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.
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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.
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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Syllabus
Week 1 Disciplined Agile Delivery
Week 2 Case Study : The New Start-Up
Week 3 Case Study: The Established Organization
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Syllabus
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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.
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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.
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Collaboration
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Find a study group to join.
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Attend study group meetings regularly.
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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.
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Machine Learning
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Find a tutorial on a specific machine learning algorithm that you are interested in.
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Follow the steps in the tutorial to implement the algorithm.
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Test the algorithm on a sample dataset.
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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.
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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.
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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.
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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.
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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
Show steps
-
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.
Review the fundamentals of data analysis
Show steps
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
Show steps
- 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
Show steps
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
Show steps
- Find a study group to join.
- Attend study group meetings regularly.
- Participate actively in discussions.
Follow a tutorial on machine learning algorithms
Show steps
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
Show steps
- 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.
Complete practice exercises on data mining techniques
Show steps
Completing practice exercises on data mining techniques will help you develop your skills in extracting valuable insights from data.
Browse courses on
Data Mining
Show steps
- 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
Show steps
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
Show steps
- 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
Show steps
Creating a data visualization will help you learn how to communicate data effectively and visually.
Browse courses on
Data Visualization
Show steps
- 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
Show steps
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
Show steps
- 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.
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