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Pinal Dave

Identifying and defining business challenges is crucial for developing data science solutions and aligning stakeholders. This course teaches you to recognize key problems that data science can address.

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Identifying and defining business challenges is crucial for developing data science solutions and aligning stakeholders. This course teaches you to recognize key problems that data science can address.

Diagnosing business challenges involves defining the problem, pinpointing its origins, assessing data science as a solution, shaping it into data objectives, and creating a focused, clear problem statement for stakeholder consensus.

In this course, Identifying and Understanding Business Problems for Data Scientists, you’ll gain the ability to effectively recognize, understand, and define business problems that can be addressed with data science.

First, you’ll explore how to uncover hidden business challenges through data trends and stakeholder engagement.

Next, you’ll discover the methods to apply data science to create impactful business solutions.

Finally, you’ll learn how to assess the readiness of a business problem for a data science approach and articulate it into clear, data-centric objectives.

When you’re finished with this course, you’ll have the skills and knowledge of business problem identification and analysis needed to confidently translate business issues into data science projects that deliver tangible results.

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Syllabus

Course Overview
Diagnosing Business Challenges
Strategizing Project Execution

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by experts in the field, Pinal Dave and his team
Explores industry-standard strategies for defining business challenges
Helps learners understand the full scope of data science, from theory to application
Covers essential concepts in data science, including data collection, analysis, and visualization
Requires learners to have a strong foundation in programming and statistics
May not be suitable for beginners with no prior experience in data science

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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 Identifying and Understanding Business Problems for Data Scientists with these activities:
Review concepts of data science and machine learning
Strengthen your foundational knowledge in data science and machine learning.
Browse courses on Data Science
Show steps
  • Revisit key concepts such as supervised and unsupervised learning
  • Review common algorithms and their applications
  • Practice implementing basic machine learning models
Review basic data analysis techniques
Brush up on data analysis techniques to strengthen your foundation for this course.
Browse courses on Data Analysis
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  • Revisit concepts of probability and statistics
  • Practice basic data visualization techniques
  • Review principles of data cleaning and preparation
Organize and review course materials
Stay organized and engaged by compiling and reviewing course materials.
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  • Gather all course materials, including notes, assignments, and readings
  • Create a system for organizing and storing the materials
  • Regularly review the materials to reinforce your understanding
Five other activities
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Show all eight activities
Attend industry events and meetups on data science
Connect with professionals in the field to expand your knowledge and explore career opportunities.
Browse courses on Data Science
Show steps
  • Identify relevant industry events and meetups
  • Attend the events and engage with attendees
  • Exchange ideas, learn about industry trends, and build your network
Solve case studies on business problem identification
Apply your understanding of business problem identification through practical case studies.
Show steps
  • Analyze real-world business scenarios
  • Identify key business challenges using data analysis techniques
  • Develop data-driven solutions to address the challenges
Explore online tutorials on advanced data science techniques
Acquire additional knowledge and skills in data science by engaging with online tutorials.
Browse courses on Data Science
Show steps
  • Identify specific areas you want to enhance your skills in
  • Search for reputable online tutorials and resources
  • Follow the tutorials and practice the techniques
Create a data-centric problem statement for a business challenge
Demonstrate your ability to articulate business problems clearly using data-centric language.
Show steps
  • Identify a specific business challenge
  • Gather data and analyze it to understand the problem
  • Formulate a clear and concise problem statement using data-driven evidence
Contribute to open-source data science projects
Gain practical experience and showcase your skills by contributing to real-world data science projects.
Browse courses on Data Science
Show steps
  • Identify open-source data science projects that align with your interests
  • Review the documentation and codebase
  • Identify areas where you can contribute and make pull requests

Career center

Learners who complete Identifying and Understanding Business Problems for Data Scientists will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists develop and maintain analytical models to extract knowledge from large data sets. Leveraging advanced tools and statistical techniques, they use data to solve complex problems and drive business decisions. This course can help build the skills needed to identify and understand the foundational business challenges that Data Scientists face. It also teaches ways to effectively frame business problems in the context of data science.
Data Analyst
Data Analysts combine domain knowledge and expertise with advanced statistical skills. They translate business needs into quantifiable metrics, using data to make objective recommendations and valuable insights. This "Identifying and Understanding Business Problems for Data Scientists" course can help teach data analysts how to effectively identify and define business problems that can be addressed with data science, which is foundational knowledge for this vital role.
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. They work with data scientists to develop models and with software engineers to integrate models into production systems. This "Identifying and Understanding Business Problems for Data Scientists" course can help lay a foundation for Machine Learning Engineers by teaching them how to recognize key problems that data science can address and how to assess the readiness of a business problem for a data science approach.
Data Engineer
Data Engineers build and maintain data pipelines and infrastructure. They work with data scientists and other engineers to ensure that data is available and usable for analysis. This course may be useful for Data Engineers interested in learning more about identifying and understanding business problems that data science can address.
Financial Analyst
Financial Analysts use financial data and models to make investment decisions and provide recommendations to clients. They need to understand business problems and how to use data to make sound financial decisions. This course can provide Financial Analysts with a foundation in identifying and understanding business problems.
Business Analyst
Business Analysts work closely with stakeholders to understand their business needs and challenges. They use analytical techniques to identify opportunities for improvement and develop solutions to drive business outcomes. The skills taught in this course on identifying and defining business problems, as well as aligning stakeholders, are critical for success in this role.
Market Researcher
Market Researchers gather and analyze data about markets and customers. They use this information to develop insights and make recommendations to help businesses make better decisions. This "Identifying and Understanding Business Problems for Data Scientists" course may help Market Researchers understand how to frame business problems in a way that data science can address.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to help solve complex business problems. They develop trading strategies, assess financial risk, and provide recommendations to businesses and investors. The skills taught in this course on identifying and understanding business problems, as well as assessing the readiness of a business problem for a data science approach, can be valuable to succeed in this role.
Business Intelligence Analyst
Business Intelligence Analysts use data to analyze business performance and identify trends. They provide insights to help businesses make better decisions. This course may be helpful for Business Intelligence Analysts to learn more about identifying and understanding business problems and how to translate them into data-centric objectives.
Product Manager
Product Managers are responsible for the overall vision and strategy of a product. They work with engineers, designers, and marketers to bring products to market and ensure they meet customer needs. This "Identifying and Understanding Business Problems for Data Scientists" course may be useful for Product Managers who want to learn more about applying data science techniques to solve business problems.
Data Architect
Data Architects design and manage data systems and infrastructure. They work closely with business stakeholders to understand data requirements and develop solutions that meet those needs. This course may be useful for Data Architects to learn how to better understand business problems and how to translate them into data-centric objectives.
Data Strategy and Governance Professional
Data Strategy and Governance Professionals develop and implement data strategies and policies. They work with business leaders to understand data needs and develop strategies to meet those needs. This course may be useful for Data Strategy and Governance Professionals to learn more about identifying and defining business problems that can be solved with data.
Actuary
Actuaries use mathematical and statistical techniques to assess and manage risk. They work in various industries, including insurance, finance, and healthcare. This course may be helpful for Actuaries interested in learning more about identifying and understanding business problems that can be addressed with data science.
Consultant
Consultants work with clients to solve business problems and improve performance. They use their expertise to identify opportunities for improvement and develop solutions. This course may be helpful for Consultants who want to learn more about identifying and understanding business problems.
Software Engineer
Software Engineers design, develop, test, and maintain software systems. They work with other engineers and stakeholders to understand requirements, develop solutions, and deliver high-quality software products. This course may be useful for Software Engineers, especially those working in data-driven organizations.

Reading list

We've selected seven 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 Identifying and Understanding Business Problems for Data Scientists.
Provides a comprehensive overview of machine learning for business intelligence. It covers topics such as machine learning algorithms, machine learning techniques, and machine learning applications.
Provides a practical guide to big data analytics for business professionals. It covers topics such as data collection, data storage, and data analysis.
Provides a comprehensive overview of data visualization for business intelligence. It covers topics such as data visualization techniques, data visualization tools, and data visualization best practices.
Provides a comprehensive overview of data mining for business analytics. It covers topics such as data collection, data preprocessing, and data mining techniques.
Provides a comprehensive overview of business intelligence. It covers topics such as data warehousing, data mining, and business analytics.
Provides a comprehensive overview of econometrics for business and economics. It covers topics such as regression analysis, time series analysis, and forecasting.

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