Blockchain is essentially an immutable and digital ledger of transactions that is duplicated and distributed across the entire network of computer systems on the blockchain.

Arrays, Stacks, Queues, Trees, Linked Lists, Graphs, HashMap, Hash Table.

Search Algorithms, Sorting Algorithms, Object Oriented Design (OOPS), Recursion and Dynamic Programming, Time Complexity.

• Functional Requirements
• Non-Functional Requirements (Scalability, Reliability, Availability, Efficiency, Serviceability)
• API Design
• Estimation (Capacity Planning)
• Database Schema Design
• High Level Design (HLD)
• Low Level Design (LLD)

Digital transformation is the adoption of digital technology by a company to improve business processes, value for customers and innovation to meet changing business and market requirements.

A cloud migration is when a company moves some or all of its data center capabilities into the cloud, usually to run on the cloud-based infrastructure (IaaS) provided by a cloud service provider.

Cloud migration strategies Rehosting (lift and shift), Replatforming, Repurchasing, Refactoring, Retiring and Retaining.

DevOps is an approach that combines software development (Dev) and Information technology operations and DevOps automation is the addition of technology that performs tasks with reduced human assistance to processes that facilitate feedback loops between operations and development teams so that iterative updates can be deployed faster to applications in production. Continuous integration/continuous delivery (CI/CD) pipelines are a practice focused on improving software delivery using either a DevOps or site reliability engineering (SRE) approach.

• Gap Analysis
• Stakeholders buy-in and engagement
• Planning and Migration Strategy
• Implementation
• Monitoring and Cloud Governance

• Product Strategy
• Product Design
• Product Roadmap
• Estimation
• Analytical/Metrics
• Behavioral
• Leadership

• Product Design
• Execution
• System Design
• Product Strategy
• Behavioral
• Leadership
• Product Strategy
• Product Design
• Estimation
• Behavioral
• System Design
• Communication & Teamwork
• Prioritization
• User Experience
• Analytical Skills (Metrics, Market Research).

Data Science has a lot to play with data, algorithms, and statistics and it is the area of study which involves extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes.

Various Machine Learning algorithms (Linear Regression, Logistic Regression, Decision Trees, Naive Bayes, KNN, SVM, K-Means Clustering, PCA, Neural Networks, Random Forests) used for solving different types of problems, as a single algorithm cannot be the best for all types of use cases. These algorithms find an application in various tasks like prediction, classification, clustering, etc. from the dataset under consideration.

Machine Learning is a current application of AI based around the idea that be able to give machines access to data and let them learn for themselves. ML Algorithms like Linear Regression, Logistic Regression, Decision Trees, Naive Bayes, KNN, SVM, K-Means Clustering, PCA, Neural Networks, Random Forests.

Deep learning is a subset of machine learning in which multilayered neural networks learn from vast amounts of data that enables computers to solve more complex problems.

• Project Charter
• RACI
• Change Management
• Risk
• PMBOK Process Groups (Process Metrics (Initiation, Planning, Execution, Monitoring & Control and Closing)
• Process Metrics (Initiation, Planning, Execution, Monitoring & Control and Closing)

The Internet of Things (IoT) describes the network of physical objects—things—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet.

The industrial internet of things (IIoT) refers to the extension and use of the internet of things (IoT) in industries and IIoT encompasses industrial applications, including robotics, medical devices, and software-defined production processes.

IaaS: Compute, Network, Storage (Image/File), LB, Proxy, Rev Proxy

PaaS: Service Mesh, Service Discovery

Cloud Native: Containers, Kubernetes(k8s), Microservices, Serverless, API Gateway

QA is about making sure that the design meets stakeholders' expectations, while testing (white-box, Smoke, Integration, Exploratory, Performance, API) is mainly detecting the bugs or bigger failures. Testing focuses on system control and error detection, with product orientation and corrective actions.

• Cloud Security and Privacy
• Cloud Cost Optimization
• Cloud Monitoring
• Cloud Risk Management
• Cloud Authorization
• Cloud Orchestration
• Cloud Compliance