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Anand Saravanan

This course will teach you how to create an exploratory data analysis research plan to get started on the path to making the best data-driven decisions for your company.

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This course will teach you how to create an exploratory data analysis research plan to get started on the path to making the best data-driven decisions for your company.

In today’s data-driven world, businesses are looking to make the most effective decisions backed by data. In this course, Designing and Executing an Exploratory Data Analysis Research Plan, you’ll gain the ability to create research reports to present to business executives to start the foundation of answering a data science problem. First, you’ll explore what exactly is and the various components that go into making an exploratory data analysis research plan. Next, you’ll go step-by-step and actually implement your own research plan to find some insights into the data. Finally, you’ll learn how to compile all the information into a cohesive and informative manner to present to other people. When you’re finished with this course, you’ll have the skills and knowledge to create an effective exploratory data analysis research plan needed to find insights within data and present it to the executives of a company.

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What's inside

Syllabus

Course Overview
Exploring Exploratory Data Analysis for Business
Crafting Our Own Exploratory Data Analysis Research Plan
Executing and Analyzing Our Own Exploratory Data Analysis Research Plan
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches how to execute and analyze a thorough exploratory data analysis research plan, suitable for a business setting
Taught by Anand Saravanan, who is recognized for their work in data science
Develops skills in creating research reports to present to business executives
Provides a step-by-step guide to implementing an exploratory data analysis research plan
Suitable for individuals looking to make data-driven decisions in a business context

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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 Designing and Executing an Exploratory Data Analysis Research Plan with these activities:
Attend Industry Meetups or Webinars on EDA
Connect with professionals in the field, stay updated on industry trends, and gain valuable insights from experts.
Browse courses on Networking
Show steps
  • Research and identify relevant industry events.
  • Register and attend the events.
  • Engage in discussions and network with attendees.
Refresh data analysis skills.
Ensure that you have the necessary data analysis skills to fully maximize the learning outcomes of this course.
Browse courses on Data Analysis
Show steps
  • Review your textbook notes and assignments.
  • Complete a few data analysis practice problems.
  • Identify and familiarize yourself with current industry tools.
Seek Mentorship from Experienced Data Analysts
Gain access to personalized guidance and support from experienced professionals who can provide valuable insights and advice.
Browse courses on Mentorship
Show steps
  • Identify potential mentors.
  • Reach out and request mentorship.
  • Connect regularly and seek advice on career development and technical challenges.
Five other activities
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Independent Research on EDA Techniques
Strengthen your critical thinking, analytical skills, and grasp of the various techniques involved in EDA.
Browse courses on Research Methods
Show steps
  • Identify a specific data set to analyze.
  • Research and understand the different EDA techniques that are suitable for your data set.
  • Apply the techniques to gain insights.
  • Document your findings in a report.
Organize a Study Group with Peers
Enhance your learning experience by collaborating with peers, discussing concepts, and solving problems together.
Browse courses on Collaboration
Show steps
  • Identify interested peers and form a study group.
  • Meet regularly to discuss course materials.
  • Work together on assignments and projects.
Complete Online Tutorials on EDA Libraries
Expand your knowledge of EDA tools and techniques by exploring specialized tutorials and online resources.
Browse courses on Data Analysis
Show steps
  • Identify reputable online tutorials.
  • Follow the tutorials step-by-step.
  • Experiment with the techniques and apply them to real-world data.
Interactive Data Exploration Tool
Demonstrate your understanding of EDA by creating an interactive tool that allows users to explore and analyze data effortlessly.
Browse courses on Data Visualization
Show steps
  • Choose a suitable data visualization library or framework.
  • Design and implement interactive features.
  • Ensure the tool is user-friendly and accessible.
Develop a Presentation on EDA Best Practices
Enhance your communication and presentation skills while reinforcing your understanding of EDA's best practices.
Show steps
  • Research and gather information on EDA best practices.
  • Structure your presentation logically.
  • Create visually appealing and informative slides.

Career center

Learners who complete Designing and Executing an Exploratory Data Analysis Research Plan will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists leverage their expertise in mathematics, statistics, and programming to extract meaningful insights from data. They build models to predict future outcomes, identify patterns, and develop solutions to complex business problems. The course on Designing and Executing an Exploratory Data Analysis Research Plan aligns well with the responsibilities of Data Scientists. It equips learners with the skills to create a structured research plan, which is crucial for managing complex data analysis projects and ensuring the validity and reliability of their findings.
Data Analyst
Data Analysts use data to solve business problems and provide recommendations to drive decision-making. They work with various data sources, including structured and unstructured data, to identify trends, patterns, and insights. A course on Designing and Executing an Exploratory Data Analysis Research Plan would be beneficial for aspiring Data Analysts as it provides a structured approach to plan and execute data analysis projects effectively. By understanding the components of a research plan, learners can develop a roadmap for their data analysis endeavors.
Market Researcher
Market Researchers gather and analyze data to understand market trends, customer behavior, and industry dynamics. They provide insights that help businesses make informed decisions about product development, marketing strategies, and target audience. The course on Designing and Executing an Exploratory Data Analysis Research Plan can enhance the skills of Market Researchers by equipping them with a systematic approach to data analysis. The course's focus on planning, execution, and presentation of research findings aligns with the core responsibilities of Market Researchers.
Business Intelligence Analyst
Business Intelligence Analysts gather, analyze, and interpret data to provide insights and recommendations to business stakeholders. They work with data from various sources to identify trends, patterns, and opportunities for improvement. The course on Designing and Executing an Exploratory Data Analysis Research Plan can provide Business Intelligence Analysts with a structured approach to data analysis and research planning. The course's emphasis on identifying trends and patterns in data can help Business Intelligence Analysts develop more effective solutions to business problems.
Statistician
Statisticians collect, analyze, interpret, and present data to provide insights and make informed decisions. They work in various industries, including healthcare, finance, and market research, to solve complex problems and draw meaningful conclusions from data. The course on Designing and Executing an Exploratory Data Analysis Research Plan can provide Statisticians with a structured approach to data analysis and research planning. The course's emphasis on identifying trends and patterns in data can help Statisticians develop more effective solutions to research questions.
Business Analyst
Business Analysts bridge the gap between business stakeholders and technical teams by understanding business requirements and translating them into technical specifications. They play a vital role in ensuring that technology solutions align with business objectives. The course on Designing and Executing an Exploratory Data Analysis Research Plan can benefit Business Analysts by providing them with a framework to analyze data and identify actionable insights that can inform decision-making and improve business outcomes.
Data Visualization Analyst
Data Visualization Analysts design and create visual representations of data to communicate insights and trends to stakeholders. They work with data analysts and other stakeholders to translate complex data into clear and engaging visualizations. The course on Designing and Executing an Exploratory Data Analysis Research Plan can provide Data Visualization Analysts with a deeper understanding of data analysis principles and techniques. The course's focus on presenting research findings in a clear and concise manner can help Data Visualization Analysts create more effective data visualizations.
Financial Analyst
Financial Analysts use financial data to evaluate investment opportunities, make recommendations, and develop financial models. They analyze financial statements, market trends, and economic indicators to identify undervalued assets, assess risk, and forecast future financial performance. The course on Designing and Executing an Exploratory Data Analysis Research Plan can provide Financial Analysts with a structured framework for data analysis. The course's emphasis on identifying trends and patterns in data can help Financial Analysts make more informed investment decisions.
Risk Analyst
Risk Analysts assess and manage risks that could impact an organization's financial performance, reputation, or operations. They analyze data to identify potential risks, evaluate their likelihood and impact, and develop mitigation strategies. The course on Designing and Executing an Exploratory Data Analysis Research Plan can benefit Risk Analysts by providing them with a structured approach to data analysis and risk assessment. The course's focus on identifying trends and patterns in data can help Risk Analysts better understand and manage risks.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve complex business problems. They work with large datasets and advanced algorithms to build models that can predict outcomes, identify patterns, and make decisions. The course on Designing and Executing an Exploratory Data Analysis Research Plan can provide Machine Learning Engineers with a solid foundation in data analysis and modeling techniques. The course's emphasis on identifying patterns and trends in data can help Machine Learning Engineers develop more effective machine learning models.
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty. They work in various industries, including insurance, finance, and healthcare, to develop and implement risk management strategies. The course on Designing and Executing an Exploratory Data Analysis Research Plan can provide Actuaries with a strong foundation in data analysis and modeling techniques. The course's emphasis on identifying patterns and trends in data can help Actuaries better understand and manage risks.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex business problems and improve operational efficiency. They develop and implement models to optimize processes, reduce costs, and enhance productivity. The course on Designing and Executing an Exploratory Data Analysis Research Plan can provide Operations Research Analysts with a foundation in data analysis and modeling techniques. The course's emphasis on identifying patterns and trends in data can help Operations Research Analysts develop more effective solutions to business problems.
Data Scientist Manager
Data Scientist Managers lead and manage teams of Data Scientists and other data professionals. They set the strategic direction for data science initiatives and ensure that data science projects align with the organization's overall goals. The course on Designing and Executing an Exploratory Data Analysis Research Plan can provide Data Scientist Managers with a deeper understanding of data analysis principles and techniques. The course's focus on planning, execution, and presentation of research findings can help Data Scientist Managers better understand the needs of data scientists and end-users.
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure to support data analysis and machine learning applications. They work with large datasets and complex data systems to ensure data quality, accessibility, and performance. The course on Designing and Executing an Exploratory Data Analysis Research Plan can provide Data Engineers with a deeper understanding of data analysis principles and techniques. The course's focus on planning, execution, and presentation of research findings can help Data Engineers better understand the needs of data analysts and end-users.
Quantitative Analyst
Quantitative Analysts use statistical models and mathematical techniques to analyze financial data and make investment decisions. They develop trading strategies, assess risk, and manage portfolios. The course on Designing and Executing an Exploratory Data Analysis Research Plan can benefit Quantitative Analysts by providing them with a solid foundation in data analysis and modeling techniques. The course's focus on identifying patterns and trends in data can help Quantitative Analysts make more informed investment decisions.

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 Designing and Executing an Exploratory Data Analysis Research Plan.
Provides a comprehensive introduction to statistical learning methods. It valuable resource for students and practitioners who want to learn more about machine learning.
Provides a thought-provoking exploration of the future of artificial intelligence. It valuable resource for students and practitioners who want to learn more about the potential of artificial intelligence.
Provides a practical introduction to data science for business professionals. It valuable resource for students and practitioners who want to learn more about using data to make better decisions.
Provides a comprehensive introduction to Bayesian data analysis. It valuable resource for students and practitioners who want to learn more about Bayesian data analysis.
Provides a comprehensive introduction to causal inference in statistics. It valuable resource for students and practitioners who want to learn more about causal inference.
Provides a comprehensive introduction to deep learning. It valuable resource for students and practitioners who want to learn more about deep learning.
Provides a comprehensive introduction to reinforcement learning. It valuable resource for students and practitioners who want to learn more about reinforcement learning.
Provides a comprehensive introduction to data science in R. It valuable resource for students and practitioners who want to learn more about using R for data analysis.
Provides a comprehensive introduction to machine learning in Python. It valuable resource for students and practitioners who want to learn more about using Python for machine learning.
Provides a comprehensive introduction to data analysis in Python. It valuable resource for students and practitioners who want to learn more about using Python for data analysis.
Provides a gentle introduction to machine learning. It valuable resource for students and practitioners who want to learn more about machine learning without getting bogged down in the technical details.

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