Data Science for Business Innovation from Coursera

This is your chance to learn all about Data Science for Business innovation and future-proof your career. Match your business experience tech and analytics!

The Data Science for Business Innovation nano-course is a compendium of the must-have expertise in data science for executives and managers to foster data-driven innovation. The course explains what Data Science is and why it is so hyped.

You will learn:

* the value that Data Science can create

* the main classes of problems that Data Science can solve

* the difference is between descriptive, predictive, and prescriptive analytics

* the roles of machine learning and artificial intelligence.

From a more technical perspective, the course covers supervised, unsupervised and semi-supervised methods, and explains what can be obtained with classification, clustering, and regression techniques. It discusses the role of NoSQL data models and technologies, and the role and impact of scalable cloud-based computation platforms. All topics are covered with example-based lectures, discussing use cases, success stories, and realistic examples.

Following this nano-course, if you wish to further deepen your data science knowledge, you can attend the Data Science for Business Innovation live course https://professionalschool.eitdigital.eu/data-science-for-business-innovation

What's inside

Syllabus

Introduction to Data-driven Business

This module introduces the course and offers some basic overview of the topics. It presents the crucial concepts related to data science and big data and provides an outlook on how to use them in real world settings for increasing business value.

Terminology and Foundational Concepts

In this module, you will learn the foundational concepts of machine learning and data science. You will understand how these techniques can be useful in terms of increased business value for organizations, thanks to the discussion of a very well known success story, namely Netflix, which can be deemed as a completely data-driven business. You will also understand how machine learning is different from programming.

Data Science Methods for Business

In this module, you will learn the concepts and intuitions about the basic approaches for data analysis, including linear regression, naive Bayes, decision trees, clustering, and logistic regression. All the methods are presented starting from typical business uses and are covered in an intuitive way through a guided explanation of how the approach works on simple examples.

Challenges and Conclusions

This module summarizes the concepts learned so far and introduces a set of challenges and risks that data-savvy managers must take into account when deciding for a data-driven strategy.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches how data science can increase business value through real-world examples

Explores the foundational concepts of machine learning and data science

Covers supervised, unsupervised and semi-supervised machine learning methods

Suitable for executives and managers with an interest in data-driven innovation

Introduces the concept of data-driven business and its benefits

Requires no prior knowledge of data science or machine learning

Reviews summary

Well-regarded data science course

Learners say that the "Data Science for Business Innovation" course is an excellent course that is well-suited for beginners and those in business who want to learn about data science. The course is well-structured, organized, and the materials are easy to understand. The course covers a wide range of topics, including algorithms, statistics, and machine learning. The course uses real-world examples to illustrate the concepts and the quizzes at the end of each module are helpful for reinforcing the learning. There are, however, some negative reviews that point out inconsistencies in the course delivery and a lack of business innovation content.

Helpful for reinforcing learning

"The quiz questions are tricky which makes it really interesting"

Concepts are explained clearly

"With a simple example the tutor explains the concept."

Uses real-world examples for context

"Nice quick introduction to the world of data science. I would try to improve the questions of the quizzes, which are sometimes really badly written."

Well-structured and easy to follow

"The structure and delivery of the learning materials is well designed."

Excellent quality content

"Informative, well-detailed, organized and excellent."

Some inconsistencies in delivery

"This course was poorly designed and felt like it was "bolted together" by several authors."

Course lacks content on business innovation

"Very misleading title for the course. It doesn't talk about innovation anywhere in the course."

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 for Business Innovation with these activities:

Refresh Statistics Fundamentals

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Having a strong grasp of basic statistics will enable you to understand concepts like descriptive, predictive, and prescriptive analytics from the course.

Browse courses on Descriptive Statistics

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Review your lecture notes or textbook from a previous statistics course.
Enroll in a free online course or watch videos to refresh your memory.
Take practice quizzes or mock exams to test your understanding.

Read 'Data Science for Business'

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This book provides a comprehensive overview of data science concepts and their applications in business, complementing the course content.

View Data Science for Business: What You Need to... on Amazon

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Read chapters that align with course topics.
Summarize key concepts and make notes.

Explore Cloud-Based Computation Platforms

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Familiarizing yourself with cloud-based platforms will enable you to leverage their scalable capabilities for data processing and analysis.

Browse courses on AWS

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Sign up for free trials or use online tutorials.
Create a virtual machine or instance.
Deploy a simple data analysis application.

Five other activities

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Practice Data Analysis Techniques

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Regular practice of data analysis techniques will improve your proficiency and confidence in applying them to real-world problems.

Browse courses on Machine Learning

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Enroll in online platforms or courses that offer practice problems.
Work through guided tutorials or exercises to gain hands-on experience.
Participate in online forums or discussion groups to ask questions and share insights.

Join a Study or Discussion Group

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Engaging in peer discussions and collaborating with others can enhance your understanding of course concepts and provide different perspectives.

Browse courses on Data Science

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Find a group or create one with classmates or online.
Set regular meeting times to discuss course material.
Share notes, ask questions, and engage in collaborative problem-solving.

Build a Data Visualization Dashboard

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Hands-on experience in creating data visualizations will enhance your understanding of how data can be presented effectively for decision-making.

Browse courses on Data Visualization

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Choose a dataset that interests you.
Select a data visualization tool (e.g., Tableau, Power BI).
Design and create interactive visualizations.
Share your dashboard with others and gather feedback.

Develop a Data-Driven Business Case

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Creating a business case will help you understand how data science can be applied to real-world business problems and justify its value to stakeholders.

Browse courses on Data-Driven Decision Making

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Identify a business problem or opportunity that data can address.
Gather data and analyze it to identify insights and potential solutions.
Develop a data-driven recommendation and justify its benefits.
Present your business case to stakeholders and seek feedback.

Contribute to Open-Source Data Science Projects

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Participating in open-source projects will provide hands-on experience with real-world data science applications and contribute to the community.

Browse courses on Data Science

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Identify open-source projects on platforms like GitHub.
Review documentation and contribute bug fixes or improvements.
Discuss and collaborate with project maintainers.

Career center

Learners who complete Data Science for Business Innovation will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course provides a comprehensive overview of data science, covering topics such as machine learning, artificial intelligence, and big data. By taking this course, you can gain the skills and knowledge necessary to pursue a successful career as a Data Scientist.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts model data, collect data, and interpret and communicate data insights to help organizations make data-driven decisions. This course teaches the fundamentals of data science, providing a strong foundation for a career as a Data Analyst. The course covers topics such as supervised and unsupervised learning, data mining, and data visualization, all of which are essential skills for success in this field.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models to solve real-world problems. This course provides a solid foundation in machine learning, covering topics such as supervised and unsupervised learning, model evaluation, and deployment. By completing this course, you will gain the skills and knowledge needed to become a successful Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Architect

Data Architects design and manage data systems and infrastructure. This course provides a comprehensive overview of data science, covering topics such as data management, data warehousing, and big data. By completing this course, you can gain the skills and knowledge needed to become a successful Data Architect.

See salaries and explore the career path for Data Architect

Data Engineer

Data Engineers design, build, and maintain data pipelines and infrastructure. This course provides a solid foundation in data science, covering topics such as data management, data warehousing, and big data. By taking this course, you can gain the skills and knowledge needed to become a successful Data Engineer.

See salaries and explore the career path for Data Engineer

Business Analyst

Business Analysts analyze business processes, identify pain points, and provide recommendations for improvement. This course provides a comprehensive overview of data science for business, covering topics such as data analysis, data visualization, and data-driven decision-making. By taking this course, you can gain the skills and knowledge needed to excel as a Business Analyst.

See salaries and explore the career path for Business Analyst

Product Manager

Product Managers are responsible for the development and launch of new products. This course provides a solid foundation in data science for business, covering topics such as data analysis, data visualization, and data-driven decision-making. By taking this course, you can gain the skills and knowledge needed to become a successful Product Manager.

See salaries and explore the career path for Product Manager

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. This course provides a solid foundation in data science, covering topics such as statistical modeling, data analysis, and data visualization. By taking this course, you can gain the skills and knowledge needed to become a successful Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Business Intelligence Analyst

Business Intelligence Analysts use data to identify trends and patterns to help businesses make better decisions. This course provides a solid foundation in data science for business, covering topics such as data analysis, data visualization, and data-driven decision-making. By taking this course, you can gain the skills and knowledge needed to become a successful Business Intelligence Analyst.

See salaries and explore the career path for Business Intelligence Analyst

Statistician

Statisticians collect, analyze, interpret, and present data. This course provides a strong foundation in data science, covering topics such as statistical modeling, data analysis, and data visualization. By taking this course, you can gain the skills and knowledge needed to become a successful Statistician.

See salaries and explore the career path for Statistician

Management Consultant

Management Consultants help organizations solve business problems and improve performance. This course provides a comprehensive overview of data science for business, covering topics such as data analysis, data visualization, and data-driven decision-making. By completing this course, you can gain the skills and knowledge needed to become a successful Management Consultant.

See salaries and explore the career path for Management Consultant

Market Research Analyst

Market Research Analysts collect, analyze, and interpret data to understand consumer behavior and trends. This course provides a comprehensive overview of data science for business, covering topics such as data analysis, data visualization, and data-driven decision-making. By taking this course, you can gain the skills and knowledge needed to become a successful Market Research Analyst.

See salaries and explore the career path for Market Research Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. This course provides a comprehensive overview of data science for business, covering topics such as data analysis, data visualization, and data-driven decision-making. By completing this course, you can gain the skills and knowledge needed to become a successful Operations Research Analyst.

See salaries and explore the career path for Operations Research Analyst

Financial Analyst

Financial Analysts analyze financial data to make investment recommendations. This course provides a solid foundation in data science for business, covering topics such as data analysis, data visualization, and data-driven decision-making. By taking this course, you can gain the skills and knowledge needed to become a successful Financial Analyst.

See salaries and explore the career path for Financial Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. This course provides a solid foundation in data science, covering topics such as machine learning, artificial intelligence, and big data. By taking this course, you can gain the skills and knowledge needed to become a successful Software Engineer.

See salaries and explore the career path for Software Engineer