Bluechip Technologies Asia at Seamless Asia Singapore

We are thrilled to announce that Bluechip Technologies Asia will be showcasing its cutting-edge AI technology innovations at Seamless Asia Singapore!

Don’t miss the opportunity to connect with our team, explore our AI demos, and engage in insightful discussions about the future of technology. Together, let’s shape a smarter and more connected world.

Microsoft Azure API training at Singapore.

Recently I did Microsoft Azure API training at NTUC Singapore.

I covered following topics at the training.

Web API Basics

Controllers, Actions and Rest

Entity Framework Core

Routing

Swagger

Securing the API (Azure B2C, Identity Server)

Working with Postman

Deploy with Azure API App Service

Azure API Management

4 Software developers attended 2 Days of API training.

Data Science Lecturing at Sri Lanka Institute of Information Technology (SLIIT).

Recently I had conducted Data Science Lecturing at Sri Lanka Institute of Information Technology for Data Science batch.  Lecturing was span across six week for 40 students covering following topics –

• Introduction to Spyder IDE, Jupiter Notebook with Python basics
• Azure Machine Learning
• Python Data science libraries / Pandas /Scikit Learn
• Introduction to tenser flow basics
• Basic Neural Networks using tenser flow

Machine Learning for Healthcare Workshop at Faculty of Medicine, University of Indonesia.

Recently I had conducted Machine Learning workshop at Faculty of Medicine, University of Indonesia.  Around 5 attended the workshop. Academic researchers and IT staff attended the workshop.

List of Visualization and Prediction achieved at the workshop

· Shelter Water waste by Province

· Height Based On Province

· Water Condition by Province

· Weight by Province

· Women BMI by Province

· Bird Flu Cases by Category

· Nutrition by Province

· Malnutrition by Occupation

· Men BMI by Province

· Normal by Province

· Nutrition Total by Province

· Nutritional Status by Province

· Nutritional Status of Children by Province

· Province Based Data

http://matadotdata.blogspot.com/2018/10/visualization.html

 

Indonesia Health Data Visualization and Prediction

 

For Training Requirement Contact-

udithamail@yahoo.com

udithait@gmail.com

training@bluechiptraining.biz

Singapore -  
+65 86738158

Sri Lanka -  
+94 716092918

Azure Machine Learning Data Science Workshop at Jakarta, Indonesia [Event Update].

Recently I had conducted Azure Machine Learning workshop at Jakarta, in partnership with Algoritma Indonesia.  Around 10 attended the workshop. Employees from Telkomsel, Government Universities and few other companies attended the workshop.

Event Details-

https://uditha.wordpress.com/2018/08/02/azure-machine-learning-data-science-workshop-at-jakarta-indonesia-2/

 

For Training Requirement Contact-

udithamail@yahoo.com

udithait@gmail.com

training@bluechiptraining.biz

Singapore- 
+65 86738158

Sri Lanka- 
+94 716092918

Azure Machine Learning Movie Recommendation Tutorial.

 

This Video tutorial shows you how to get started with Movie Recommendation algorithm using Azure Machine Learning.

 

MCSA: Machine Learning Certifications Sri Lanka.

Earning an MCSA: Machine Learning demonstrates knowledge relevant to Machine Learning, Data Scientists and Data Analysts positions, particularly those who process and analyze large data sets using R and use Azure cloud services to build and deploy intelligent solutions. It is the first step on your path to becoming a Data Management and Analytics Microsoft Certified Solutions Expert (MCSE).

Course 20774A:
Perform Cloud Data Science with Azure Machine Learning

Course Outline

Module 1: Introduction to Machine Learning

This module introduces machine learning and discussed how algorithms and languages are used.Lessons

• What is machine learning?
• Introduction to machine learning algorithms
• Introduction to machine learning languages

Lab : Introduction to machine Learning

• Sign up for Azure machine learning studio account
• View a simple experiment from gallery
• Evaluate an experiment

After completing this module, students will be able to:

• Describe machine learning

• Describe machine learning algorithms

• Describe machine learning languages

Module 2: Introduction to Azure Machine Learning

Describe the purpose of Azure Machine Learning, and list the main features of Azure Machine Learning Studio.Lessons

• Azure machine learning overview
• Introduction to Azure machine learning studio
• Developing and hosting Azure machine learning applications

Lab : Introduction to Azure machine learning

• Explore the Azure machine learning studio workspace
• Clone and run a simple experiment
• Clone an experiment, make some simple changes, and run the experiment

After completing this module, students will be able to:

• Describe Azure machine learning.

• Use the Azure machine learning studio.

• Describe the Azure machine learning platforms and environments.

Module 3: Managing Datasets

At the end of this module the student will be able to upload and explore various types of data in Azure machine learning.Lessons

• Categorizing your data
• Importing data to Azure machine learning
• Exploring and transforming data in Azure machine learning

Lab : Managing Datasets

• Prepare Azure SQL database
• Import data
• Visualize data
• Summarize data

After completing this module, students will be able to:

• Understand the types of data they have.

• Upload data from a number of different sources.

• Explore the data that has been uploaded.

Module 4: Preparing Data for use with Azure Machine Learning

This module provides techniques to prepare datasets for use with Azure machine learning.Lessons

• Data pre-processing
• Handling incomplete datasets

Lab : Preparing data for use with Azure machine learning

• Explore some data using Power BI
• Clean the data

After completing this module, students will be able to:

• Pre-process data to clean and normalize it.

• Handle incomplete datasets.

Module 5: Using Feature Engineering and Selection

This module describes how to explore and use feature engineering and selection techniques on datasets that are to be used with Azure machine learning.Lessons

• Using feature engineering
• Using feature selection

Lab : Using feature engineering and selection

• Prepare datasets
• Use Join to Merge data

After completing this module, students will be able to:

• Use feature engineering to manipulate data.

• Use feature selection.

Module 6: Building Azure Machine Learning Models

This module describes how to use regression algorithms and neural networks with Azure machine learning.Lessons

• Azure machine learning workflows
• Scoring and evaluating models
• Using regression algorithms
• Using neural networks

Lab : Building Azure machine learning models

• Using Azure machine learning studio modules for regression
• Create and run a neural-network based application

After completing this module, students will be able to:

• Describe machine learning workflows.

• Explain scoring and evaluating models.

• Describe regression algorithms.

• Use a neural-network.

Module 7: Using Classification and Clustering with Azure machine learning models

This module describes how to use classification and clustering algorithms with Azure machine learning.Lessons

• Using classification algorithms
• Clustering techniques
• Selecting algorithms

Lab : Using classification and clustering with Azure machine learning models

• Using Azure machine learning studio modules for classification.
• Add k-means section to an experiment
• Add PCA for anomaly detection.
• Evaluate the models

After completing this module, students will be able to:

• Use classification algorithms.

• Describe clustering techniques.

• Select appropriate algorithms.

Module 8: Using R and Python with Azure Machine Learning

This module describes how to use R and Python with azure machine learning and choose when to use a particular language.Lessons

• Using R
• Using Python
• Incorporating R and Python into Machine Learning experiments

Lab : Using R and Python with Azure machine learning

• Exploring data using R
• Analyzing data using Python

After completing this module, students will be able to:

• Explain the key features and benefits of R.

• Explain the key features and benefits of Python.

• Use Jupyter notebooks.

• Support R and Python.

Module 9: Initializing and Optimizing Machine Learning Models

This module describes how to use hyper-parameters and multiple algorithms and models, and be able to score and evaluate models.Lessons

• Using hyper-parameters
• Using multiple algorithms and models
• Scoring and evaluating Models

Lab : Initializing and optimizing machine learning models

• Using hyper-parameters

After completing this module, students will be able to:

• Use hyper-parameters.

• Use multiple algorithms and models to create ensembles.

• Score and evaluate ensembles.

Module 10: Using Azure Machine Learning Models

This module explores how to provide end users with Azure machine learning services, and how to share data generated from Azure machine learning models.Lessons

• Deploying and publishing models
• Consuming Experiments

Lab : Using Azure machine learning models

• Deploy machine learning models
• Consume a published model

After completing this module, students will be able to:

• Deploy and publish models.

• Export data to a variety of targets.

Module 11: Using Cognitive Services

This module introduces the cognitive services APIs for text and image processing to create a recommendation application, and describes the use of neural networks with Azure machine learning.Lessons

• Cognitive services overview
• Processing language
• Processing images and video
• Recommending products

Lab : Using Cognitive Services

• Build a language application
• Build a face detection application
• Build a recommendation application

After completing this module, students will be able to:

• Describe cognitive services.

• Process text through an application.

• Process images through an application.

• Create a recommendation application.

Module 12: Using Machine Learning with HDInsight

This module describes how use HDInsight with Azure machine learning.Lessons

• Introduction to HDInsight
• HDInsight cluster types
• HDInsight and machine learning models

Lab : Machine Learning with HDInsight

• Provision an HDInsight cluster
• Use the HDInsight cluster with MapReduce and Spark

After completing this module, students will be able to:

• Describe the features and benefits of HDInsight.

• Describe the different HDInsight cluster types.

• Use HDInsight with machine learning models.

Module 13: Using R Services with Machine Learning

This module describes how to use R and R server with Azure machine learning, and explain how to deploy and configure SQL Server and support R services.Lessons

• R and R server overview
• Using R server with machine learning
• Using R with SQL Server

Lab : Using R services with machine learning

• Deploy DSVM
• Prepare a sample SQL Server database and configure SQL Server and R
• Use a remote R session
• Execute R scripts inside T-SQL statements

Microsoft EXAM – 70-774

Perform Cloud Data Science with Azure Machine Learning

https://www.microsoft.com/en-us/learning/exam-70-774.aspx

 

Second Course 20773A:
Analyzing Big Data with Microsoft R

https://www.microsoft.com/en-us/learning/course.aspx?cid=20773

Microsoft EXAM – 70-773

Analyzing Big Data with Microsoft R

https://www.microsoft.com/en-us/learning/exam-70-773.aspx

 

 

By-
Uditha Bandara is specializes in Microsoft AI Development technologies.  He is the South East Asia`s First XNA/DirectX MVP (Most Valuable Professional).  He had delivered sessions at various events and conferences in Hong Kong, Malaysia, Singapore, Sri Lanka and India. He has published several books,articles, tutorials, and demos on his Blog – https://uditha.wordpress.com

· Contact    +94 071-6092918

· udithamail@yahoo.com

· udithait@gmail.com

Microsoft Bot Application Development Tutorial.

 

This Video tutorial shows you how to get started with Microsoft Bot Application development using Azure.

 

Blue Chip Training and Consulting Corporate Video.

 

Version 1.0 of the Blue Chip Training and Consulting Corporate Video

Bot Application Development Workshop Sri Lanka.

 

 

Getting Started with Bots

· What is a Bot

· Examples of Bots

 

Understanding Microsoft’s Bot Framework

· What is the Microsoft Bot Framework?

· Creating a Microsoft Azure Account

· Conversation as a service

· Connector Service and Activities

· Setting up development environment

· Cards and Buttons

 

Creating Bots

· Creating your first bot

· Post method

· Activity Types

· Test bot using Bot Emulator

· Dialogs?

· The IDialog Interface and Saving State

· Demo – Adding Dialogs to Your Bot

· Form Flow

· Customizing Your Forms

· Demo – Creating a Form Flow Dialog

 

Publishing

· Publishing bot to channels

· Registering Bots with Microsoft Bot Framework

· Configuring channels

· Publishing to Microsoft Azure

 

By-
Uditha Bandara is specializes in Microsoft Development technologies.  He is the South East Asia`s First XNA/DirectX MVP (Most Valuable Professional).  He had delivered sessions at various events and conferences in Hong Kong, Malaysia, Singapore, Sri Lanka and India. He has published several books,articles, tutorials, and game demos on his XNA Game Development Blog – https://uditha.wordpress.com

Contact    +94 071-6092918

udithamail@yahoo.com

udithait@gmail.com