Python Online Training Singapore.
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/
For Training Requirement Contact-
Sri Lanka
+94 0716092918
Singapore-
+65 86738158
IBM AI Enterprise Workflow Data Science Specialist Training
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-
Sri Lanka
+94 0716092918
Singapore-
+65 86738158
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.
Official Web – https://www.spaceappscolombo.org/
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
For Training Requirement Contact-
Sri Lanka
+94 0716092918
Singapore-
+65 86738158
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.
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
Data Science Solution on Azure Online Singapore Training.
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
Around 20 participants attended the training.
For Training Requirement Contact-
Sri Lanka
+94 0716092918
Singapore-
+65 86738158
Cloud Machine Learning Workshop Sri Lanka.
https://www.meetup.com/Colombo-AI-Technology-Meetup/events/270402228/
Register URL – https://bit.ly/3fdAK56
Contact us at +94 (071) 6092918
Feel free to contact us for any inquiries
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
Tools to Working from home in Sri Lanka.
Working from home is getting more important in these days due to lockdowns in many countries. Following free and paid tools helps you to manage your work efficiently at home.
Skype
We all know Skype for conference calls, instant messaging with clients or chat rooms. But if you haven’t been using it for business, you may have missed out on some new functionalities. Record Skype calls to capture key decisions, and use live subtitles to read the words spoken. Easily share presentations, images, or anything on your screen during a call with integrated screen sharing. Access one skype account across multiple devices—even Alexa!
Slack
Slack is the communication tool that brings remote teams together. The platform organizes conversations into channels, which team members can join and leave, as needed, so nobody receives messages or notifications irrelevant to them. Conversations can also be had in threads, which keep messages outside of the main channel so chats don’t get in the way of main topics and projects.
Key features
• Instant messaging: Live communication between every team member for seamless collaboration.
• Statuses: Users can set availability statuses to focus on individual tasks as needed.
• File sharing: Drag-and-drop file sharing for PDFs, images, videos and other common files types.
• Voice & video calls: Voice and video calls directly from within Slack.
• Screen sharing: Allows team members to show their work to others in real-time for stronger collaboration.
GoToMeeting
GoToMeeting is a web-hosted service created and marketed by LogMeIn. It is an online meeting, desktop sharing, and video conferencing software package that enables the user to meet with other computer users, customers, clients or colleagues via the Internet in real time.
Zoom
Zoom is a suite of video conferencing and communication tools designed for remote teams, virtual businesses conferences, webinars and other corporate purposes. We use Zoom for our virtual meetings, which we can use to run video and voice calls, but it’s capable of much more than this.
Key features
· Video meetings: Remote teams can run video meetings and one-to-one video calls.
· Voice calls: You can also run group or one-to-one voice calls when face-to-face meetings aren’t necessary.
· Webinars: You can also use Zoom to host webinars.
· Messaging: Team members can send messages using Zoom.
· File sharing: Share files during and outside of video/voice chats for collaboration between members.
Microsoft Teams
Teams is a chat-based collaboration tool that provides global, remote, and dispersed teams with the ability to work together and share information via a common space. You can utilize cool features like document collaboration, one-on-one chat, team chat, and more. Microsoft Teams is also fully integrated with many other Office 365 services, such as Skype, SharePoint, Exchange, and Yammer.
https://products.office.com/en-us/microsoft-teams/work-remotely
Team viewer
TeamViewer is a remote access software that allows desktop sharing and file transfer. It is an exceptionally secure software that does not disturb the functioning of existing firewall or antivirus in your system. TeamViewer 14 protects your data simultaneously while you are sharing your desktop screen through remote access.
TeamViewer helps in increasing your output significantly. The remote access software helps in sharing files while your system is on the screen sharing mode.
Features of TeamViewer 14
• Advanced Device Grouping
• One-Click Remote
• Optimized for macOS
• Custom Device Information
• Performance stability on low bandwidth
• Improved connection quality
• QuickSupport for service camp integration
https://www.teamviewer.com/en/
Cisco Webex
Cisco Webex is a cloud-based collaboration suite comprised of Webex Meetings, Webex Teams and Webex Devices. The Webex suite is a merger of Cisco’s WebEx web conferencing platform and Cisco Spark team collaboration app. The services rebranded under Webex in April 2018 to centralize Cisco’s collaboration portfolio.
Features of Cisco Webex
• HD Video Conferencing
• Platform Versatility and Data Protection
• Secure Online Meetings Anywhere
• Integrated Communication
• Easily Share Desktops and Documents
Data Science and Machine Learning March 2020 Workshop Sri Lanka.
Few weeks ago I had conducted the workshop on Data Science and Machine Learning.
Around 12 attended the workshop.Employees from Stretch line,Enso,Sri Lanka Insurance (SLIC),Sri Lanka Tourism Development Authority
and Attune came to the event.
Topic covered at the workshop-
https://uditha.wordpress.com/2017/11/15/big-data-and-machine-learning-workshop-sri-lanka/
For Training Requirement Contact-
Machine learning and AI Bootcamp training at Colombo , Sri Lanka.
Recently I did Data Science and Machine learning Bootcamp training at Sri Lanka.
This 3 days training was focus on getting started with Data Science technologies. Azure machine learning studio, R studio, Jupyter Notebook ,
Spyder with Python for data science. It also includes real world usage of machine learning for regression, classification and product recommendations.
Course Outline –
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
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
Managing Datasets
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
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
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
Introduction to Python
• Python History
• Installing Python
• Installing IDE
Data types
• Numbers
• Sequences
• File
• Tuples
• Dictionaries
Data Science Intro
• Why Python for Data Science
• Popular packages
• Use cases
• Popular Libraries
• Panda
• Numpy
• Matplotlib
• Scikit-learn
Working with data
• Reading & Writing to different data sources
• Cleaning data
• Visualization
• Data Transformation
Introduction to Deep Learning
· Deep learning basics
· Deep learning tools
· Introduction to neural network
· CNN, ANN, RNN neural network
Introduction to Tensor Flow
· Installing Tensor Flow
· Tensor Flow basics
· Basic Neural Networks using tenser flow
· Advanced Neural Networks using tenser flow (CNN, RNN, ANN)
24 software engineers attended 3 Days of training.
For Training Requirement Contact-