Toward Business Transformation
-
Led by Dr. Hong-Linh Truong, we provide high-quality services including deep training programs (online, hybrid), effective consulting, and innovative solutions for companies transforming their businesses with modern Data Analytics and Platforms, Data Science, AI/ML/LLMs Systems, Cloud Modernization, and AI Assistant/Agent.
CONSULTING AND DEVELOPING SOLUTIONS
ON-DEMAND
Assess, analysis, and recommend for particular needs
- short time period
- 1-5 cycles, 4 hours/1 cycle
- including a meeting in 1 hour for discussion
PROJECT-BASED
Research, develop, and deploy solutions and co-develop products
- within a project
- according to specific project
- according to project's scopes
REGULAR
Assess, analysis, and recommend for long-run transformation and modernization
- long time period
- 3-6-9-12 months
- including 2-4 monthly meetings (1 hour/meeting) for discussion
TRAINING AND BUILDING TEAMS
Core-1: DIGITAL TRANSFORMATION
Modernizing, Transforming and Automating Business and Operation Workflows with IoT, Data Analytics, and Cloud Services
Making Data-centric Decision and Building Digital Workforce
------------------------------------------------------------------------------------------------------------------------
Core-2: DATA PLATFORM FUNDAMENTALS AND TECHNOLOGIES
Fundamentals and technologies for versatile data journeys: including architectures, data lifecycle management, data lakehouse and tiering, workflow analysis, and near real-time stream processing
------------------------------------------------------------------------------------------------------------------------
Core-3: AI AGENTS, GENAI SERVICES, AND AGENTIC SYSTEMS
Fundamentals on large language models (LLMs) and agentic systems utilization, services and application integration for development and business tasks
------------------------------------------------------------------------------------------------------------------------
Core-4: AI IMPLEMENTATION STRATEGIES, TRUSTWORTHINESS AND RISKS
Understand Potentials, Requirements, and How to apply: ML and AI/GenAI capabilities and their relationships for common use cases
Trustworthy AI/GenAI, Principles and components of trustworthiness, potential risks and risk governance frameworks
------------------------------------------------------------------------------------------------------------------------
Prac-1: PRINCIPLES TO HANDLE DATA QUALITY
High level view on Data Quality & Key principles to handle Data Quality
Data quality in real-time systems
Tools and hands-on
------------------------------------------------------------------------------------------------------------------------
Prac-2: DATA ANALYTICS FOR OPERATIONS
Data analytics for common use cases and suitable solutions for data platforms and infrastructure operations
Workflows, Tools and hands-on
------------------------------------------------------------------------------------------------------------------------
Prac-3: MACHINE LEARNING (ML) ENGINEERING
Preparing data, building, training, and deploying machine learning models and services
Workflows, Tools and techniques
Hands-on with real cases of customers/practitioners
------------------------------------------------------------------------------------------------------------------------
Prac-4: WORKFLOW SYSTEMS AND PROGRAMMING SPECIALIZATION
Workflow and Distributed Programming Models
Airflow Introduction and Hands-on basic workflow
Managing data exchange in workflows
Airflow complex automation workflows
Advanced data analysis workflows: analysis, scheduling, resources
Workflows specialized for different application domains
GenAI/LLM workflow hands-on: using workflow technologies to design and create workflows integrating AI/LLM services with multiple types of other services for complex business processes
------------------------------------------------------------------------------------------------------------------------
3 training levels: AI in general, AI engineering, AI advanced
2-6 hours/module
Targets:
Making strategic AI decisions, developing AI strategies and roadmap for digital transformation, evaluating AI risks
Assess existing solutions/tools, integrate existing solutions/tools, designing AI/ML services with current infrastructures/systems, modernizing IT services
Understanding AI/ML programming, coding/developing AI/ML models, training/deploying AI/ML services/models, monitoring and managing AI/ML services (observability)
Customized workshops, training and building teams for IoT-Edge-Cloud, AI/ML/LLMs, Automation and Data Analytics Workflows solutions
3 hours/1 day/3 days/on-project training