Data Science and Agile Systems for Product Management from edX

Modern systems today must be designed for agility in order to outpace the competition. Concepts like Agile, DevOps, and Data Science were once considered only for the technology-based companies. Today that means every company. Because there is no greater currency than timely information for optimizing operations and meeting the needs of customers.

Modern product management requires that every development and operations value stream is identified and continuously improved. This means using Lean and DevOps principles to streamline handoffs and information flows across teams. It means reorienting towards self-service and automation wherever possible. And to avoid incrementalism, it means a robust Agile development process to keep innovations important and aggressive enough to make noticeable improvements in value delivery.

Agile systems in a DevOps environment requires that products are built completely differently from a traditional designs. Modularity, open set architectures, and flexible data management paradigms are a starting point. The evolutionary nature of the product with so much change enables functionality, design, and technology to drive and influence each other simultaneously. And beneath it all is a data collection and feedback loop essential for anticipating and reacting to business needs both for operations and marketing.

Data science and analytics are the lifeblood of any product organization, and enable product managers to tackle risks early. Luckily, new technologies allow us to collect and integrate data without extreme upfront constraints and onerous controls. This means all data is fair game, and when tagged and stored properly, can be made available at nearly any scale for preparation, visualization, analysis, and modeling.

We’ll teach you the paradigms, processes, and introduce some key technologies that make the data-driven product organization the optimal competitor in the market.

What's inside

Learning objectives

Designing and modeling for fast feedback and idea sharing
System optimization with open architectures
Validating functions and verifying performance
Leveraging and enabling the system designs, platforms, and ecosystems

Lean startup and product innovation analytics
Developing the data collection and preparation pipeline for products and services
Analyzing the performance and testing hypotheses for usability, fast-feedback, and growth
Customer experience (cx) validation and enhancement leveraging usability analytics

Designing and modeling for fast feedback and idea sharing
System optimization with open architectures
Validating functions and verifying performance
Leveraging and enabling the system designs, platforms, and ecosystems
Lean startup and product innovation analytics
Developing the data collection and preparation pipeline for products and services
Analyzing the performance and testing hypotheses for usability, fast-feedback, and growth
Customer experience (cx) validation and enhancement leveraging usability analytics

Syllabus

Module 1: Agile Systems Engineering

Module 2: DevOps Principles for Business Agility

Module 3: Data Science for Product Risk Management

Module 4: Implementing Data-Driven Controls using Technology and Teams

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches principles and practices associated with DevOps, Lean, and Data Science

Suitable for product managers and software engineers

Emphasizes the importance of data collection and analysis for product development

Covers a wide range of topics, including product development, data science, and DevOps

Taught by experienced professionals in the field

Provides real-world examples and case studies

Reviews summary

Empowering product management with data and agile

Learners say this course is an excellent choice to strengthen product management skills by providing a thorough grounding in data science and agile systems. They caution that this course is intellectually rigorous but highly recommend it for those seeking a thorough, in-depth learning experience. Key topics covered include:

Learners remark on how well-structured the course content is, finding it simple to comprehend and follow.

""The course content was laid out in a very linear fashion, each lesson progressed either chronologically ... or scaffolding concepts.""

Many learners caution that this course is intellectually rigorous, but they walk away with a sense of accomplishment and a deep understanding of data science and agile in product management.

""Warning: This isn't a course that you can just click through and know the answers to. It's much more than that.""

""Overall, this is a great course for anyone looking to improve their data science skills and learn agile systems in product management. It's a great investment in professional development that will pay dividends for years to come.""

Students found the instructors to be knowledgeable and passionate, using their experience to make complex concepts more accessible.

""The instructors are knowledgeable and engaging, offering practical insights and industry-relevant examples that help students grasp the concepts easily.""

""The instructors demonstrated a deep understanding of the subject matter and a passion for sharing their knowledge""

Several students reference the practical applications in the course and how they contribute to understanding the true challenges and rewards of product management.

""The course also includes hands-on projects, which enable students to apply what they have learned in real-world scenarios.""

""Real-world case studies and practical exercises allowed me to apply theoretical concepts in a simulated environment""

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Science and Agile Systems for Product Management with these activities:

Review coding fundamentals

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Reinforce your understanding of basic coding concepts and techniques prior to the start of the course.

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Review basic algorithms and data structures
Practice writing code in a chosen programming language
Debug and test basic programs

Solve coding challenges on LeetCode

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Enhance your problem-solving skills and deepen your understanding of algorithms and data structures.

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Select a set of coding challenges on LeetCode
Work through the challenges, implementing solutions in your preferred language
Review your solutions and identify areas for improvement

Participate in a study group

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Engage with fellow students to discuss course concepts and enhance your understanding.

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Form a study group or join an existing one
Meet regularly to discuss lecture material and assignments
Work together on problem-solving exercises

Six other activities

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Explore tutorials on DevOps tools and practices

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Enhance your DevOps knowledge by exploring tutorials and practicing with industry-standard tools.

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Identify a reputable platform or resource for DevOps tutorials
Choose a tutorial that aligns with your learning goals
Follow the tutorial steps and implement the concepts
Experiment with the tools and techniques covered in the tutorial

Read 'Agile Principles, Patterns, and Practices'

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Expand your knowledge of Agile principles and best practices by reading this comprehensive book.

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Read the book's introduction and first chapter
Summarize the key concepts discussed in each chapter
Identify the principles that resonate with you and your team

Write a blog post on Agile methodologies

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Solidify your understanding by explaining Agile methodologies to a broader audience.

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Choose an aspect of Agile methodologies to focus on
Research the topic and gather relevant information
Write a clear and engaging blog post
Publish your blog post and promote it

Attend a workshop on data science for business

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Gain practical insights and expand your knowledge of data science applications in a business context.

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Identify a relevant workshop on data science for business
Register for and attend the workshop
Actively participate in the workshop activities

Develop a prototype for a data visualization tool

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Apply your understanding of data visualization techniques by creating a functional prototype.

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Identify the data you want to visualize
Choose appropriate visualization techniques
Develop the prototype using a suitable software
Present the prototype and get feedback

Contribute to an open-source project related to agile or devops

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Gain hands-on experience and contribute to the community by participating in an open-source project related to Agile or DevOps.

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Identify an open-source project that aligns with your interests
Review the project's documentation and codebase
Identify areas where you can contribute
Submit a pull request with your contributions

Career center

Learners who complete Data Science and Agile Systems for Product Management will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists help organizations make data-driven decisions that lead to improved products and services. To be successful in this role, a strong foundation in data science and analytics is essential. This course will help you develop the skills and knowledge you need to collect, prepare, analyze, and interpret data. You will also learn how to use data to make informed decisions and solve business problems.

See salaries and explore the career path for Data Scientist

Product Manager

Product Managers are responsible for the success of a product throughout its lifecycle. They work with engineers, designers, and marketers to develop and launch new products, and they continue to manage the product after it is released. To be successful in this role, you need a strong understanding of product development and marketing. This course will help you develop the skills and knowledge you need to be a successful Product Manager.

See salaries and explore the career path for Product Manager

Software Engineer

Software Engineers design, develop, and maintain software applications. To be successful in this role, you need a strong foundation in computer science and software engineering. This course will help you develop the skills and knowledge you need to be a successful Software Engineer.

See salaries and explore the career path for Software Engineer

Data Engineer

Data Engineers design, build, and maintain data pipelines. To be successful in this role, you need a strong foundation in computer science and data engineering. This course will help you develop the skills and knowledge you need to be a successful Data Engineer.

See salaries and explore the career path for Data Engineer

Business Analyst

Business Analysts help organizations improve their performance by analyzing data and identifying opportunities for improvement. To be successful in this role, you need a strong understanding of business analysis and data science. This course will help you develop the skills and knowledge you need to be a successful Business Analyst.

See salaries and explore the career path for Business Analyst

Quality Assurance Analyst

Quality Assurance Analysts test software applications to ensure that they meet the requirements of the business. To be successful in this role, you need a strong understanding of software testing and quality assurance. This course will help you develop the skills and knowledge you need to be a successful Quality Assurance Analyst.

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User Experience Designer

User Experience Designers design and develop user interfaces for software applications. To be successful in this role, you need a strong understanding of user experience design and human-computer interaction. This course will help you develop the skills and knowledge you need to be a successful User Experience Designer.

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DevOps Engineer

DevOps Engineers work to improve the collaboration between development and operations teams. To be successful in this role, you need a strong understanding of both development and operations. This course will help you develop the skills and knowledge you need to be a successful DevOps Engineer.

See salaries and explore the career path for DevOps Engineer

Scrum Master

Scrum Masters facilitate agile development teams. To be successful in this role, you need a strong understanding of agile methodologies and scrum. This course will help you develop the skills and knowledge you need to be a successful Scrum Master.

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Data Architect

Data Architects design and manage data systems. To be successful in this role, you need a strong understanding of data architecture and data management. This course will help you develop the skills and knowledge you need to be a successful Data Architect.

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Product Owner

Product Owners are responsible for the development and release of software products. To be successful in this role, you need a strong understanding of product development and agile methodologies. This course will help you develop the skills and knowledge you need to be a successful Product Owner.

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Business Intelligence Analyst

Business Intelligence Analysts use data to help organizations make better decisions. To be successful in this role, you need a strong understanding of business intelligence and data analysis. This course will help you develop the skills and knowledge you need to be a successful Business Intelligence Analyst.

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Data Analyst

Data Analysts use data to solve business problems. To be successful in this role, you need a strong understanding of data analysis and data mining. This course may help you develop the skills and knowledge you need to be a successful Data Analyst.

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Software Developer

Software Developers design, develop, and maintain software applications. To be successful in this role, you need a strong foundation in computer science and software development. This course may help you develop the skills and knowledge you need to be a successful Software Developer.

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IT Manager

IT Managers oversee the IT infrastructure of an organization. To be successful in this role, you need a strong understanding of IT management and technology. This course may help you develop the skills and knowledge you need to be a successful IT Manager.

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