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Machine Learning Courses in Dubai

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Discover a diverse range of Machine Learning courses in Dubai tailored to meet your educational needs. Explore accredited programs, expert instructors, and flexible learning options to excel in your chosen field. Enroll today and embark on a transformative educational journey.

1 to 8 of 8 Courses
Simpliv Llc

By:   Simpliv Llc

  • Location :
    Dubai
  • Fees :
  • Duration :
  • Schedule :
  • Segment :
    IT Training
  • Subject :
    Machine Learning

Course Details

ABOUT THE COURSE:

Learn to use Python, the ideal programming language for Machine Learning, with this comprehensive course from Simpliv. Gain expertise in core areas of Python and Machine Learning, such as algorithms, model evaluation, supervised vs. unsupervised learning, reinforcement learning, neural networks, k-nearest Neighbor Classifier, Naive Bayes Classifier, and lots more. Become a complete Machine Learning and Python pro. Our experts will show you how to use your knowledge of Python to learn to use it for Machine Learning. All you need is basic knowledge of Python. Our course will take it up from there and make you an expert.

Who is the target audience?

 Programmers, Developers, Technical Leads, Architects, Freshers, Data Scientists, Data Analysts, Business Intelligence Managers.

Basic knowledge:

 There are no hard pre-requisites. However, a basic understanding of Computer Programming terminologies is beneficial.

Curriculum

Python Introduction

  • Introduction to Python   
  • Core programming concepts   
  • Objects in Python   
  • Visualizations in Python  
  • Packages in Python   
  • Matrix operations  
  • Data frames   

Machine Learning

  • Data Pre-processing   
  • Regression   
  • Classification   
  • Clustering   
  • Association Rule   
  • Natural Language Processing 

Price:  Ã¢â€šÂ¹ 16665    ( Enroll Today and Get Flat 40% OFF )

New Batch starts from 7th Jan 2019 Days: Mon-Fri (10 Days) 07:00 PM - 10:00 PM (IST)

Simpliv Llc

By:   Simpliv Llc

  • Location :
    Dubai
  • Fees :
  • Duration :
  • Schedule :
  • Segment :
    IT Training
  • Subject :
    Machine Learning

Course Details

If you want to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course is for you. The Complete iOS Machine Learning Masterclass™ is the only course that you need for machine learning on iOS. Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants like Google and IBM taking the lead. In this course, you’ll use the most cutting-edge iOS Machine Learning technology stacks to add a layer of intelligence and polish to your mobile apps. We’re approaching a new era where only apps and games that are considered “smart” will survive. (Remember how Blockbuster went bankrupt when Netflix became a giant?) Jump the curve and adopt this innovative approach; the Complete iOS Machine Learning Masterclass™ will introduce Machine Learning in a way that’s both fun and engaging.

In this course, you will:

  • Master the 3 fundamental branches of applied Machine Learning: Image & Video Processing, Text Analysis, and Speech & Language Recognition
  • Develop an intuitive sense for using Machine Learning in your iOS apps
  • Create 7 projects from scratch in practical code-along tutorials
  • Find pre-trained ML models and make them ready to use in your iOS apps
  • Create your own custom models
  • Add Image Recognition capability to your apps
  • Integrate Live Video Camera Stream Object Recognition to your apps
  • Add Siri Voice speaking feature to your apps
  • Dive deep into key frameworks such as coreML, Vision, CoreGraphics, and GamePlayKit.
  • Use Python, Keras, Caffee, Tensorflow, sci-kit learn, libsvm, Anaconda, and Spyder–even if you have zero experience
  • Get FREE unlimited hosting for one year
  • And more!

This course is also full of practical use cases and real-world challenges that allow you to practice what you’re learning. Are you tired of courses based on boring, over-used examples? Yes? Well then, you’re in a treat. We’ll tackle 5 real-world projects in this course so you can master topics such as image recognition, object recognition, and modifying existing trained ML models. You’ll also create an app that classifies flowers and another fun project inspired by Silicon Valley™ Jian Yang’s masterpiece: a Not-Hot Dog classifier app! 

Why Machine Learning on iOS

One of the hottest growing fields in technology today, Machine Learning is an excellent skill to boost your your career prospects and expand your professional tool kit. Many of Silicon Valley’s hottest companies are working to make Machine Learning an essential part of our daily lives. Self-driving cars are just around the corner with millions of miles of successful training. IBM’s Watson can diagnose patients more effectively than highly-trained physicians. AlphaGo, Google DeepMind’s computer, can beat the world master of the game Go, a game where it was thought only human intuition could excel.

In 2017, Apple has made Machine Learning available in iOS 11 so that anyone can build smart apps and games for iPhones, iPads, Apple Watches and Apple TVs. Nowadays, apps and games that do not have an ML layer will not be appealing to users. Whether you wish to change careers or create a second stream of income, Machine Learning is a highly lucrative skill that can give you an amazing sense of gratification when you can apply it to your mobile apps and games.

Why This Course Is Different

Machine Learning is very broad and complex; to navigate this maze, you need a clear and global vision of the field. Too many tutorials just bombard you with the theory, math, and coding. In this course, each section focuses on distinct use cases and real projects so that your learning experience is best structured for mastery.

This course brings my teaching experience and technical know-how to you. I’ve taught programming for over 10 years, and I’m also a veteran iOS developer with hands-on experience making top-ranked apps. For each project, we will write up the code line by line to create it from scratch. This way you can follow along and understand exactly what each line means and how to code comes together. Once you go through the hands-on coding exercises, you will see for yourself how much of a game-changing experience this course is.

As an educator, I also want you to succeed. I’ve put together a team of professionals to help you master the material. Whenever you ask a question, you will get a response from my team within 48 hours. No matter how complex your question, we will be there–because we feel a personal responsibility in being fully committed to our students.

By the end of the course, you will confidently understand the tools and techniques of Machine Learning for iOS on an instinctive level.

Don’t be the one to get left behind. Get started today and join millions of people taking part in the Machine Learning revolution.

topics: ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection 

Who is the target audience?

  • People with a basic foundation in iOS programming who would like to discover Machine Learning, a branch of Artificial Intelligence
  • People who want to pursue a career combining app development and Machine Learning to become a hybrid iOS developer and ML expert
  • Developers who would like to apply their Machine Learning skills by creating practical mobile apps
  • Entrepreneurs who want to leverage the exponential technology of Machine Learning to create added value to their business could also take this course. However, this course does assume that you are familiar with basic programming concepts such as object oriented programming, variables, methods, classes, and conditional statements

BASIC KNOWLEDGE

  • Basic understanding of programming
  • Have access to a MAC computer or MACinCloud website

WHAT YOU WILL LEARN

  • Build smart iOS 11 & Swift 4 apps using Machine Learning
  • Use trained ML models in your apps
  • Convert ML models to iOS ready models
  • Create your own ML models
  • Apply Object Prediction on pictures, videos, speech and text
  • Discover when and how to apply a smart sense to your apps
Simpliv Llc

By:   Simpliv Llc

  • Location :
    Dubai
  • Fees :
  • Duration :
  • Schedule :
  • Segment :
    IT Training
  • Subject :
    Machine Learning

Course Details

Image Processing Applications on Raspberry Pi is a beginner course on the newly launched Raspberry Pi 3 and is fully compatible with Raspberry Pi 2 and Raspberry Pi Zero.

The course is ideal for those who are new to the Raspberry Pi and want to explore more about it.

You will learn the components of Raspberry Pi, connecting components to Raspberry Pi, installation of NOOBS operating system, basic Linux commands, Python programming and building Image Processing applications on Raspberry Pi.

This course will take beginners without any coding skills to a level where they can write their own programs.

Basics of Python programming language are well covered in the course.

Building Image Processing applications are taught in the simplest manner which is easy to understand.

Users can quickly learn hardware assembly and coding in Python programming for building Image Processing applications. By the end of this course, users will have enough knowledge about Raspberry Pi, its components, basic Python programming, and execution of Image Processing applications in the real time scenario.

The course is taught by an expert team of Electronics and Computer Science engineers, having PhD and Postdoctoral research experience in Image Processing. 

Anyone can take this course. No engineering knowledge is expected. Tutor has explained all required engineering concepts in the simplest manner.

The course will enable you to independently build Image Processing applications using Raspberry Pi.

This course is the easiest way to learn and become familiar with the Raspberry Pi platform.

By the end of this course, users will build Image Processing applications which includes scaling and flipping images, varying brightness of images, perform bit-wise operations on images, blurring and sharpening images, thresholding, erosion and dilation, edge detection, image segmentation. User will also be able to build real-world Image Processing applications which includes real-time human face eyes nose detection, detecting cars in video, real-time object detection, human face recognition and many more. 

The course provides complete code for all Image Processing applications which are compatible on Raspberry Pi 3/2/Zero.

Who is the target audience?

  • Anyone who wants to explore Raspberry Pi and interested in building Image Processing applications

BASIC KNOWLEDGE

  • Only High School Maths
  • No prior programming knowledge is expected
  • All the code files and images used in this course will be provided
  • Hardware needed: Raspberry Pi 3/2/Zero, Monitor, Mouse, Keyboard, HDMI-VGA connector, USB flash drive (minimum storage capacity 2 GB), Micro SD card (minimum storage capacity 8 GB), Micro SD card reader, Power adapter (2 Amp, Micro-USB charger is preferred), USB Webcam (minimum 5 Megapixel resolution)

WHAT YOU WILL LEARN

  • What is Raspberry Pi? and what are its components?
  • Understand peripherals that need to be connected to Raspberry Pi
  • Wire up your Raspberry Pi to create a fully functional computer
  • Easily learn preparing SD Card to load Operating System for Raspberry Pi
  • Install packages needed to build Image Processing applications
  • Learn basic programming aspects of Python
  • Create simple Image Processing applications using Python and OpenCV
  • Build real-world Image Processing applications on Raspberry Pi
Simpliv Llc

By:   Simpliv Llc

  • Location :
    Dubai
  • Fees :
  • Duration :
  • Schedule :
  • Segment :
    IT Training
  • Subject :
    Machine Learning

Course Details

Prerequisites: No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided.

Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce. 

This course is a down-to-earth, shy but confident take on machine learning techniques that you can put to work today

Let’s parse that.

The course is down-to-earth: it makes everything as simple as possible - but not simpler

The course is shy but confident: It is authoritative, drawn from decades of practical experience -but shies away from needlessly complicating stuff.

You can put ML to work today: If Machine Learning is a car, this car will have you driving today. It won't tell you what the carburetor is.

The course is very visual: most of the techniques are explained with the help of animations to help you understand better.

This course is practical as well: There are hundreds of lines of source code with comments that can be used directly to implement natural language processing and machine learning for text summarization, text classification in Python.

The course is also quirky. The examples are irreverent. Lots of little touches: repetition, zooming out so we remember the big picture, active learning with plenty of quizzes. There’s also a peppy soundtrack, and art - all shown by studies to improve cognition and recall.

What's Covered:

Machine Learning: 

Supervised/Unsupervised learning, Classification, Clustering, Association Detection, Anomaly Detection, Dimensionality Reduction, Regression.

Naive Bayes, K-nearest neighbours, Support Vector Machines, Artificial Neural Networks, K-means, Hierarchical clustering, Principal Components Analysis, Linear regression, Logistics regression, Random variables, Bayes theorem, Bias-variance tradeoff

Natural Language Processing with Python: 

Corpora, stopwords, sentence and word parsing, auto-summarization, sentiment analysis (as a special case of classification), TF-IDF, Document Distance, Text Summarization, Text classification with Naive Bayes and K-Nearest Neighbours and Clustering with K-Means

Sentiment Analysis: 

Why it's useful, Approaches to solving - Rule-Based, ML-Based, Training, Feature Extraction, Sentiment Lexicons, Regular Expressions, Twitter API, Sentiment Analysis of Tweets with Python

Mitigating Overfitting with Ensemble Learning:

Decision trees and decision tree learning, Overfitting in decision trees, Techniques to mitigate overfitting (cross-validation, regularization), Ensemble learning and Random forests

Recommendations: Content-based filtering, Collaborative filtering and Association Rules learning

Get started with Deep learning: Apply Multi-layer perceptrons to the MNIST Digit recognition problem

A Note on Python: The code-alongs in this class all use Python 2.7. Source code (with copious amounts of comments) is attached as a resource with all the code-alongs. The source code has been provided for both Python 2 and Python 3 wherever possible.

Who is the target audience?

  • Yep! Analytics professionals, modelers, big data professionals who haven't had exposure to machine learning
  • Yep! Engineers who want to understand or learn machine learning and apply it to problems they are solving
  • Yep! Product managers who want to have intelligent conversations with data scientists and engineers about machine learning
  • Yep! Tech executives and investors who are interested in big data, machine learning or natural language processing
  • Yep! MBA graduates or business professionals who are looking to move to a heavily quantitative role

BASIC KNOWLEDGE

  • No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided.

WHAT YOU WILL LEARN

  • Identify situations that call for the use of Machine Learning
  • Understand which type of Machine learning problem you are solving and choose the appropriate solution
  • Use Machine Learning and Natural Language processing to solve problems like text classification, text summarization in Python
Simpliv Llc

By:   Simpliv Llc

  • Location :
    Dubai
  • Fees :
  • Duration :
    2 Hours
  • Schedule :
    18th April 2019 to 18th April 2023
  • Segment :
    IT Training
  • Subject :
    Machine Learning

Course Details

About this Course

Machine Learning is the up and upcoming branch of Artificial Intelligence and it holds great promises for the generations to come. In this course, we will talk about Machine Learning and Artificial Neural Networks and how you can implement a simple Machine Learning Model in MATLAB.

Who this course is for:

  • Anyone who is interested in learning basic concepts of Machine Learning and Neural networks

Basic knowledge

  • The course is beginner level for those who are interested in implementing Machine Learning in MATLAB. No prior technical Knowledge is required. However, if you are already familiar with MATLAB, it can be a plus point

What you will learn

  • You will learn about Machine Learning and how you can train a simple Model in MATLAB on a simple Dataset. You will get to know some basics of MATLAB too and how you can write and run scripts in MATLAB. You will be able to import your own dataset and train it using different parameters to make some interactive prediction model
Simpliv Llc

By:   Simpliv Llc

  • Location :
    Dubai
  • Fees :
    AED 519
  • Duration :
    30 Hours
  • Schedule :
    2nd Mar. 2019 End Date : 27th Apr.2019 Days: Sat-Sun (8Wks) 07:00 AM - 09:00 AM (IST)
  • Segment :
    IT Training
  • Subject :
    Machine Learning

Course Details

Learn to use Python, the ideal programming language for Machine Learning, with this comprehensive course from Simpliv. Gain expertise in core areas of Python and Machine Learning, such as algorithms, model evaluation, supervised vs. unsupervised learning, reinforcement learning, neural networks, k-nearest Neighbor Classifier, Naive Bayes Classifier, and lots more. Become a complete Machine Learning and Python pro. Our experts will show you how to use your knowledge of Python to learn to use it for Machine Learning. All you need is basic knowledge of Python. Our course will take it up from there and make you an expert.

Who is the target audience?

 Programmers, Developers, Technical Leads, Architects, Freshers,Data Scientists, Data Analysts,Business Intelligence Managers.

 

Basic knowledge:

 There are no hard pre-requisites. However, basic understanding of Computer Programming terminologies is beneficial.

Curriculam

Python Introduction

  • Introduction to Python   
  • Core programming concepts   
  • Objects in Python   
  • Visualizations in Python  
  • Packages in Python   
  • Matrix operations  
  • Dataframes

Machine Learning

  • Data Pre-processing   
  • Regression   
  • Classification   
  • Clustering   
  • Association Rule   
  • Natural Language Processing 

New Batch starts from 2nd Mar. 2019 Days: SAT-SUN (8-Wks) 07:00 AM - 09:00 AM (IST)

Simpliv Llc

By:   Simpliv Llc

  • Location :
    Dubai
  • Fees :
    AED 44
  • Duration :
    7 Hours
  • Schedule :
    All days
  • Segment :
    IT Training
  • Subject :
    Machine Learning

Course Details

If you want to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course is for you. The Complete iOS Machine Learning Masterclass™ is the only course that you need for machine learning on iOS. Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants like Google and IBM taking the lead. In this course, you’ll use the most cutting-edge iOS Machine Learning technology stacks to add a layer of intelligence and polish to your mobile apps. We’re approaching a new era where only apps and games that are considered “smart” will survive. (Remember how Blockbuster went bankrupt when Netflix became a giant?) Jump the curve and adopt this innovative approach; the Complete iOS Machine Learning Masterclass™ will introduce Machine Learning in a way that’s both fun and engaging.

In this course, you will:

  • Master the 3 fundamental branches of applied Machine Learning: Image & Video Processing, Text Analysis, and Speech & Language Recognition
  • Develop an intuitive sense for using Machine Learning in your iOS apps
  • Create 7 projects from scratch in practical code-along tutorials
  • Find pre-trained ML models and make them ready to use in your iOS apps
  • Create your own custom models
  • Add Image Recognition capability to your apps
  • Integrate Live Video Camera Stream Object Recognition to your apps
  • Add Siri Voice speaking feature to your apps
  • Dive deep into key frameworks such as coreML, Vision, CoreGraphics, and GamePlayKit.
  • Use Python, Keras, Caffee, Tensorflow, sci-kit learn, libsvm, Anaconda, and Spyder–even if you have zero experience
  • Get FREE unlimited hosting for one year
  • And more!

This course is also full of practical use cases and real-world challenges that allow you to practice what you’re learning. Are you tired of courses based on boring, over-used examples? Yes? Well then, you’re in a treat. We’ll tackle 5 real-world projects in this course so you can master topics such as image recognition, object recognition, and modifying existing trained ML models. You’ll also create an app that classifies flowers and another fun project inspired by Silicon Valley™ Jian Yang’s masterpiece: a Not-Hot Dog classifier app! 

Why Machine Learning on iOS

One of the hottest growing fields in technology today, Machine Learning is an excellent skill to boost your your career prospects and expand your professional tool kit. Many of Silicon Valley’s hottest companies are working to make Machine Learning an essential part of our daily lives. Self-driving cars are just around the corner with millions of miles of successful training. IBM’s Watson can diagnose patients more effectively than highly-trained physicians. AlphaGo, Google DeepMind’s computer, can beat the world master of the game Go, a game where it was thought only human intuition could excel.

In 2017, Apple has made Machine Learning available in iOS 11 so that anyone can build smart apps and games for iPhones, iPads, Apple Watches and Apple TVs. Nowadays, apps and games that do not have an ML layer will not be appealing to users. Whether you wish to change careers or create a second stream of income, Machine Learning is a highly lucrative skill that can give you an amazing sense of gratification when you can apply it to your mobile apps and games.

Why This Course Is Different

Machine Learning is very broad and complex; to navigate this maze, you need a clear and global vision of the field. Too many tutorials just bombard you with the theory, math, and coding. In this course, each section focuses on distinct use cases and real projects so that your learning experience is best structured for mastery.

This course brings my teaching experience and technical know-how to you. I’ve taught programming for over 10 years, and I’m also a veteran iOS developer with hands-on experience making top-ranked apps. For each project, we will write up the code line by line to create it from scratch. This way you can follow along and understand exactly what each line means and how to code comes together. Once you go through the hands-on coding exercises, you will see for yourself how much of a game-changing experience this course is.

As an educator, I also want you to succeed. I’ve put together a team of professionals to help you master the material. Whenever you ask a question, you will get a response from my team within 48 hours. No matter how complex your question, we will be there–because we feel a personal responsibility in being fully committed to our students.

By the end of the course, you will confidently understand the tools and techniques of Machine Learning for iOS on an instinctive level.

Don’t be the one to get left behind. Get started today and join millions of people taking part in the Machine Learning revolution.

topics: ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection 

Who is the target audience?

  • People with a basic foundation in iOS programming who would like to discover Machine Learning, a branch of Artificial Intelligence
  • People who want to pursue a career combining app development and Machine Learning to become a hybrid iOS developer and ML expert
  • Developers who would like to apply their Machine Learning skills by creating practical mobile apps
  • Entrepreneurs who want to leverage the exponential technology of Machine Learning to create added value to their business could also take this course. However, this course does assume that you are familiar with basic programming concepts such as object oriented programming, variables, methods, classes, and conditional statements

BASIC KNOWLEDGE

  • Basic understanding of programming
  • Have access to a MAC computer or MACinCloud website

WHAT YOU WILL LEARN

  • Build smart iOS 11 & Swift 4 apps using Machine Learning
  • Use trained ML models in your apps
  • Convert ML models to iOS ready models
  • Create your own ML models
  • Apply Object Prediction on pictures, videos, speech and text
  • Discover when and how to apply a smart sense to your apps
Cybermodo Training Solutions

By:   Cybermodo Training Solutions

  • Location :
    Dubai
  • Fees :
    AED 2000
  • Duration :
    24 Hours
  • Schedule :
    sun,Tue,Thu 9pm to 9pm
  • Segment :
    IT Training
  • Subject :
    Machine Learning

Course Details

CyberModo has trained many individuals and corporate levels and we are proud for share of contribution we made in the lives of those who we have trained. 

Our Ms-office training program includes word, Excel, PowerPoint and Internet. 

We can assure you of the quality training and all the studies material will be provided to you. Flexible days and time are available on Weekend and Weekdays between 9am to 9pm. 

If you have any further queries, please do not hesitate to call or come down to our institute to discuss more in details with our senior consultant, we will be more than happy to provide you our quick assistance.

Kindly visit our website www.cybermodo.com for IT and www.cybermodo.net for Management for more details and you can also chat live with our online professionals to help you choose the right course for you. 

We appreciate your course inquiry with CyberModo Solutions - Professional Training Center and look forward to pr oviding you with our Professional Training Services.