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Fabiana Cherubim Bortoleto
The Data Science in Business course equips participants with the tools and techniques to leverage data for informed decision-making in the corporate world. Covering data analysis, and data-driven strategies, this course empowers individuals to extract valuable insights, enhance business processes, and drive strategic initiatives through data-driven approaches. Combining theoretical foundations with hands-on applications, learners will be well-prepared to navigate the intersection of data science and business analytics.
Register for this course and see more details by visiting:
OpenCourser.com/course/oser4s/data
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What's inside
Syllabus
Introduction to Data Analysis
This week, you’ll learn the impact of data analysis and its elements on business. Also, the diferences of variables, measurement scales and types of data analysis.
Read more
Syllabus
Introduction to Data Analysis
This week, you’ll learn the impact of data analysis and its elements on business. Also, the diferences of variables, measurement scales and types of data analysis.
Read more
Organizing and Visualizing Data
This week, you’ll learn how to tell something through data. Managing data in graphs and tables, and the principals pitfalls about data visualization.
Descriptive measures: univariate and bivariate
This week, you’ll learn how to deal with data and how to describe data in terms of some parameters: the differences between dispersion and central tendcy measures.
Statistical Inference
In this week you will see some probability principles which are linked with datasets and data visualization. Also, statistical principles which are applied in data analysis.
Regression Analysis
In this week you will see topics in linear regressions. Regression analysis is used to investigate the relationship between two or more variables. Often used in predicting some characteristic using one or more independent variables .
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Supports data science and analytics field growth in business
Builds a foundation in data analysis for business
Provides an overview of the intersection of business and data
Incorporates real-world examples into learning process
Enhances learners' data-driven decision-making skills
Covers foundational concepts in data analysis
Save this course
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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 Analysis for Business with these
activities:
Read 'Data Science for Business'
Show steps
Gain a comprehensive understanding of data science concepts and their application in business.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
-
Read the book thoroughly, taking notes and highlighting key concepts.
-
Complete the exercises and case studies at the end of each chapter.
-
Summarize the main takeaways from the book and how they relate to the course material.
Join a data science study group
Show steps
Connect with peers, discuss course material, and support each other's learning.
Show steps
-
Find or create a study group with other students enrolled in the course.
-
Meet regularly to discuss the course material and work on assignments together.
-
Collaborate on projects and share knowledge and resources.
Brush up on data visualization basics
Show steps
Solidify your understanding of data visualization concepts to prepare for the course's data analysis and visualization modules.
Browse courses on
Data Visualization
Show steps
-
Review the principles of data visualization, such as charts, graphs, and tables.
-
Identify the different types of data that can be visualized.
-
Practice creating basic data visualizations using tools like Excel or Google Sheets.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve data analysis problems
Show steps
Enhance your problem-solving abilities and apply data analysis techniques to real-world scenarios.
Browse courses on
Data Analysis
Show steps
-
Work through practice problems related to data cleaning, exploration, and analysis.
-
Analyze data sets to identify trends, patterns, and insights.
-
Present your findings and recommendations based on the data analysis.
Participate in data science workshops
Show steps
Gain hands-on experience and learn from experts in the field.
Show steps
-
Identify data science workshops that focus on topics relevant to your career goals.
-
Register and attend these workshops.
-
Actively participate in the workshops and ask questions.
Develop a data analysis portfolio
Show steps
Showcase your data analysis skills and build a portfolio of projects that demonstrate your expertise.
Show steps
-
Identify a business problem or question that can be addressed through data analysis.
-
Collect and clean relevant data from various sources.
-
Analyze the data using appropriate techniques and tools.
-
Present your findings and recommendations in a clear and concise manner.
Explore advanced data analysis techniques
Show steps
Expand your knowledge of data analysis by exploring advanced techniques and technologies.
Browse courses on
Big Data Analysis
Show steps
-
Identify advanced data analysis techniques that align with your career goals.
-
Find online tutorials or courses that cover these techniques.
-
Complete the tutorials and practice the techniques on real-world data sets.
Participate in data science competitions
Show steps
Test your skills, solve real-world problems, and network with professionals.
Show steps
-
Identify data science competitions that align with your interests and career goals.
-
Form a team or participate individually.
-
Analyze the competition data, develop models, and submit your solution.
Read 'Data Science for Business'
Show steps
Gain a comprehensive understanding of data science concepts and their application in business.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
Show steps
Show steps
- Read the book thoroughly, taking notes and highlighting key concepts.
- Complete the exercises and case studies at the end of each chapter.
- Summarize the main takeaways from the book and how they relate to the course material.
Join a data science study group
Show steps
Connect with peers, discuss course material, and support each other's learning.
Show steps
Show steps
Show steps
- Find or create a study group with other students enrolled in the course.
- Meet regularly to discuss the course material and work on assignments together.
- Collaborate on projects and share knowledge and resources.
Brush up on data visualization basics
Show steps
Solidify your understanding of data visualization concepts to prepare for the course's data analysis and visualization modules.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Review the principles of data visualization, such as charts, graphs, and tables.
- Identify the different types of data that can be visualized.
- Practice creating basic data visualizations using tools like Excel or Google Sheets.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve data analysis problems
Show steps
Enhance your problem-solving abilities and apply data analysis techniques to real-world scenarios.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Work through practice problems related to data cleaning, exploration, and analysis.
- Analyze data sets to identify trends, patterns, and insights.
- Present your findings and recommendations based on the data analysis.
Participate in data science workshops
Show steps
Gain hands-on experience and learn from experts in the field.
Show steps
Show steps
Show steps
- Identify data science workshops that focus on topics relevant to your career goals.
- Register and attend these workshops.
- Actively participate in the workshops and ask questions.
Develop a data analysis portfolio
Show steps
Showcase your data analysis skills and build a portfolio of projects that demonstrate your expertise.
Show steps
Show steps
Show steps
- Identify a business problem or question that can be addressed through data analysis.
- Collect and clean relevant data from various sources.
- Analyze the data using appropriate techniques and tools.
- Present your findings and recommendations in a clear and concise manner.
Explore advanced data analysis techniques
Show steps
Expand your knowledge of data analysis by exploring advanced techniques and technologies.
Browse courses on
Big Data Analysis
Show steps
Show steps
Show steps
- Identify advanced data analysis techniques that align with your career goals.
- Find online tutorials or courses that cover these techniques.
- Complete the tutorials and practice the techniques on real-world data sets.
Participate in data science competitions
Show steps
Test your skills, solve real-world problems, and network with professionals.
Show steps
Show steps
Show steps
- Identify data science competitions that align with your interests and career goals.
- Form a team or participate individually.
- Analyze the competition data, develop models, and submit your solution.
Career center
Learners who complete Data Analysis for Business will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts mine large datasets to unearth patterns and insights that can help businesses make better decisions. They use statistical and analytical techniques to identify trends, predict outcomes, and develop strategies. The Data Analysis for Business course from Fundação Instituto de Administração provides a strong foundation in these techniques, making it an excellent choice for aspiring Data Analysts. The course covers topics such as data visualization, descriptive statistics, statistical inference, and regression analysis, all of which are essential for success in this field.
Business Analyst
Business Analyst
Business Analysts use data to identify and solve business problems. They work with stakeholders to understand their needs, gather data, and develop recommendations. The Data Analysis for Business course from Fundação Instituto de Administração provides a valuable foundation for Business Analysts, as it teaches them how to collect, analyze, and interpret data in order to make sound business decisions.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand customer behavior and develop marketing campaigns. They track key metrics such as website traffic, conversion rates, and customer lifetime value. The Data Analysis for Business course from Fundação Instituto de Administração provides a valuable foundation for Marketing Analysts, as it teaches them how to collect, analyze, and interpret data in order to make effective marketing decisions.
Data Scientist
Data Scientist
Data Scientists use advanced statistical and machine learning techniques to extract insights from data. They work on a variety of projects, such as predicting customer behavior, developing new products, and improving business processes. The Data Analysis for Business course from Fundação Instituto de Administração provides a strong foundation in the fundamentals of data science, making it a good choice for aspiring Data Scientists. The course covers topics such as data visualization, statistical inference, and regression analysis, all of which are essential for success in this field.
Financial Analyst
Financial Analyst
Financial Analysts use data to evaluate the financial health of companies and make investment recommendations. They analyze financial statements, conduct industry research, and develop financial models. The Data Analysis for Business course from Fundação Instituto de Administração provides a valuable foundation for Financial Analysts, as it teaches them how to collect, analyze, and interpret data in order to make sound investment decisions.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency of business operations. They work on a variety of projects, such as optimizing supply chains, scheduling production, and improving customer service. The Data Analysis for Business course from Fundação Instituto de Administração provides a valuable foundation for Operations Research Analysts, as it teaches them how to collect, analyze, and interpret data in order to make operational improvements.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use data to develop mathematical models for financial markets. They work in investment banks, hedge funds, and other financial institutions. The Data Analysis for Business course from Fundação Instituto de Administração provides a valuable foundation for Quantitative Analysts, as it teaches them how to collect, analyze, and interpret data in order to develop and test financial models.
Statistician
Statistician
Statisticians use data to solve problems across a variety of industries. They design and conduct studies, analyze data, and interpret results. The Data Analysis for Business course from Fundação Instituto de Administração provides a valuable foundation for Statisticians, as it teaches them the fundamental principles of statistics and how to apply them to real-world problems.
Risk Analyst
Risk Analyst
Risk Analysts use data to identify and manage risks. They work in a variety of industries, such as banking, insurance, and healthcare. The Data Analysis for Business course from Fundação Instituto de Administração provides a valuable foundation for Risk Analysts, as it teaches them how to collect, analyze, and interpret data in order to make informed risk management decisions.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data systems. They work with data analysts, data scientists, and other stakeholders to ensure that data is available, reliable, and secure. The Data Analysis for Business course from Fundação Instituto de Administração provides a valuable foundation for Data Engineers, as it teaches them the principles of data management and how to build and maintain data systems.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. They work with data engineers, data analysts, and other stakeholders to ensure that data is available, reliable, and secure. The Data Analysis for Business course from Fundação Instituto de Administração may be useful for Database Administrators, as it provides a foundation in data management and data analysis. However, Database Administrators typically need an advanced degree in computer science or a related field.
Data Architect
Data Architect
Data Architects design and manage the architecture of data systems. They work with data engineers, data analysts, and other stakeholders to ensure that data systems meet the needs of the business. The Data Analysis for Business course from Fundação Instituto de Administração may be useful for Data Architects, as it provides a foundation in data management and data analysis. However, Data Architects typically need an advanced degree in computer science or a related field.
Web Developer
Web Developer
Web Developers design and develop websites and web applications. They work with data analysts, data scientists, and other stakeholders to ensure that websites and web applications meet the needs of the business. The Data Analysis for Business course from Fundação Instituto de Administração may be useful for Web Developers, as it provides a foundation in data analysis and data visualization. However, Web Developers typically need an advanced degree in computer science or a related field.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with data analysts, data scientists, and other stakeholders to ensure that software applications meet the needs of the business. The Data Analysis for Business course from Fundação Instituto de Administração may be useful for Software Engineers, as it provides a foundation in data analysis and data visualization. However, Software Engineers typically need an advanced degree in computer science or a related field.
IT Manager
IT Manager
IT Managers plan, implement, and manage IT systems and services. They work with data analysts, data scientists, and other stakeholders to ensure that IT systems and services meet the needs of the business. The Data Analysis for Business course from Fundação Instituto de Administração may be useful for IT Managers, as it provides a foundation in data analysis and data management. However, IT Managers typically need an advanced degree in computer science or a related field.
For more career information including salaries, visit:
OpenCourser.com/course/oser4s/data
Reading list
We've selected 12 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
Data Analysis for Business.
This textbook is specifically tailored for business students and professionals looking to learn data science. It covers everything from data wrangling and visualization to machine learning and predictive modeling. It also includes real-world case studies and exercises that make it easy to apply what you learn.
Comprehensive guide to using Python for data analysis. It covers everything from basic data manipulation to advanced statistical modeling. It also includes a number of helpful resources for learning Python, such as interactive exercises and code examples.
Save
Comprehensive guide to using R for data science. It covers everything from basic data manipulation to advanced statistical modeling. It also includes a number of helpful resources for learning R, such as interactive exercises and code examples.
Save
Practical guide to data visualization. It covers everything from choosing the right charts and graphs to designing effective dashboards. It also includes a number of helpful resources for creating visualizations, such as templates and code examples.
Save
Practical guide to using machine learning for business. It covers everything from the basics of machine learning to specific applications for business, such as predictive modeling and customer segmentation. It also includes a number of helpful resources for getting started with machine learning, such as code examples and case studies.
Gentle introduction to data analysis. It covers everything from the basics of data analysis to more advanced topics, such as statistical modeling and machine learning. It also includes a number of helpful resources for learning data analysis, such as practice problems and code examples.
Save
Comprehensive guide to statistics for business. It covers everything from descriptive statistics to inferential statistics. It also includes a number of helpful resources for learning statistics, such as practice problems and code examples.
Practical guide to using data science for business leaders. It covers everything from the basics of data science to specific applications for business, such as decision-making and risk management. It also includes a number of helpful resources for getting started with data science, such as case studies and examples.
Save
Provides a comprehensive overview of predictive analytics. It covers everything from the basics of predictive analytics to more advanced topics, such as machine learning and data mining. It also includes a number of helpful resources for learning predictive analytics, such as case studies and examples.
Provides a gentle introduction to data management. It covers everything from the basics of data management to more advanced topics, such as data governance and data security. It also includes a number of helpful resources for learning data management, such as practice problems and code examples.
Save
Gentle introduction to SQL. It covers everything from the basics of SQL to more advanced topics, such as data manipulation and data analysis. It also includes a number of helpful resources for learning SQL, such as practice problems and code examples.
Practical guide to using Python and R for data analysis. It covers everything from the basics of Python and R to more advanced topics, such as data visualization and machine learning. It also includes a number of helpful resources for learning Python and R, such as code examples and case studies.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/oser4s/data
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Effort
5 weeks
Level
Intermediate
Via
Coursera
Institution
Fundação Instituto de Administração
Instructor
Fabiana Cherubim Bortoleto
Language
English
This course belongs to a
collection
called
Data & Finance for the future. It's comprised of four courses:
- Data Analysis for Business (viewing)
- Valuation & Strategic Finance
- Financial Accounting
- Macroeconomics for Business Management
Good to know
Supports data science and analytics field growth in business
Builds a foundation in data analysis for business
Provides an overview of the intersection of business and data
Incorporates real-world examples into learning process
Enhances learners' data-driven decision-making skills
Covers foundational concepts in data analysis
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