Agile Development Of Artificial Intelligence With Scrum

SCRUM and Artificial Intelligence

What you'll learn

Understand Agile Development and SCRUM

Gain a comprehensive understanding of Agile Development principles and the SCRUM framework

Learn how Agile and SCRUM differ from traditional, linear methodologies and why they are effective for managing complex projects

Learn SCRUM Roles and Responsibilities

Understand the roles within SCRUM, including the Product Owner, Scrum Master, and Development Team

Recognize the responsibilities of each role and how they collaborate to achieve project goals

Master SCRUM Events and Artifacts

Familiarize yourself with the key SCRUM events such as Sprint Planning, Daily Scrums, Sprint Reviews, and Sprint Retrospectives

Understand the importance of SCRUM artifacts, including the Product Backlog, Sprint Backlog, and Increment

Apply SCRUM in AI Projects

Learn how to adapt SCRUM methodologies to the unique challenges of AI projects, such as managing data, models, and computational resources

Understand the importance of iterative development and continuous improvement in AI projects.

Develop AI Models Using SCRUM

Gain practical experience in planning, developing, and deploying AI models within the SCRUM framework

Learn how to manage AI projects using SCRUM, including sprint planning, retrospective sessions, and continuous feedback loops

Implement AI Testing and Validation Strategies

Understand the importance of testing and validation in AI projects, including data validation, model performance testing, and bias management

Learn how to use tools and techniques to ensure the robustness, fairness, and ethical considerations of AI models

Manage Computational Resources and Model Optimization

Learn how to optimize AI models for deployment, including techniques like quantization, pruning, and knowledge distillation

Understand the management of computational resources, including auto-scaling, resource quotas, and monitoring

Ensure Ethical and Responsible AI Development

Explore the ethical challenges in AI development, including bias, fairness, and transparency

Learn how to implement ethical AI practices and manage bias in AI models

Develop a Final AI Project Using SCRUM

Apply all the knowledge and skills learned throughout the course to develop a final AI project using the SCRUM methodology

Create a web application with generative AI, integrating everything learned in the course

Prepare for Professional AI Project Management

Gain the practical skills and knowledge necessary to manage real-world AI development projects using Agile and SCRUM methodologies

Develop a practical methodology for approaching AI projects, combining theoretical knowledge with hands-on experience

Requirements

Basic knowledge of programming and python

Description

Welcome to the Course on Agile Development of Artificial Intelligence with SCRUM!Are you ready to revolutionize the way AI projects are developed and managed? Whether you're a seasoned developer, a project manager, or a beginner in AI, this course is your gateway to mastering the art of combining Agile Development and the SCRUM framework with the cutting-edge world of Artificial Intelligence.What is this course about?This course is not just another programming course—it’s a comprehensive immersion into the most effective methodologies for managing, developing, and deploying AI projects. Over the next modules, you’ll learn how to combine two revolutionary worlds: Agile software development and generative Artificial Intelligence, using the SCRUM framework as your guiding tool.You’ll explore everything from the fundamentals of Agile and SCRUM to the practical implementation of AI models in real-world projects. Whether you’re building a recommendation system, a customer churn prediction model, or a generative AI web application, this course will provide you with the tools, templates, and knowledge to succeed.Why take this course?Real-World Applications: Learn how to manage AI projects using SCRUM, from data collection and model development to deployment and continuous improvement.Hands-On Experience: Dive into practical case studies, templates, and exercises that will prepare you for professional AI project management.Cutting-Edge AI Techniques: Discover how to optimize AI models, manage computational resources, and ensure ethical and responsible AI development.SCRUM for AI: Understand how to adapt the SCRUM framework to the unique challenges of AI projects, including data management, model testing, and iterative development.What will you learn?This course is structured into 9 intensive modules, designed to take you from the basics to advanced AI project management. Here’s a sneak peek of what you’ll master:Agile Development and SCRUM Fundamentals:Understand the Agile Manifesto and SCRUM principles.Learn the roles, events, and artifacts of SCRUM.SCRUM in AI Projects:Adapt SCRUM to manage AI projects, including data sprints, model development, and continuous improvement.AI Model Development with SCRUM:Plan, develop, and deploy AI models using SCRUM, with a focus on iterative delivery and continuous feedback.AI Testing and Validation:Learn how to validate AI models, manage bias, and ensure ethical considerations.Computational Resource Management:Optimize AI models and manage computational resources efficiently.Ethical AI Development:Explore the ethical challenges in AI and learn how to implement fair, transparent, and responsible AI systems.Final AI Project:Apply everything you’ve learned to develop a web application with generative AI, using the SCRUM methodology.Who is this course for?AI Enthusiasts: If you’re passionate about AI and want to learn how to manage AI projects effectively, this course is for you.Project Managers: If you’re looking to transition into AI project management or enhance your existing skills, this course will provide you with the tools and knowledge you need.Developers: If you’re a developer interested in integrating AI into your projects using Agile and SCRUM, this course will guide you step by step.Entrepreneurs: If you’re building an AI-driven startup or product, this course will help you manage your AI projects efficiently and ethically.What’s included?Detailed PowerPoint Presentations: Clear and concise slides to guide you through each module.Templates: Ready-to-use templates for sprint planning, retrospective sessions, and AI project management.Case Studies: Real-world examples of AI projects managed with SCRUM.Exams: Test your knowledge with quizzes and exams to reinforce your learning.Final Project: A hands-on project where you’ll develop a generative AI web application using everything you’ve learned.Are you ready to transform how AI projects are developed?This course is designed to be challenging yet rewarding. You’ll work with complex concepts, but we’ll guide you step by step, with method and clarity. By the end of this course, you’ll not only have theoretical knowledge but also a practical methodology for approaching AI projects in a professional and ethical manner.Join us and take the first step toward mastering Agile AI development with SCRUM!Whether you’re looking to advance your career, build innovative AI solutions, or simply deepen your understanding of Agile and AI, this course will provide you with the skills and confidence to succeed.Enroll now and start your journey to becoming an AI project management expert!

Overview

Section 1: Module 1. Introduction to Agile Development and SCRUM

Lecture 1 Introduction to the fundamentals of agile development

Lecture 2 Introduction to SCRUM

Lecture 3 Roles in Scrum

Lecture 4 SCRUM Events

Lecture 5 Scrum Artifacts

Lecture 6 Use Case: Managing a Sprint in an Agile SCRUM Project

Lecture 7 Additional Resources for Agile Development and SCRUM

Lecture 8 Presentation. Introduction to Agile Development and SCRUM

Section 2: Module 2. Artificial Intelligence and Agile Development

Lecture 9 Basic concepts of AI

Lecture 10 Generative AI

Lecture 11 Specific Challenges in AI Projects

Lecture 12 Adapting SCRUM for AI Projects

Lecture 13 Use Case: Develop a Personalized Recommendation System for an E-commerce Platfor

Lecture 14 Additional Resources

Lecture 15 Module 2. Artificial Intelligence and Agile Development - Presentation

Section 3: Module 3. Planning and Management of AI Projects

Lecture 16 Defining the Product Backlog for AI Projects

Lecture 17 Task Estimation and Prioritisation in AI Projects

Lecture 18 Sprints in AI Projects: Duration and Objectives

Lecture 19 Metrics and KPIs for AI Projects

Lecture 20 Use Case: Managing an AI Recommendation System Project Using Scrum

Lecture 21 Additional Resources

Lecture 22 Module 3. Planning and Management of AI Projects - Presentation

Section 4: Module 4. Implementing SCRUM in AI Projects

Lecture 23 Setting Up the Development Environment for AI

Lecture 24 Managing Data and Models in Sprints

Lecture 25 Continuous Integration and Continuous Deployment (CI/CD) for AI Models

Lecture 26 Managing Dependencies and Versions in AI Projects

Lecture 27 Use Case: AI Model Development for Customer Churn Prediction Using SCRUM

Lecture 28 Additional Resources

Lecture 29 Module 4. Implementing SCRUM in AI Projects - Presentation

Section 5: Module 5. Practical Case - Developing a Web Application with Generative AI

Lecture 30 Project Definition GPT-Based Text Generation App

Lecture 31 Configuring the Product Backlog

Lecture 32 Sprint Planning for the First Sprint

Lecture 33 Iterative Development Implementing the AI API

Lecture 34 Integration of AI with the Frontend

Lecture 35 Sprint Review and Retrospective

Lecture 36 Use Case: Generate Text Using Predefined Template

Lecture 37 Additional Resources

Lecture 38 Module 5. Practical Case - Developing a Web Application with Generative AI - Pre

Section 6: Module 6. Testing and Quality in AI Projects

Lecture 39 Testing Strategies for AI Models

Lecture 40 Validation and Verification of AI Results

Lecture 41 Bias Management and Ethics in AI

Lecture 42 Continuous Model Improvement During Sprints

Lecture 43 Case Study: Predicting Patient Readmission Rates in Healthcare

Lecture 44 Use Case: Bias Management and Ethical AI in Hiring Process at TechCompany

Lecture 45 Additional Resources

Lecture 46 Module 6. Testing and Quality in AI Projects - Presentation

Section 7: Module 7. Scalability and Maintenance

Lecture 47 AI Model Optimization

Lecture 48 Management of Computational Resources

Lecture 49 Monitoring and Logging of AI Systems

Lecture 50 Continuous Updates and Maintenance

Lecture 51 Use Case: Deploying an Optimized AI Model for Prod Recommendations in an E-comme

Lecture 52 Case Study: Implementing Monitoring, Logging, and Continuous Maintenance

Lecture 53 Additional Resources

Lecture 54 Module 7. Scalability and Maintenance - Presentation

Section 8: Module 8. Project Closure and Lessons Learned

Lecture 55 Final Evaluation of the AI Product

Lecture 56 Project Documentation

Lecture 57 Complete Project Retrospective

Lecture 58 Best Practices and Lessons Learned

Lecture 59 Use Case: Final AI Project Management Using SCRUM Methodology

Lecture 60 Additional Resources

Lecture 61 Module 8. Project Closure and Lessons Learned - Presentation

Section 9: Modulo 9. Final Project

Lecture 62 Final Project. Developing CreatiText AI Using SCRUM Methodology

Lecture 63 Final Project. Developing CreatiText AI Using SCRUM Methodology - Presentation

Section 10: Project Management Templates Starter Kit

Lecture 64 Templates

Software developers,Developers who want to learn about artificial intelligence,Python developers,Developers who want to learn about agile methodologies,People who want to get started in software development,People who want to get started in developing applications with artificial intelligence,People who want to get started in development using agile methodologies such as SCRUM