About Fundamental Technology

​

The Digital Transformation: Fundamental Technology course equips IT and business professionals with essential knowledge of digital transformation and core technologies, including cloud computing, blockchain, and IoT. It highlights the benefits, challenges, and practical applications of these technologies, providing a clear understanding of how they drive innovation and efficiency in real-world business environments.

​

Program Structure  

• 100% online  

• Self-paced  

• modules (50 hours total)  

• Includes video lessons and quizzes  

• Certificate of Completion provided  

 

Modules

​

Fundamental Digital Transformation  

• Key drivers and challenges of digital transformation  

• Shifting from product-centric to customer-centric strategies  

• Customer journeys, omni-channel experiences, and data intelligence  

• Data sources, collection methods, and smart data use  

• Intelligent and automated decision-making in business processes  

 

Digital Transformation in Practice  

• Core concepts of distributed solution design and data integration  

• Key automation technologies: cloud computing, blockchain, IoT, and RPA  

• Introduction to data science in digital transformation: big data, machine learning, and AI  

• Benefits, risks, and challenges of emerging technologies  

• Designing and mapping end-to-end, customer-centric digital solutions  

• How data intelligence is collected, processed, and applied in transformation initiatives.

​

Fundamental Cloud Computing 

• Core cloud computing concepts, terminology, and defining characteristics

• Benefits, challenges, and risks of modern cloud platforms

• Key cloud service models: SaaS, PaaS, and IaaS

• Virtualization, containerization, and architectural building blocks

• Scaling, resiliency, and resource optimization in cloud systems

• Cloud balancing, bursting, and practical deployment strategies

​

Fundamental Blockchain

• Blockchain fundamentals: decentralized models, value propositions, and business/technology drivers

• Applications across industries, including distributed ledgers and relational database comparisons

• Core blockchain architecture: blocks, transactions, nodes, and consensus mechanisms

• Key technologies: cryptography, hashing, coins, tokens, and smart contracts

• Blockchain types and activities: public/private, on-chain/off-chain, cross-chain

• Advanced concepts: Merkle trees, forks, metrics, and lifecycle processes

​

Fundamental IoT 

• IoT foundations: business drivers, benefits, challenges, and core domains (personal, enterprise, utilities, mobile)

• Devices and connectivity: sensors, microcontrollers, RFID, LPWANs, and power sources

• Data and commands: telemetry, real-time contextual data, and data serialization methods (JSON, Protocol Buffers)

• IoT architecture: layers, gateways, platforms, and key design considerations

• Communication protocols: REST, HTTP, CoAP, MQTT, and radio transport options

• Advanced approaches: edge and fog computing for efficiency and scalability

​

***Participants may specialize in either  Fundamental IoT or Fundamental Blockchain according to their interest.

​

Fundamental AI Architecture 

• Comparing AI architecture and engineering, including product vs. custom designs

• System scopes and solution types: monolithic, modular, and hybrid architectures

• Data management approaches: storage models, ingestion, preprocessing, and feature engineering

• Core system components: inference engines, model repositories, and decision-making logic

• Monitoring and performance: operations, data, model evaluation, and bias detection

• Supporting mechanisms: explainability, robustness, security, and data quality controls