Overview: 

This course provides the knowledge and skills to design and implement DevOps processes and practices. Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms. 

Profile: 

Students in this course are interested in designing and implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam. 

Outline: 

Module 1: Planning for DevOps 

• Transformation Planning 
• Project Selection 
• Team Structures 
• Migrating to Azure DevOps 

Lab : Agile Planning and Portfolio Management with Azure Boards 

Module 2: Getting Started with Source Control 

• What is Source Control 
• Benefits of Source Control 
• Types of Source Control Systems 
• Introduction to Azure Repos 
• Introduction to GitHub 
• Migrating from Team Foundation Version Control (TFVC) to Git in Azure Repos 

Lab : Version Controlling with Git in Azure Repos 

Module 3: Managing Technical Debt 

• Identifying Technical Debt 
• Knowledge Sharing within Teams 
• Modernizing Development Environments with Codespaces 

Lab : Sharing Team Knowledge using Azure Project Wikis 

Module 4: Working with Git for Enterprise DevOps 

• How to Structure Your Git Repo 
• Git Branching Workflows 
• Collaborating with Pull Requests in Azure Repos 
• Why Care About Git Hooks 
• Fostering Inner Source 
• Managing Git Repositories 

Lab : Version Controlling with Git in Azure Repos 

Module 5: Configuring Azure Pipelines 

• The Concept of Pipelines in DevOps 
• Azure Pipelines 
• Evaluate use of Hosted versus Self-Hosted Agents 
• Agent Pools 
• Pipelines and Concurrency 
• Azure DevOps and Open-Source Projects (Public Projects) 
• Azure Pipelines YAML versus Visual Designer 

Lab : Configuring Agent Pools and Understanding Pipeline Styles 

Module 6: Implementing Continuous Integration using Azure Pipelines 

• Continuous Integration Overview 
• Implementing a Build Strategy 
• Integration with Azure Pipelines 
• Integrating External Source Control with Azure Pipelines 
• Set Up Self-Hosted Agents 

Lab : Enabling Continuous Integration with Azure Pipelines 

Lab : Integrating External Source Control with Azure Pipelines 

Overview: 

Data science is becoming increasingly popular with more and more industries beginning to value its importance, while recent advancements in open-source software have made the discipline accessible to a wide range of people. Python is a popular choice for most data scientists, owing to its ease of use and versatile nature. 

In this course, we show how Jupyter Notebooks can be used with Python for various data-science applications. Aside from being an ideal "virtual playground" for data exploration, Jupyter Notebooks are equally suitable for creating reproducible data processing pipelines, visualizations, and prediction models. 

We will look at various data modelling concepts using Jupyter Notebooks, and we will see the full power of Jupyter Notebooks as we work through this course. 

This fast-paced practical single-day course focuses on solving challenges presented by data science in a manner that is simple to conceptualize and easy to implement. 

This is achieved by leveraging Python libraries that offer abstractions to complicated underlying algorithms. The result is that data science becomes very approachable for beginners, a fact which is reflected by the strength and growing popularity of the Python ecosystem. In this course, we will cover every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. 

The Jupyter Notebook acts as an add-on tool - a virtual playground - that allows you to create and share live code, equations, visualizations, and text. 

By touching on a variety of topics within the discipline, you'll be exposed to many interesting examples with real-world data. 

Outcome: 

This course focuses on creating reproducible data analyses using Python and Jupyter, and is intended for an audience with a background in Python. As such, we do not cover the basics of Python in this course. However, we will take a brief tour of the Jupyter interface. 

Outline: 

Module 1: Jupyter Fundamentals 

• Basic Functionality and Features
• Our First Analysis - The Boston Housing Dataset

Module 2: Data Cleaning and Advanced Machine Learning 

• Preparing to Train a Predictive Model
• Training Classification Models

Module 3: Web Scraping and Interactive Visualizations 

• Scraping Web Page Data
• Interactive Visualizations

Overview: 

This instructor-led 3 day Blockchain Architecture training is for technical leaders who need to make decisions about architecture, environment, and development platforms. The Certified Blockchain Solution Architecture exam is included with class. 

Outcome: 

Clear understanding of: 

• What is Blockchain 
• How does Blockchain work 
• Types of Blockchains 
• How is Blockchain different from what we have today 
• What are use cases for Blockchain 
• What does a Blockchain app look like 
• How do I design a Blockchain app 
• How do I develop a Blockchain app 
• How do I test a Blockchain app 

Outline: 

Module 1: What is Blockchain 

• Blockchain Basic Principles 
• Centralized and Decentralized Ledgers 
• Mechanics of Blockchain 
• What is a Block? 
• How are Blocks Chained Together? 

Module 2: How Does Blockchain Work 

• Benefits and Drawbacks of Blockchain 
• Cryptography 
• Public Key Cryptography 
• Cryptographic Hashing 
• Blockchain Consensus 
• Proof of Work Consensus 
• Proof of Stake Consensus 
• Other Consensus Mechanisms Explained 
• Lifecycle of a Public Blockchain Transaction 

Module 3: Types of Blockchains 

• Public vs Private Blockchains 
• Open vs Closed Blockchains 
• Open Source Blockchain Projects 
• Blockchain Smart Contracts 
• Tokens and Coins 
• Using Gas in Ethereum 
• “Blockless” Solution Platforms 

Module 4: How is Blockchain Different Than What We Have Today 

• Types of Networks 
• Centralized Networks 
• Distributed Networks 
• Decentralized Networks 
• Software vs Firmware 
• Blockchain vs Database 

Module 5: What Does a Blockchain Application Look Like? 

• Blockchain Application Architecture 
• Integrated Development Environment (IDE) 
• User Interaction Layer 
• Middle/Interface Layer 
• Smart Contracts/Chaincode 

Module 6: How Do I Design a Blockchain Application? 

• Guiding Design Principles 
• Personas (User Types) 
• User Stories (Application Interaction) 
• Application Functional Requirements 
• Application Technical Requirements 
• Design Tasks 
• Fundamental Design Questions 

Module 7: How Do I Develop a Blockchain Application? 

• Fundamental Design Concepts 
• Calling External Contracts 
• Error Handling 
• Pull vs Push Payments 
• On-Chain Data 
• Local Testing Recommendations 
• Not Using Agile Development Process 
• Technology Design Decisions 
• Monolithic vs Modular 
• Complexity Models 

Module 8: How Do I test a Blockchain Application? 

• Blockchain Testing Approaches 
• Unit Testing 
• Developer Level Testing 
• Configuration & Environment Testing 
• Load/Performance Testing 
• Volume/Stress Testing 
• Regression Testing 
• Application Bug Classifications 
• User Load Testing 
• Key Blockchain Architecture Testing Questions 

Module 9: Use Cases for Blockchain 

• Real world implementations of Blockchain 
• Current Use Cases 2021 

Overview: 

In the previous few years, smart phones have become the go-to platform for developing all sorts of applications. Business applications for banks, TV broadcasters, universities, shopping stores... have been migrating from websites to mobile applications. On the same level, Android and iOS devices are dominating the market share of mobile devices. All this has made Android and iOS application development among the most required skills in the IT sector and in the available IT jobs. 

Outcome: 

Clear understanding of: 

• Covers a wide range of flutter development topics. 
• Visual, behavioral and motion rich Flutter widgets 
• Step-by-step lab to built flutter apps 
• Build Google Maps apps  
• Android and iOS app publishing guidelines.  

Outline: 

Module 1: introduction to Flutter and Dart Programming Language 

• Introduction  
• Importance of Flutter  
• Introduction to Dart  
• Writing Dart code  
• DartPad  
• Installing Dart SDK  
• IntelliJ IDEA  
• Lab 1: Installing Dart IDE and Writing Dart Program  
• Installing IntelliJ IDEA  
• Creating a Dart Project Using IntelliJ IDEA  
• Using DartPad  

Module 2: Dart Programming - Syntax 

• Introduction  
• main( ) function  
• Dart Variables  
• Dart Data Types  
• Input of Information to Dart Program 
• Writing Comments  
• Dart Conditional Operators  
• If Statement 
• If – Else Statement  
• If…Else and Else…If... Statement 
• If Else and Logical Operators  
• For Loops  
• While Loops  
• Do-while Loops  
• Break Statement  
• Switch Case Statement  
• Lab 2: Create a Pizza Order Program  

Module 3: Dart Functions & Object-Oriented Programming (OOP) 

• Functions 
• Object-Oriented Programming (OOP) 
• Dart Project Structure and Dart Libraries 
• Lab 3: Create a Small Overtime Payment Program 

Module 4: Introduction to Flutter 

• Understanding Flutter  
• Flutter Framework  
• Android Studio  
• Flutter SDK  
• Installing and Configuring Flutter SDK  
• Creating a New Flutter Project  
• Setup an Android Virtual Device  
• Run a Flutter App  
• Installing Flutter on Mac 
• Test Your Flutter App on iOS Phone with Windows O.S  
• Android Studio Sugar and Spice  
• Run your Apps on a Hardware Device (Physical Phone)  
• Emulator Debug Mode  
• Introduction to Flutter Widgets  
• Creating a Flutter App Using Widgets  
• What is a MaterialApp widget?  
• Lab 4: Creating a Simple Flutter App 

Module 5: Flutter Widgets Fundamentals 

• Image Widget  
• Container Widget  
• Column and Row Widgets  
• Icon Widget  
• Layouts in Flutter  
• Card Widget  
• App Icons for iOS and Android Apps  
• Hot Reload and Hot Restart  
• Stateful and Stateless Widgets 5-55 
• Use a Custom Font  
• Lab: Creating a Restaurant Menu 

Module 6: Navigation and Routing 

• Button Widget  
• FloatingActionButton  
• RaisedButton, FlatButton, and IconButton  
• DropdownButton  
• OutlineButton  
• ButtonBar  
• PopupMenuButton  
• App Structure and Navigation  
• Navigate to a New Screen and Back  
• Navigate with Named Routes  
• Send and Return Data Among Screens  
• Animate a Widget Across Screens  
• WebView Widget in Flutter  
• Lab 6: Navigation and Routing a Pizza Store App

Overview: 

In the previous few years, smart phones have become the go-to platform for developing all sorts of applications. Business applications for banks, TV broadcasters, universities, shopping stores... have been migrating from websites to mobile applications. On the same level, Android and iOS devices are dominating the market share of mobile devices. All this has made Android and iOS application development among the most required skills in the IT sector and in the available IT jobs. 

Outcome: 

Clear understanding of: 

• Covers a wide range of flutter development topics. 
• Visual, behavioral and motion rich Flutter widgets 
• Step-by-step lab to built flutter apps 
• Build Google Maps apps  
• Android and iOS app publishing guidelines.  

Outline: 

Module 1: introduction to Flutter and Dart Programming Language 

• Introduction  
• Importance of Flutter  
• Introduction to Dart  
• Writing Dart code  
• DartPad  
• Installing Dart SDK  
• IntelliJ IDEA  
• Lab 1: Installing Dart IDE and Writing Dart Program  
• Installing IntelliJ IDEA  
• Creating a Dart Project Using IntelliJ IDEA  
• Using DartPad  

Module 2: Dart Programming - Syntax 

• Introduction  
• main( ) function  
• Dart Variables  
• Dart Data Types  
• Input of Information to Dart Program 
• Writing Comments  
• Dart Conditional Operators  
• If Statement 
• If – Else Statement  
• If…Else and Else…If... Statement 
• If Else and Logical Operators  
• For Loops  
• While Loops  
• Do-while Loops  
• Break Statement  
• Switch Case Statement  
• Lab 2: Create a Pizza Order Program  

Module 3: Dart Functions & Object-Oriented Programming (OOP) 

• Functions 
• Object-Oriented Programming (OOP) 
• Dart Project Structure and Dart Libraries 
• Lab 3: Create a Small Overtime Payment Program 

Module 4: Introduction to Flutter 

• Understanding Flutter  
• Flutter Framework  
• Android Studio  
• Flutter SDK  
• Installing and Configuring Flutter SDK  
• Creating a New Flutter Project  
• Setup an Android Virtual Device  
• Run a Flutter App  
• Installing Flutter on Mac 
• Test Your Flutter App on iOS Phone with Windows O.S  
• Android Studio Sugar and Spice  
• Run your Apps on a Hardware Device (Physical Phone)  
• Emulator Debug Mode  
• Introduction to Flutter Widgets  
• Creating a Flutter App Using Widgets  
• What is a MaterialApp widget?  
• Lab 4: Creating a Simple Flutter App 

Module 5: Flutter Widgets Fundamentals 

• Image Widget  
• Container Widget  
• Column and Row Widgets  
• Icon Widget  
• Layouts in Flutter  
• Card Widget  
• App Icons for iOS and Android Apps  
• Hot Reload and Hot Restart  
• Stateful and Stateless Widgets 5-55 
• Use a Custom Font  
• Lab: Creating a Restaurant Menu 

Module 6: Navigation and Routing 

• Button Widget  
• FloatingActionButton  
• RaisedButton, FlatButton, and IconButton  
• DropdownButton  
• OutlineButton  
• ButtonBar  
• PopupMenuButton  
• App Structure and Navigation  
• Navigate to a New Screen and Back  
• Navigate with Named Routes  
• Send and Return Data Among Screens  
• Animate a Widget Across Screens  
• WebView Widget in Flutter  
• Lab 6: Navigation and Routing a Pizza Store App

Overview: 

The Agile Scrum Foundation certification is an industry-recognized Agile Project Management certification for professionals worldwide. This Agile Scrum Foundation course provided by EXIN is designed to test the fundamental understanding Agile Principles and Scrum methodology. 

The Agile Scrum Foundation course imparts fundamental knowledge of Agile and Scrum concepts and allows you to be part of cross-functional and self-manageable teams to produce efficient deliverables. The course allows you to become a skilled Scrum professional, enhance your knowledge and deliver high quality products by applying scrum concepts. 

Individuals and enterprise teams can take up this Agile Scrum Foundation course in live online, and on-site training delivery modes. 

Outcome: 

Clear understanding of: 

• Agile way of thinking 
• Scrum values and principles 
• How to efficiently plan a sprint and arrive at a suitable definition of ‘Ready’ and ‘Done’ 
• Scrum estimation techniques such as Planning Poker Estimation 
• How to monitor and track Scrum projects using various metrics 
• Advanced concepts of Scrum framework 

Outline: 

• Module 1: Concepts of Agile and Scrum, especially “Agile way of Thinking” 
• Module 2: Scrum Practices, Roles, Events, importance of Backlog, and definition of done 
• Module 3: Planning and executing Scrum Projects 
• Module 4: Monitoring and tracking Scrum Projects including Kanban boards, burn-down charts, and information radiators 
• Module 5: Advanced Scrum concepts that includes applying scrum to large and complex projects 
• Module 6: Creating an Agile workspace 

Overview: 

Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this course, you'll learn effective techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems. 

Outcome: 

Clear understanding of: 

• Learning Objectives 
• Use Python to read and transform data into different formats 
• Generate basic statistics and metrics using data on the disk 
• Work with computing tasks distributed over a cluster 
• Convert data from various sources into storage or querying formats 
• Prepare data for statistical analysis, visualization, and machine learning 
• Present data in the form of effective visuals 

Outline: 

Module 1: The Python Data Science Stack 

• Python Libraries and Packages 
• Using Pandas 
• Data Type Conversion 
• Aggregation and Grouping 
• Exporting Data from Pandas 
• Visualization with Pandas 

Module 2: Statistical Visualizations 

• Types of Graphs and When to Use Them 
• Components of a Graph 
• Which Tool Should Be Used? 
• Types of Graphs 
• Pandas DataFrames and Grouped Data 
• Changing Plot Design: Modifying Graph Components 
• Exporting Graphs 

Module 3: Working with Big Data Frameworks 

• Hadoop 
• Spark 
• Writing Parquet Files 
• Handling Unstructured Data 

Module 4: Diving Deeper with Spark 

• Getting Started with Spark DataFrames 
• Writing Output from Spark DataFrames 
• Exploring Spark DataFrames 
• Data Manipulation with Spark DataFrames 
• Graphs in Spark 

Module 5: Handling Missing Values and Correlation Analysis 

• Setting up the Jupyter Notebook 
• Missing Values 
• Handling Missing Values in Spark DataFrames 
• Correlation 

Module 6: Exploratory Data Analysis 

• Defining a Business Problem 
• Translating a Business Problem into Measurable Metrics and Exploratory Data Analysis (EDA) 
• Structured Approach to the Data Science Project Life Cycle 

Module 7: Reproducibility in Big Data Analysis 

• Reproducibility with Jupyter Notebooks 
• Gathering Data in a Reproducible Way 
• Code Practices and Standards 
• Avoiding Repetition 

Module 8: Creating a Full Analysis Report 

• Reading Data in Spark from Different Data Sources 
• SQL Operations on a Spark DataFrame 
• Generating Statistical Measurements 

Overview: 

The development and maintenance of monoliths presents organizations with increasing challenges, resulting in high costs and a slow time-to-market. More and more organizations are therefore attempting to componentize their applications. The latest and greatest paradigm microservices finally seems to deliver on the promises of service-oriented architecture: shortening time-to-market, scalability, autonomy, and exchangeability of technology and databases. The challenges of delivering microservices however are equally big. What makes a component a microservice? How to design, develop and deploy these small services? How does collaboration between analysts, developers, testers, and operations change the organizations? 

Outcome: 

Clear understanding of: 

• Get a clear understand of the strengths and weaknesses of using microservices 
• Learn to understand which problems microservices can solve and which not 
• Help you decide whether microservices will solve your current problems 
• Learn how your software architecture will evolve when you move towards microservices and how to keep your architecture flexible 
• Learn how to design and model applications, microservices and resources in this new architecture 
• Get understanding of the more explicit role of testing in a microservices architecture, and which technique apply well 
• Learn about continuous integration and continuous delivery, and how you design your deployment pipelines 

Outline: 

Module 1: An introduction to components and services 

• Introduction 
• Monoliths versus microservices 
• Strengths and weaknesses of monolithic software 
• A brief history of components and services 

Module 2: Introducing microservices 

• Are we beyond the hype yet? 
• A definition of microservices 
• Characteristics of microservices 
• Containers and scalability 
• Polyglot persistence 
• Promises of microservices 
• Challenges in microservices 
• How  big or small are microservices? 

Module 3: Greenfield or brownfield? 

• Presenting two real world cases 
• Guiding principles from both cases 
• A business process first approach 
• Different levels of business processes 
• An architecture first approach 
• How to split up your existing code base? 
• Brownfield migration to microservices 

Module 4: Evolutionary software architecture 

• Where to start? 
• Introducing design patterns 
• Applications, workers and services 
• Service consuming applications 
• Service delivering components 
• Dealing with communication and REST 
• Authentication and tokens 

Module 5: Designing and building microservices 

• Why modular design is key 
• Guidelines for design microservices 
• The Single Responsibility Principle (SRP) 
• Introducing domain driven design 
• Explaining bounded contexts 
• Modeling micro-applications 
• Wireframes 
• Smart use cases 
• Mapping bounded contexts around resources 
• Working with HTTP verbs 
• Creating a RESTful API for you services 
• Explaining Postel’s law 
• Introducing the resource model 

Module 6: Testing microservices 

• An overview of test techniques for microservices 
• Why manual testing isn’t efficient 
• Unit testing 
• Behavior driven design with examples 
• Introducing service contracts 
• QA (with SonarQube) 
• Integration testing 
• Acceptance testing 
• When to test what in your deployment pipelines 

Module 7: Deployment of microservices 

• Continuous integration 
• Designing your deployment pipelines 
• Moving towards continuous delivery 
• Minimal viable products (MVP)  
• Agile, Kanban and microservices 
• Microservices and DevOps 
• Do microservices change your organization? 

Module 8: Concluding 

• Some final recommendations 
• Do microservices solve all challenges your IT department has? 
• How to proceed? 

Overview: 

Working in groups on simulated challenge and going through the whole Design Thinking cycle. During the process many typical Design Thinking technics and methods will be used.  

Outcome: 

They will learn Scoping - Brain dump of the knowledge of the team members to get a common understanding of the challenge. And also do Research - preparation and execution of interviews to gather relevant user data and generating emphatic understanding of the user. 

Outline: 

• Lesson 1: Design Thinking  
• Lesson 2: Scoping  
• Lesson 3: Research  
• Lesson 4: Synthesis  
• Lesson 5: Ideation  
• Lesson 6: Prototyping  
• Lesson 7: Validation  
• Lesson 8: Application

Overview: 

Many a time conflict takes place in a working environment and most of the time is not due to direct intention of the persons involved. 90% of these incidents are caused by miscommunication. People are not aware that what they are saying or the way they are saying it is offending others. Once you take responsibility of the way to communicate with others, this will minimise the risk of you being misunderstood and work can be done well.  

Outcome: 

• Recognise the importance of communication  
• Identify ways to build interpersonal relationships at the workplace  
• Apply common courtesies when communicating with others  
• Apply appropriate styles to suit various situations  

Outline: 

• Lesson 1: What is Communication  
• Lesson 2: Workplace Communication  
• Lesson 3: Structure of Conversation  
• Lesson 4: Fostering Relationship at Workplace