Data Science Academy

Machine Learning and Game Development Workshops.

Machine Learning and Game Development Workshops sri lanka

Machine Learning and Game Development Workshops sri lanka

Recently I did 2 workshop on Game Development and Machine Learning at Sabaragamuwa University and SLIIT.

Machine Learning and Game Development Workshops sri lanka

Data Science and Machine Learning Workshop Sri Lanka.

Recently I had conducted the workshop on Data Science and Machine Learning.Around 7 participants attended the workshop.

Topic covered at the workshop-

https://uditha.wordpress.com/2017/11/15/big-data-and-machine-learning-workshop-sri-lanka/

For Training Requirement Contact-

udithamail@yahoo.com

udithait@gmail.com

training@bluechiptraining.biz

Introduction to Machine Learning Workshop

Introduction to Machine Learning Workshop

Course Content

The main purpose of the workshop is to give students the ability to analyze and present data by

using Azure Machine Learning Python ,Jupiter Notebook and to provide an introduction to the use of machine learning.

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

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

Module 3: Managing Data-sets
At the end of this module the student will be able to 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

Module 4: 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
· Using regression algorithms
· Using neural networks

Module 5: 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

Module 6: 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

Module 7: Python Data Science tools

Module 8 :Reinforcement Learning Basics (RL)

Cost – 6000 Rupees
Feel free to contact us for any inquiries

uditha bandara – 0716092918

Uditha Bandara (MVP) is specializes in Data Science, Mobile App and Blockchain 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, Indonesia, Sri Lanka and India. He has published several books,articles, tutorials, and demos on his Blog – https://uditha.wordpress.com
http://datasciencesrilanka.education

Register URL – https://bit.ly/3fdAK56
Contact us at +94 (071) 6092918

udithait@gmail.com
training@bluechiptraining.biz

https://www.meetup.com/Colombo-AI-Technology-Meetup/events/276692216/

Python Online Training Singapore.

Python Online Training Sri Lanka.

Recently we had conducted online Python training for Bank of America staff at Singapore.

Following topics covered at the training.

http://www.bluechiptraining.biz/python-programming-course-sri-lanka/

Python Online Training Sri Lanka.

Python Online Training Sri Lanka.

For Training Requirement Contact-

udithait@gmail.com

training@bluechiptraining.biz

Sri Lanka

+94 0716092918

Singapore-

+65 86738158

IBM AI Enterprise Workflow Data Science Specialist Training

2

In this program, we decided to take a different approach than traditional product certifications, and instead of building a product-centric certification,

we decided to build a process-centric certification with specific guiding principles:

1.    Using a single use case/real world scenario as the foundation to work through what it takes to build an end to end AI solution

2.    Leveraging Design thinking as a framework to work through the translation of business goals into AI technical implementations

3.    Bringing together different capabilities such as Machine Learning, Optimization, and specific narrow-AI functionality

4.    Leveraging python as the tool of choice for building AI models, and bringing in Watson Studio where it adds value on top of Python and other open source tools

Section 1: Scientific, Mathematical, and technical essentials for Data Science and AI

· Explain the difference between Descriptive, Prescriptive, Predictive, Diagnostic, and Cognitive Analytics

· Describe and explain the key terms in the field of artificial intelligence (Analytics, Data Science, Machine Learning, Deep Learning, Artificial Intelligence etc.)

· Distinguish different streams of work within Data Science and AI (Data Engineering, Data Science, Data Stewardship, Data Visualization etc.)

· Describe the key stages of a machine learning pipeline.

· Explain the fundamental terms and concepts of design thinking

· Explain the different types of fundamental Data Science

· Distinguish and leverage key Open Source and IBM tools and technologies that can be used by a Data Scientist to implement AI solutions

Section 2: Applications of Data Science and AI in Business

· Identify use cases where artificial intelligence solutions can address business opportunities

· Translate business opportunities into a machine learning scenario

· Differentiate the categories of machine learning algorithms and the scenarios where they can be used

· Show knowledge of how to communicate technical results to business stakeholders

· Demonstrate knowledge of scenarios for application of machine learning

Section 3: Data understanding techniques in Data Science and AI

· Demonstrate knowledge of data collection practices

· Explain characteristics of different data types

· Show knowledge of data exploration techniques and data anomaly detection

· Use data summarization and visualization techniques to find relevant insight

Section 4: Data preparation techniques in Data Science and AI

· Demonstrate expertise cleaning data and addressing data anomalies

· Show knowledge of feature engineering and dimensionality reduction techniques

· Demonstrate mastery preparing and cleaning unstructured text data

Section 5: Application of Data Science and AI techniques and models

· Explain machine learning algorithms and the theoretical basis behind them

· Demonstrate practical experience building machine learning models and using different machine learning algorithms

Section 6: Evaluation of AI models

· Identify different evaluation metrics for machine learning algorithms and how to use them in the evaluation of model performance

· Demonstrate successful application of model validation and selection methods

· Show mastery of model results interpretation

· Apply techniques for fine tuning and parameter optimization

Section 7: Deployment of AI models

· Describe the key considerations when selecting a platform for AI model deployment

· Demonstrate knowledge of requirements for model monitoring, management and maintenance

· Identify IBM technology capabilities for building, deploying, and managing AI models

Section 8: Technology Stack for Data Science and AI

· Describe the differences between traditional programming and machine learning

· Demonstrate foundational knowledge of using python as a tool for building AI solutions

· Show knowledge of the benefits of cloud computing for building and deploying AI models

· Show knowledge of data storage alternatives

· Demonstrate knowledge on open source technologies for deployment of AI solutions

· Demonstrate basic understanding of natural language processing

· Demonstrate basic understanding of computer vision

· Demonstrate basic understanding of IBM Watson AI services

For Training Requirement Contact-

udithait@gmail.com

training@bluechiptraining.biz


Sri Lanka

+94 0716092918

Singapore-
+65 86738158

MATLAB FUNDAMENTALS Course.

1

This course provides a comprehensive introduction to the MATLAB® technical computing environment.

No prior programming experience or knowledge of MATLAB is assumed. Themes of data analysis, visualization, modeling, and programming are explored throughout the course.

You will learn:

• How to use Matlab to analyze data and report results

• How to load and save information using several file formats including text, binary and Excel

• How to automate analyses using basic programming and built-in functions

• How to create robust, reusable and maintainable code

• To design and present data in graphs and GUI windows

• The basic skills that will enable you to continue learning advanced topics by yourself, at your own pace

1. The Matlab environment

· Learn how to use the Matlab desktop

· The Matlab workspace and command window

· Using the command history

· Using the documentation system and other online resources

2. Using numeric and character-based data

· Matlab’s data types and precisions

· Matlab’s data storage types

· Creating and manipulating data

· Operators and expressions

· Using functions

· Accessing sub-elements and data ranges

3. Matlab Programming

· Creating your first Matlab script

· The Matlab editor

· Using the debugger

· Scripts vs. functions

· Controlling program control flow

· Coding conventions and best practices

4. Analyzing data

· Removing and fixing invalid data

· Fitting data

· Error handling

5. Saving and loading data

· To/from Matlab workspace

· To/from text or binary files

· To/from Excel

· To/from a webpage

6. Visualizing data

· Displaying results in the command window

· Plotting data in 2D and 3D graphs

· Presenting data tables

· Exporting graphics to external applications

For Training Requirement Contact-

udithait@gmail.com

training@bluechiptraining.biz


Sri Lanka

+94 0716092918

Singapore-
+65 86738158

NASA Space Apps Challenge 2020.

NASA Space Apps Challenge 2020

NASA is inviting coders, entrepreneurs, scientists, designers, storytellers, makers, builders, artists, and technologists to

come together in a global, virtual hackathon. During a period of 48 hours, participants from around the world will come

together to create virtual teams and solve challenges using NASA’s open-source data.


We are proud and thrilled to announce ‘NASA Space Apps Colombo, 2020’, which is the very

first international hackathon event in Sri Lanka, in line with NASA’s guidelines and direct collaboration.

The event is organised by SEDS Sri Lanka, which is the international body that strives to promote

space exploration and development via educational and engineering projects.

NASA Space Apps Challenge 2020

Official Web –  https://www.spaceappscolombo.org/

AI for Business Leaders Workshop Sri Lanka.

AI for Business Leaders Workshop Sri Lanka.

Recently I did AI for Business Leaders Workshop at Orel IT. I covered following topics during the workshop.

AI based business opportunities

AI development life cycle

Cloud based AI technologies

AI Use Cases

AI for Business Leaders Workshop Sri Lanka.

AI for Business Leaders Workshop Sri Lanka.

AI for Business Leaders Workshop Sri Lanka.

For Training Requirement Contact-

udithait@gmail.com

training@bluechiptraining.biz


Sri Lanka

+94 0716092918

Singapore-

+65 86738158

Online Healthcare Machine Learning workshop at Melbourne.

Online Healthcare Machine Learning workshop at Melbourne.

Recently we had conducted online Machine Learning workshop for St John of God Health Care Doctors at Melbourne.

Following topics covered at the training.

Introduction to Data Science

Introduction to Machine Learning

Machine Learning in Healthcare

Healthcare research in Machine Learning.

Online Healthcare Machine Learning workshop at Melbourne.

Online Healthcare Machine Learning workshop at Melbourne.

Sri Lanka DevOps Community Online Meetup.

Sri Lanka DevOps Community Online Meetup

Machine Learning Operations (MLOps) is based on DevOps principles and practices that increase the efficiency of workflows. For example, continuous integration, delivery, and deployment.

MLOps applies these principles to the machine learning process, with the goal of:

• Faster experimentation and development of models
• Faster deployment of models into production
• Quality assurance

Agenda –
• Azure Machine Learning
• ML Pipeline
• Azure DevOps Integration

Azure Architect Technologies (AZ-300) Online Singapore Training.

Azure Architect Technologies (AZ-300) Online Singapore Training.

Recently I had conducted Azure Architect Technologies (AZ-300) online training. Following topics covered at the training.

Deploying and Configuring Infrastructure

Implementing Workloads and Security

Understanding Cloud Architect Technology Solutions

Creating and Deploying Apps

Developing for the Cloud

http://www.bluechiptraining.biz/azure-architect-technologies-az-300-training-sri-lanka/

Azure Architect Technologies (AZ-300) Online Singapore Training.

Azure Architect Technologies (AZ-300) Online Singapore Training.

Around 20 participants attended the training.

For Training Requirement Contact-

udithait@gmail.com

training@bluechiptraining.biz

Sri Lanka

+94 0716092918

Singapore-
+65 86738158

Data Science Solution on Azure Online Singapore Training.

11111

Recently I had conducted Azure Data Science solution online training. Following topics covered at the training.

Module 1: Introduction to Azure Machine Learning
Module 2: No-Code Machine Learning with Designer
Module 3: Running Experiments and Training Models
Module 4: Working with Data
Module 5: Compute Contexts
Module 6: Orchestrating Operations with Pipelines
Module 7: Deploying and Consuming Models
Module 8: Training Optimal Models
Module 9: Interpreting Models
Module 10: Monitoring Models

qqqqq

2222

Around 20 participants attended the training.

For Training Requirement Contact-

udithait@gmail.com

training@bluechiptraining.biz

Sri Lanka

+94 0716092918

Singapore-
+65 86738158