site as well acquire the skills in order to change site settings to control spam.

    Prerequisite Skills

  • Understanding the WordPress Admin panel and how to navigate the admin menus.
  • Understanding of installing and activating plug-ins on a self-hosted WordPress website.

    Readiness Questions

  • Do students have the skills to navigate through the admin panels and change basic settings?
  • Do students have the skills to install and activate a plugin?

    Target Audience

    Who is this lesson intended for? What interests/skills would they bring? Choose all that apply.

  • [x] Users
  • [ ] Designers
  • [ ] Developers
  • [ ] Speakers
  • [ ] All

    Experience Level


7 hours

$1,990

Know ZMOD

About

Zementis Modeler (ZMOD)

Zementis modeler is an open source machine learning and artificial intelligence platform for Data Scientist to solve business problems faster and quicker, build prototypes and convert them to actual project. The modeler helps from data preparation to model building and deployment, the tool supports large variety of algorithms that can be run without a single line of code. The web based tool has various components which help Data Scientist to perfrom several model building tasks and provides deployment ready PMML files which can be hosted as a REST services. Zementis Modeler allows its user to cover wide variety of algorithms and Deep Neural Network architectures, with minimal or No code enviornment. It is also one of the few deep-learning platforms to support the Predictive Model Markup Languaue (PMML) format, PMML allows for different statistical and data mining tools to speak the same language. The feature offerings of Zementis Modeler are:

  • Zementis AutoML : Automatically train Machine learning models on data supports huge space of algorithms and hyper parameters tuning.
  • Zementis Model Editor : Create Deep Neural Network models using drag and drop functionality, which supports wide variety of model layers, once model architecture is ready, train your model. Zementis Modeler Editor also comes with pre-trained architcture templates that helps in quick model building and training.
  • Jupyter Notebook : Zementis Modeler comes with integrated Jupyter Notebook (For R and Python).
  • Tensorboard : Zementis Modeler provides Tensorboard dashboard to show the progress of models.
  • Code Execution : Zementis Modeler provides support of executing Python script files for more advance requirements.
  • REST API Support : Zementis Modeler can be used using REST calls and can be used as a deployment tool. Zementis Modeler comes to you with the complete source code in Python, .Net, Angular, docker files and extended HTML documentation on how to use guidelines, and a growing number of video, blogs and tutorials that help you familiarize yourself with the way Zementis Modeler supports a Data Scientist on becoming more productive.

7 hours

$1,990

Work around Anatomy Of A Theme

About

Anatomy Of A Theme

Description

In this lesson, you'll learn about the different files that make up a theme and how they work together to display your WordPress website.

Objectives

After completing this lesson, participants will be able to:

  • Recognize that many files are needed to make a theme.
  • Identify the basic blocks are used in a WordPress theme.
  • Identify the files required to make a WordPress theme.

    Target Audience

    Who is this lesson intended for? What interests/skills would they bring? Choose all that apply.

  • [ ] Users
  • [x] Designers
  • [ ] Developers
  • [ ] Speakers
  • [ ] All

    Experience Level


7 hours

$1,990

Discover AssignPointsToExistingClusters

About

AssignPointsToExistingClusters are algorithms for assigning points in one dataset to clusters in another dataset. Ideally, if we have two datasets that represent the same objects in the real world, there would be an unambiguous correspondence between the two datasets. Though, this is not usually the case when working with real-world data. Hence, this repository exists. Finding correct correspondences between datasets is particularly important when training and testing supervised machine learning models. These algorithms have been specifically developed for finding matches between in situ data and clusters in remotely sensed point clouds (such as from lidar and Structure from Motion), though the ideas will generalize to other contexts in machine learning in which the goal is to match points in one dataset to clusters in another dataset.


7 hours

$1,990

Explore Ufrgs Intel Modern Code

About

ufrgs-intel-modern-code

Intel Modern Code is an initiative to spread knowledge on how to design and optimize software through the use of parallelism, aiming to exploit the full potential of computers and supercomputers. This community is made up of experts who provide libraries, support and training in modern code techniques. The GPPD (Parallel and Distributed Processing Group), the Institute of Informatics at UFRGS, joined the modern source community as an Intel Partner Modern Code (MCP) in August 2016 to offer courses and training.


7 hours

$1,990

Work around Trainingdaytwo

About

Terraform Day Two (102)

Overview - Creating Terraform modules.

A Terraform module is a grouping of variables, resources, and outputs that can be reused. It reduces code repetition, and means that the module can be maintained externally to the template using it. And a module is just a Terraform template itself!

Training Goals for day two

  • Understand how to create a module
  • How to use a module from GitHub
  • How to use a versioned module
  • Restrictions of modules: We will be using the same user roles as trainingdayone had so all terraform commands should be run like this, to use the correct account and user. aws-vault exec terraformrole -- terraform init aws-vault exec terraformrole -- terraform apply
    1. Create a module that creates an ec2 launch template, autoscaling group, and load balancer
    2. Create a template that uses the module to create a Drupal website.
    3. Using a Makefile to simplify commands
    4. Create an S3 bucket in a particular region

7 hours

$1,990

Learn What Is Open Source

About

What is Open Source?

Description

In this lesson, you will learn the meaning of the term Open Source when referring to software, what the GPL software license provides, why WordPress is an open-source project and how this is important for both the users of WordPress and the contributors to WordPress.

Objectives

After completing this lesson, students will be able to:

  • Describe and compare the concepts of open-source software, free software, and proprietary software.
  • Define the purpose of the GPL license.
  • Explain the benefits of open-source software for WordPress users.
  • Identify the ways that individuals and organizations can contribute to the WordPress project.

    Target Audience

    Who is this lesson intended for? What interests/skills would they bring? Choose all that apply.

  • [ ] Users
  • [ ] Designers
  • [X] Developers
  • [ ] Speakers
  • [ ] All

    Experience Level


7 hours

$1,990


Is learning Programming XI hard?


In the field of Programming XI learning from a live instructor-led and hand-on training courses would make a big difference as compared with watching a video learning materials. Participants must maintain focus and interact with the trainer for questions and concerns. In Qwikcourse, trainers and participants uses DaDesktop , a cloud desktop environment designed for instructors and students who wish to carry out interactive, hands-on training from distant physical locations.


Is Programming XI a good field?


For now, there are tremendous work opportunities for various IT fields. Most of the courses in Programming XI is a great source of IT learning with hands-on training and experience which could be a great contribution to your portfolio.



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