We may earn an affiliate commission when you visit our partners.
This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.
Register for this course and see more details by visiting:
OpenCourser.com/course/pphd0r/predictive
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches the use of data analytics for business and management professionals in their daily work
Provides a foundation for applying data analytics to real-world business challenges
Helps identify appropriate analytic tools for specific business needs
Focuses on the ethical and responsible use of data in decision-making
Prepares learners to analyze and visualize data effectively
Save this course
Save Predictive Analytics and Data Mining to your list so you can find it easily later:
Save
Save
Reviews summary
Data analytics for business
This course focuses on providing a solid foundation in data analytics. It is well-received by students, who praise the detailed explanations, clear communication, and relevance to real-world business challenges. However, some students have expressed concerns about outdated course materials, vague instructions, and lack of support on discussion forums.
Detailed and well-explained concepts
"Very detailed and well explained, good experience!"
"Professor Seshadri excels at communicating complex concepts and his presentation style works well in remote channels."
Limited response on discussion forums
"I don't think anyone other than students ever checks them, which is not good - one of the reasons I had to transfer to another class was because of the lack of response on the discussion forums."
Unclear instructions in assignments
"The use of Rattle is unclear. WEKA is a very similar environment with a more intuitive UI. Additionally the instructions provided in assignments are also vague and unclear, leaving a lot to student guesswork."
Outdated course package and software issues
"Without updating the course package, the package necessary for the class is no longer available, so the course cannot be continued."
"Outdated material, very difficult to install the required software for the assignments (rattle), slides with lots of texts, unable to get reviews for the certification."
Focus on selected methods, not all relevant algorithms covered
"Not all algorithms that are relevant for the subject are covered, there is not enough time for that."
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 Predictive Analytics and Data Mining with these
activities:
Brush up on foundational math skills
Show steps
Ensure foundational understanding of math concepts, particularly statistics and probability, which are essential for this course.
Browse courses on
Statistics
Show steps
-
Review key concepts of statistics
-
Practice solving probability problems
-
Complete sample problems and exercises
Review Data Analytics for Business Professionals by Randy Bartlett
Show steps
Review the foundational concepts of data analytics for businesses, particularly those that will be covered in this course.
Show steps
-
Read Chapters 1-3 of the text
-
Summarize the key concepts of each chapter
-
Complete the review questions at the end of each chapter
Complete online quizzes and exercises
Show steps
Reinforce your understanding of the course material through interactive exercises.
Show steps
-
Access the online quizzes and exercises provided by the instructor
-
Complete the quizzes and exercises regularly
-
Review your results and identify areas for improvement
Four other activities
Expand to see all activities and additional details
Show all seven activities
Develop a data collection plan for a real-world business problem
Show steps
Create a plan to collect and analyze data, which is a key component of business analytics.
Browse courses on
Data Collection
Show steps
-
Identify a specific business problem
-
Determine the data needed to solve the problem
-
Develop a strategy for collecting the data
-
Create a plan for analyzing the data
-
Present your plan to a group for feedback
Complete practice problems on data analysis techniques
Show steps
Reinforce data analysis techniques and concepts through practice.
Browse courses on
Data Analysis
Show steps
-
Find practice problems online or in textbooks
-
Work through the problems step-by-step
-
Check your answers and identify areas for improvement
Collaborate with peers on a data analysis project
Show steps
Enhance problem-solving skills and teamwork in the context of a business analytics project.
Browse courses on
Data Analysis
Show steps
-
Divide the work among the group members
-
Form a study group with 2-3 peers
-
Choose a data analysis project to work on
-
Meet regularly to discuss progress and troubleshoot
-
Present your findings to the class
Contribute to an open-source data analysis project
Show steps
Gain hands-on experience in practical data analysis and contribute to the open-source community.
Browse courses on
Data Analysis
Show steps
-
Find an open-source data analysis project on GitHub
-
Review the project documentation and code
-
Identify an area where you can contribute
-
Make a pull request with your changes
-
Work with the project maintainers to incorporate your changes
Brush up on foundational math skills
Show steps
Ensure foundational understanding of math concepts, particularly statistics and probability, which are essential for this course.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Review key concepts of statistics
- Practice solving probability problems
- Complete sample problems and exercises
Review Data Analytics for Business Professionals by Randy Bartlett
Show steps
Review the foundational concepts of data analytics for businesses, particularly those that will be covered in this course.
Show steps
Show steps
Show steps
- Read Chapters 1-3 of the text
- Summarize the key concepts of each chapter
- Complete the review questions at the end of each chapter
Complete online quizzes and exercises
Show steps
Reinforce your understanding of the course material through interactive exercises.
Show steps
Show steps
Show steps
- Access the online quizzes and exercises provided by the instructor
- Complete the quizzes and exercises regularly
- Review your results and identify areas for improvement
Four other activities
Expand to see all activities and additional details
Show all seven activities
Develop a data collection plan for a real-world business problem
Show steps
Create a plan to collect and analyze data, which is a key component of business analytics.
Browse courses on
Data Collection
Show steps
Show steps
Show steps
- Identify a specific business problem
- Determine the data needed to solve the problem
- Develop a strategy for collecting the data
- Create a plan for analyzing the data
- Present your plan to a group for feedback
Complete practice problems on data analysis techniques
Show steps
Reinforce data analysis techniques and concepts through practice.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Find practice problems online or in textbooks
- Work through the problems step-by-step
- Check your answers and identify areas for improvement
Collaborate with peers on a data analysis project
Show steps
Enhance problem-solving skills and teamwork in the context of a business analytics project.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Divide the work among the group members
- Form a study group with 2-3 peers
- Choose a data analysis project to work on
- Meet regularly to discuss progress and troubleshoot
- Present your findings to the class
Contribute to an open-source data analysis project
Show steps
Gain hands-on experience in practical data analysis and contribute to the open-source community.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Find an open-source data analysis project on GitHub
- Review the project documentation and code
- Identify an area where you can contribute
- Make a pull request with your changes
- Work with the project maintainers to incorporate your changes
Career center
Learners who complete Predictive Analytics and Data Mining will develop knowledge and skills
that may be useful to these careers:
Data Mining Engineer
Data Mining Engineer
Data Mining Engineers specialize in extracting valuable insights from large datasets using advanced data mining techniques. This course on Predictive Analytics and Data Mining aligns directly with the responsibilities of a Data Mining Engineer, covering both theoretical and practical aspects of data mining, including data exploration, pattern recognition, and predictive modeling. Completing this course will provide you with the necessary skills to excel in this specialized field.
Data Scientist
Data Scientist
Data Scientists are at the forefront of data-driven innovation, using advanced statistical and computational techniques to extract knowledge from vast amounts of data. This course on Predictive Analytics and Data Mining provides a valuable foundation for aspiring Data Scientists, covering fundamental concepts in data mining, predictive modeling, and data visualization. By mastering the skills taught in this course, you will be well-equipped to make significant contributions to the field of data science.
Data Analyst
Data Analyst
Data Analysts play a pivotal role in the business world, extracting valuable insights from raw data to help organizations make informed decisions. This course on Predictive Analytics and Data Mining provides a solid foundation for aspiring Data Analysts, covering essential data collection, analysis, visualization, and decision-making techniques. Understanding the concepts taught in this course will empower you to succeed in this in-demand field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve complex business problems. This course on Predictive Analytics and Data Mining complements the skillset required for Machine Learning Engineers, providing a solid understanding of data preprocessing, feature engineering, and model evaluation techniques. The knowledge gained from this course will enhance your ability to build and implement effective machine learning solutions.
Decision Scientist
Decision Scientist
Decision Scientists use data analysis and modeling techniques to inform and improve decision-making. This course on Predictive Analytics and Data Mining provides a solid foundation for Decision Scientists, covering essential data analysis and modeling concepts, as well as techniques for evaluating and communicating decision outcomes. The knowledge gained from this course will empower you to make significant contributions to the field of decision science.
Business Analyst
Business Analyst
Business Analysts bridge the gap between technical and business domains, helping organizations leverage data to improve processes and achieve strategic goals. This course on Predictive Analytics and Data Mining aligns well with the skillset required for Business Analysts, providing a deep understanding of data analysis methodologies and their application in real-world business scenarios. Completing this course will enhance your ability to identify opportunities for data-driven decision-making.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data analysis and visualization techniques to provide insights that drive informed business decisions. This course on Predictive Analytics and Data Mining provides a valuable foundation for Business Intelligence Analysts, covering essential data analysis and visualization concepts, as well as techniques for identifying trends and patterns in data. The knowledge gained from this course will empower you to make significant contributions to the business intelligence field.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data to gain insights and inform decision-making. This course on Predictive Analytics and Data Mining provides a solid foundation for aspiring Statisticians, covering fundamental statistical principles and methodologies. By completing this course, you will enhance your ability to conduct rigorous statistical analyses and communicate your findings effectively.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure to support data analysis and modeling. This course on Predictive Analytics and Data Mining may be useful for Data Engineers who seek to enhance their understanding of data analysis techniques and gain a deeper appreciation for the role of data in decision-making.
Data Architect
Data Architect
Data Architects design and manage data systems and infrastructure to meet the needs of an organization. This course on Predictive Analytics and Data Mining may be useful for Data Architects who seek to enhance their understanding of data analysis techniques and gain a deeper appreciation for the role of data in decision-making.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to improve the efficiency and effectiveness of business processes. This course on Predictive Analytics and Data Mining may be useful for Operations Research Analysts who seek to enhance their data analysis and modeling skills. The course covers techniques for data collection, analysis, and visualization, as well as optimization techniques, which can be valuable in operations research.
Market Research Analyst
Market Research Analyst
Market Research Analysts conduct research to understand market trends, customer behavior, and industry dynamics. This course on Predictive Analytics and Data Mining may be useful for Market Research Analysts who seek to enhance their analytical skills and gain a deeper understanding of data-driven decision-making. The course covers techniques for data collection, analysis, and visualization, which can be valuable in conducting market research studies.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and manage risks within organizations. This course on Predictive Analytics and Data Mining may be useful for Risk Analysts who seek to enhance their analytical skills and gain a deeper understanding of data-driven decision-making. The course covers techniques for data collection, analysis, and visualization, which can be valuable in risk management.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess and manage financial risks. This course on Predictive Analytics and Data Mining may be useful for Actuaries who seek to enhance their analytical skills and gain a deeper understanding of data-driven decision-making. The course covers techniques for data collection, analysis, and visualization, which can be valuable in actuarial work.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical modeling to assess financial risks and make investment decisions. While this course on Predictive Analytics and Data Mining does not directly focus on financial applications, it provides a solid foundation in data analysis and modeling techniques that may be useful for Quantitative Analysts seeking to expand their skillset.
For more career information including salaries, visit:
OpenCourser.com/course/pphd0r/predictive
Reading list
We've selected 13 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
Predictive Analytics and Data Mining.
Save
Provides a comprehensive overview of predictive analytics, including its history, development, and applications. It valuable resource for students who want to learn more about the field and its potential.
Save
Classic textbook on data mining. It covers all the major concepts and techniques in the field, and it valuable resource for students who want to learn more about data mining.
Practical guide to using Python for data analysis. It covers all the major topics in the field, and it valuable resource for students who want to learn how to use Python to analyze data.
Save
Practical guide to using R for data science. It covers all the major topics in the field, and it valuable resource for students who want to learn how to use R to analyze data.
Save
Practical guide to using Tableau for data analysis. It covers all the major topics in the field, and it valuable resource for students who want to learn how to use Tableau to visualize data.
Save
Practical guide to using Power BI for data analysis. It covers all the major topics in the field, and it valuable resource for students who want to learn how to use Power BI to visualize data.
Save
Practical guide to data visualization. It covers all the major topics in the field, and it valuable resource for students who want to learn more about how to visualize data.
Classic textbook on information visualization. It covers all the major topics in the field, and it valuable resource for students who want to learn more about how to visualize data.
Save
Practical guide to data science. It covers all the major topics in the field, and it valuable resource for students who want to learn more about how to use data science to solve real-world problems.
Save
Practical guide to big data. It covers all the major topics in the field, and it valuable resource for students who want to learn more about how to use big data to solve real-world problems.
Classic textbook on Hadoop. It covers all the major topics in the field, and it valuable resource for students who want to learn more about how to use Hadoop to analyze data.
Classic textbook on Spark. It covers all the major topics in the field, and it valuable resource for students who want to learn more about how to use Spark to analyze data.
Practical guide to using Python for deep learning. It covers all the major topics in the field, and it valuable resource for students who want to learn more about how to use Python to solve real-world problems.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/pphd0r/predictive
Share
Similar courses
Here are nine courses similar to
Predictive Analytics and Data Mining.
Data Analytics for Business
OpenCourser.com/course/35qgnn/data
Data Analytics for Business
Introduction to Business Analytics: Communicating with Data
OpenCourser.com/course/sajd2y/introduction
Introduction to Business Analytics: Communicating with...
Machine Learning for Accounting with Python
OpenCourser.com/course/lnusql/machine
Machine Learning for Accounting with Python
Distributed Computing with Spark SQL
OpenCourser.com/course/e8ru2j/distributed
Distributed Computing with Spark SQL
The Power of Data in Health and Social Care
OpenCourser.com/course/79m2td/the
The Power of Data in Health and Social Care
Foundations of strategic business analytics
OpenCourser.com/course/nyaqrh/foundations
Foundations of strategic business analytics
Mastering Amazon Redshift Development & Administration
OpenCourser.com/course/1yulmm/mastering
Mastering Amazon Redshift Development & Administration
Introduction to Data Analytics
OpenCourser.com/course/7owxen/introduction
Introduction to Data Analytics
Advanced Analytics and Ethics in Business Analytics
OpenCourser.com/course/9d79ab/advanced
Advanced Analytics and Ethics in Business Analytics
Time
25 hours
Via
Coursera
Institution
University of Illinois at Urbana-Champaign
Good to know
Teaches the use of data analytics for business and management professionals in their daily work
Provides a foundation for applying data analytics to real-world business challenges
Helps identify appropriate analytic tools for specific business needs
Focuses on the ethical and responsible use of data in decision-making
Prepares learners to analyze and visualize data effectively
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser