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Digital Transformation with Data Analytics Projects

Every modern organization is a digital organization or will rapidly become digital. Artificial intelligence, Google/Amazon/Facebook/Uber, and big data have dramatically raised customer expectations and demand.

Organizations that are effective in using data will win in the economies of the mid-21st century. These must-have core competencies include data analysis, machine learning, data visualizations, data mining, and predictive analytics, and deep learning. Organizations that won't or can't digitally transform will go the way of Blockbuster or Border's Bookstore.

The organization that better harnesses the power of data to create a superior customer experience will thrive in the new business realities.

The question is, how does an organization digitally transform? There are many digital technologies for organizations to choose from - too many choices! And digital technologies are only part of creating a digital organization. The employees must be trained in the new technologies, leaders must learn how to use data in making strategic decisions, and the organization's business processes must be reinvented. So many choices to make and the stakes have never been higher!

This course will give you a framework to help you successfully navigate the challenges posed by digital transformation. First, we will discuss how to use the organization's dynamic capabilities to start the digital transformation. Second, we will use fitness landscapes to build a competitive digital business model. Finally, we will implement a strategic foresight function to help evolve the digital business model for the organization's continued success.

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What's inside

Syllabus

Week 1 Disciplined Agile Delivery

Week 2 Case Study : The New Start-Up

Week 3 Case Study: The Established Organization

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Introduces data analysis and predictive analytics, which are valuable for career growth in the modern economy

Provides instruction in data analysis, visualizations, and mining, enhancing employability in data-driven industries

Emphasizes the significance of data-driven decision-making and strategic foresight for organizational success in the digital age

Offers a comprehensive framework to guide digital transformation, encompassing dynamic capabilities, competitive business models, and strategic foresight

Taught by instructors with extensive experience in data analysis, machine learning, and digital transformation

Requires prior knowledge of data analysis and data visualization concepts, which may pose a barrier to some learners

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Reviews summary

Digital transformation strategy and frameworks

According to students, this course provides a strong strategic framework for understanding digital transformation, particularly beneficial for managers and business leaders. Learners appreciate the high-level overview and insightful case studies that connect theory to practical scenarios. However, a recurring caution for prospective students is the misleading course title. Many expected a more hands-on data analytics curriculum, finding the content primarily focused on business strategy. While highly relevant for those in strategic roles, it is not suited for learners seeking deep technical data skills.

Best suited for those in leadership or strategic roles.

"Perfect for my role as a project manager... highly recommend for managers."

"If you're looking for an executive-level view, this is it. Don't expect to become a data scientist."

"It's not a coding course, but it clearly articulates how data analytics fits into a larger business strategy."

Case studies effectively link theory to real-world applications.

"The case studies were particularly insightful and helped connect theory to practical scenarios."

"A good foundational course for understanding digital transformation challenges... The case studies were well-chosen and illustrative."

"The emphasis on frameworks and case studies made the concepts tangible."

Provides valuable frameworks and a high-level view of digital transformation.

"This course provided a fantastic high-level overview of digital transformation. The case studies were particularly insightful..."

"Excellent course for understanding the strategic aspects of digital transformation. The frameworks provided are highly valuable..."

"It's great for managers or consultants needing to understand the big picture of digital change."

Largely theoretical, lacking practical data application.

"I signed up hoping for hands-on data analytics projects, but the course was much more theoretical and strategic."

"The 'projects' were more like discussions than actual data analysis tasks."

"Very little practical application for anyone in a technical data role."

Title creates unmet expectations for technical data analytics.

"I signed up hoping for hands-on data analytics projects, but the course was much more theoretical and strategic."

"Disappointed. The title is misleading. 'Data Analytics Projects' implied something very different."

"Completely misleading title. If you want data analytics, look elsewhere. This is purely theoretical business strategy."

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 Digital Transformation with Data Analytics Projects with these activities:

Review the fundamentals of data analysis

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Reviewing the fundamentals of data analysis will help you understand the basic concepts and techniques that will be covered in this course.

Browse courses on Data Analysis

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Read through the course syllabus and identify the key concepts and techniques that will be covered.
Review your notes from previous data analysis courses or tutorials.
Complete some practice exercises or problems related to data analysis.

Participate in a study group

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Participating in a study group will allow you to collaborate with other students, learn from their perspectives, and clarify your understanding of the course material.

Browse courses on Collaboration

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Find a study group to join.
Attend study group meetings regularly.
Participate actively in discussions.

Follow a tutorial on machine learning algorithms

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Following a tutorial on machine learning algorithms will help you learn how to implement and use different machine learning algorithms in practice.

Browse courses on Machine Learning

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Find a tutorial on a specific machine learning algorithm that you are interested in.
Follow the steps in the tutorial to implement the algorithm.
Test the algorithm on a sample dataset.

Four other activities

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Complete practice exercises on data mining techniques

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Completing practice exercises on data mining techniques will help you develop your skills in extracting valuable insights from data.

Browse courses on Data Mining

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Find a set of practice exercises on data mining techniques.
Complete the exercises.
Review your answers and identify areas where you need improvement.

Volunteer with a data-driven organization

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Volunteering with a data-driven organization will allow you to apply your skills to a social cause while learning from professionals in the field.

Browse courses on Data Science

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Find a data-driven organization that you are interested in volunteering with.
Contact the organization and inquire about volunteering opportunities.
Attend a volunteer training program.
Work on data-related projects with the organization.

Create a data visualization

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Creating a data visualization will help you learn how to communicate data effectively and visually.

Browse courses on Data Visualization

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Choose a dataset that you are interested in.
Clean and prepare the data.
Choose an appropriate data visualization technique.
Create the visualization using a data visualization tool.

Participate in a data science competition

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Participating in a data science competition will challenge you to apply your skills to a real-world problem and learn from others in the field.

Browse courses on Data Science

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Find a data science competition that you are interested in.
Read the competition brief and understand the problem that you are trying to solve.
Build a model to solve the problem.
Submit your model to the competition.

Career center

Learners who complete Digital Transformation with Data Analytics Projects will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Digital Transformation with Data Analytics Projects.

The Grammar of Graphics

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Seminal work on the grammar of graphics, a formal language for describing data visualizations. It covers a wide range of topics, from the basics of the grammar of graphics to the use of the grammar of graphics to create a variety of charts and graphs.

The Grammar of Graphics (Statistics and Computing)

Hardcover

$$$$

The Grammar of Graphics (Statistics and Computing)...

Paperback Bunko

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