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.
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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.
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.
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.
What's inside
Syllabus
Week 1: The Digital Enterprise
Week 2: Dynamic Capabilities
Week 3: Fitness Landscapes
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Syllabus
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Activities
Review 'Big Data' by Viktor Mayer-Schönberger and Kenneth Cukier
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Build a stronger foundational understanding of data science concepts by independently reviewing the preeminent book on the subject.
View
Reinventing Capitalism in the Age of Big Data
on Amazon
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Read the book
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Summarize key concepts
-
Identify areas for further research
Join a Study Group for Data Analysis
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Enhance learning through collaborative discussions, knowledge sharing, and peer support, solidifying understanding and fostering critical thinking.
Browse courses on
Data Analysis
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Find a study group or start your own
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Meet regularly to discuss course material
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Work on group projects
Seek Mentorship from Industry Professionals
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Connect with experienced professionals in the field of data science to gain insights, guidance, and support, enhancing practical knowledge and career growth.
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Attend industry events
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Connect with professionals on LinkedIn
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Request informational interviews
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Follow Tutorials on Data Mining Techniques
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Develop proficiency in data mining techniques by following guided tutorials, gaining a deeper understanding of algorithms and their applications.
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Data Mining
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Identify relevant tutorials
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Follow the tutorials step-by-step
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Complete practice exercises
Complete Python Practice Drills on DataCamp
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Strengthen Python skills by applying them in practical exercises, leading to proficiency in data handling.
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Python
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Sign up for a DataCamp account
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Complete the Python Data Analysis with Pandas course
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Practice regularly
Attend Workshops on Machine Learning
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Enhance understanding of machine learning algorithms and techniques through interactive workshops, fostering practical knowledge and hands-on experience.
Browse courses on
Machine Learning
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Identify relevant workshops
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Register and attend workshops
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Participate actively in hands-on activities
Volunteer at a Data Science Hackathon
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Gain hands-on experience in a collaborative environment, contribute to real-world projects, and build teamwork and problem-solving skills.
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Identify hackathons in your area
-
Register and join a team
-
Participate in the hackathon
Create a Data Visualization Dashboard
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Build practical skills in data visualization by creating an interactive dashboard, reinforcing data analysis and presentation techniques.
Browse courses on
Data Visualization
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-
Choose a dataset
-
Design the dashboard
-
Develop the dashboard using Tableau or Power BI
-
Present the dashboard
Review 'Big Data' by Viktor Mayer-Schönberger and Kenneth Cukier
Show steps
Build a stronger foundational understanding of data science concepts by independently reviewing the preeminent book on the subject.
View
Reinventing Capitalism in the Age of Big Data
on Amazon
Show steps
- Read the book
- Summarize key concepts
- Identify areas for further research
Join a Study Group for Data Analysis
Show steps
Enhance learning through collaborative discussions, knowledge sharing, and peer support, solidifying understanding and fostering critical thinking.
Browse courses on
Data Analysis
Show steps
- Find a study group or start your own
- Meet regularly to discuss course material
- Work on group projects
Seek Mentorship from Industry Professionals
Show steps
Connect with experienced professionals in the field of data science to gain insights, guidance, and support, enhancing practical knowledge and career growth.
Show steps
- Attend industry events
- Connect with professionals on LinkedIn
- Request informational interviews
Follow Tutorials on Data Mining Techniques
Show steps
Develop proficiency in data mining techniques by following guided tutorials, gaining a deeper understanding of algorithms and their applications.
Browse courses on
Data Mining
Show steps
- Identify relevant tutorials
- Follow the tutorials step-by-step
- Complete practice exercises
Complete Python Practice Drills on DataCamp
Show steps
Strengthen Python skills by applying them in practical exercises, leading to proficiency in data handling.
Browse courses on
Python
Show steps
- Sign up for a DataCamp account
- Complete the Python Data Analysis with Pandas course
- Practice regularly
Attend Workshops on Machine Learning
Show steps
Enhance understanding of machine learning algorithms and techniques through interactive workshops, fostering practical knowledge and hands-on experience.
Browse courses on
Machine Learning
Show steps
- Identify relevant workshops
- Register and attend workshops
- Participate actively in hands-on activities
Volunteer at a Data Science Hackathon
Show steps
Gain hands-on experience in a collaborative environment, contribute to real-world projects, and build teamwork and problem-solving skills.
Show steps
- Identify hackathons in your area
- Register and join a team
- Participate in the hackathon
Create a Data Visualization Dashboard
Show steps
Build practical skills in data visualization by creating an interactive dashboard, reinforcing data analysis and presentation techniques.
Browse courses on
Data Visualization
Show steps
- Choose a dataset
- Design the dashboard
- Develop the dashboard using Tableau or Power BI
- Present the dashboard
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