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Fundamentals of Data Analysis
Erik Herman
Erik Herman
This course is the first of a series that aims to prepare you for a role working in data analytics. In this course, you’ll be introduced to many of the primary types of data analytics and core concepts. You’ll learn about the tools and skills required to conduct data analysis. We’ll go through some of the foundational math and statistics used in data analysis and workflows for conducting efficient and effective data analytics. This course covers a wide variety of topics that are critical for working in data analytics and are designed to give you an introduction and overview as you begin to build relevant knowledge and skills.
Register for this course and see more details by visiting:
OpenCourser.com/course/m8mcpl/fundamentals
What's inside
Syllabus
Types of Data Analysis
In the first module of the course, we'll learn about the primary types of data analysis including, descriptive, predictive, diagnostic, and exploratory. We will also learn about some advanced data analytic types including mechanistic, causal, and inferential. By the end of this module, you will know how to identify the different types of data analysis and their use cases. So let's get started!
Read more
Syllabus
Types of Data Analysis
In the first module of the course, we'll learn about the primary types of data analysis including, descriptive, predictive, diagnostic, and exploratory. We will also learn about some advanced data analytic types including mechanistic, causal, and inferential. By the end of this module, you will know how to identify the different types of data analysis and their use cases. So let's get started!
Read more
The Phases of Data Analysis
In the second module of this course, we'll learn about the phases of the data analysis process including identifying data, defining scope, and level of detail. We'll learn about the data collection process, from gathering targeted information to evaluating outcomes. We'll discover the importance of data cleaning and how removing, modifying, and formatting data is a priority, as well as the benefits of visualizing data.
Data Analytics Tools and Skills
In the third module of this course, we'll learn about the tools and skills essential for data analysis. We'll learn about using spreadsheets and databases for analyzing and managing the data. We'll discover the power of query languages and multidimensional expressions. We’ll also describe the fundamental programming languages used in data analytics.
Foundational Data Analytics Math and Stats
In the fourth module of this course, we'll learn about the fundamental math and stats used for data analysis. We’ll also describe some advanced data analytic algorithms and their use cases, including linear regression and clustering.
Data Analytics Methodologies and Workflows
In the fifth week of this course, we'll learn about defining data analytics methodologies and workflows.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines various types of data analysis, a core understanding in the industry
Covers the data analysis process from start to finish to develop essential skills
Highlights the essential tools and skills for effective data analysis
Reinforces foundational math and statistics concepts in a data analysis context
Develops methodologies and workflows to structure the data analysis process
May require prior knowledge and experience in data analysis
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Save Fundamentals of Data Analysis to your list so you can find it easily later:
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Reviews summary
Introductory data analysis course
Learners say that Fundamentals of Data Analysis is an engaging introductory data analysis course geared towards beginners. While the course content is generally comprehensive, there could be more depth. Some students also experienced difficulty with the course quizzes, which often require exact spelling and have obscure answers. Despite these issues, many students found the teaching format to be easy to understand.
Course is beginner-friendly.
"The fact that he repeatedly mentions he does not have a math or computer science background is extremely reassuring for those of us who are changing careers and coming from a non-data-specific background !"
"The unfortunate and frustrating parts were the non-working links and the fill in the blank questions that did not allow for variation other than a very specifically worded response that was hard to determine. For example ~ "Factor Analysis" was correct for one but only "Factor" was acceptable for a similar question with the same answer. "Six" was not accepted but "6" was, etc. The content itself is great, tho!"
"I debated between giving this course two stars or three stars and decided to give it the benefit of the doubt and give it three, since there is some useful information contained with it, despite its many flaws."
Course content is generally positive.
"VERRY GOOD"
"Basic Theory only"
"The content and teaching format are excellent. The information is easy to understand and the fact that he repeatedly mentions he does not have a math or computer science background is extremely reassuringg for those of us who are changing careers and coming from a non-data-specific background ! "
"Some quizes contain very obscure answers, other than that, its a good course on data analysis for beginners."
Course quizzes can be difficult.
"The unfortunate and frustrating parts were the non-working links and the fill in the blank questions that did not allow for variation other than a very specifically worded response that was hard to determine."
"For example ~ "Factor Analysis" was correct for one but only "Factor" was acceptable for a similar question with the same answer. "Six" was not accepted but "6" was, etc."
"The content itself is great, tho!"
Activities
Coming soon
We're preparing activities for
Fundamentals of Data Analysis.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Fundamentals of Data Analysis will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use their expertise in machine learning, statistics, programming, and data visualization to extract insights from large volumes of structured and unstructured data. This course provides a solid foundation for aspiring Data Analysts by introducing them to the core concepts, tools, and techniques used in data analysis. The course covers various types of data analysis, including descriptive, predictive, diagnostic, and exploratory analysis. It also introduces learners to essential data analytics tools and skills, including spreadsheets, databases, query languages, and programming languages. By completing this course, learners will gain a comprehensive understanding of the data analysis process and develop the skills necessary to excel as Data Analysts.
Business Analyst
Business Analyst
Business Analysts use their understanding of business processes and data analysis techniques to help organizations improve their performance. This course is a valuable resource for aspiring Business Analysts as it provides a solid foundation in data analysis, which is essential for identifying and solving business problems. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as tools and techniques for data collection, cleaning, and visualization. By completing this course, learners will gain the skills and knowledge necessary to succeed as Business Analysts.
Data Scientist
Data Scientist
Data Scientists use their expertise in machine learning, statistics, and data analysis to extract insights from large volumes of data and develop predictive models. This course is a valuable resource for aspiring Data Scientists as it provides a solid foundation in data analysis, which is a core skill for this role. The course covers various types of data analysis, including descriptive, predictive, diagnostic, and exploratory analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Data Scientists.
Market Researcher
Market Researcher
Market Researchers use their understanding of data analysis techniques to gather and interpret data about consumer behavior and market trends. This course is a valuable resource for aspiring Market Researchers as it provides a solid foundation in data analysis, which is essential for conducting effective market research. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as tools and techniques for data collection, cleaning, and visualization. By completing this course, learners will gain the skills and knowledge necessary to succeed as Market Researchers.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their expertise in data analysis and optimization techniques to improve the efficiency and effectiveness of business processes. This course is a valuable resource for aspiring Operations Research Analysts as it provides a solid foundation in data analysis, which is essential for this role. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Operations Research Analysts.
Financial Analyst
Financial Analyst
Financial Analysts use their expertise in data analysis and financial modeling to make investment recommendations and evaluate the performance of financial instruments. This course is a valuable resource for aspiring Financial Analysts as it provides a solid foundation in data analysis, which is essential for this role. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Financial Analysts.
Actuary
Actuary
Actuaries use their expertise in data analysis and statistics to assess and manage financial risks. This course is a valuable resource for aspiring Actuaries as it provides a solid foundation in data analysis, which is essential for this role. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Actuaries.
Statistician
Statistician
Statisticians use their expertise in data analysis and probability theory to collect, analyze, and interpret data. This course is a valuable resource for aspiring Statisticians as it provides a solid foundation in data analysis, which is essential for this role. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Statisticians.
Data Engineer
Data Engineer
Data Engineers use their expertise in data management and data analysis to design and build data pipelines and data warehouses. This course is a valuable resource for aspiring Data Engineers as it provides a solid foundation in data analysis, which is essential for this role. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Data Engineers.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use their expertise in data analysis and financial modeling to develop trading strategies and manage investment portfolios. This course is a valuable resource for aspiring Quantitative Analysts as it provides a solid foundation in data analysis, which is essential for this role. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Quantitative Analysts.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use their expertise in data analysis and machine learning to develop and deploy machine learning models. This course is a valuable resource for aspiring Machine Learning Engineers as it provides a solid foundation in data analysis, which is essential for this role. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Machine Learning Engineers.
Data Architect
Data Architect
Data Architects use their expertise in data management and data analysis to design and build data architectures. This course is a valuable resource for aspiring Data Architects as it provides a solid foundation in data analysis, which is essential for this role. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Data Architects.
Software Engineer
Software Engineer
Software Engineers use their expertise in computer science and software development to design, build, and maintain software systems. This course may be useful for aspiring Software Engineers as it provides a solid foundation in data analysis, which is increasingly used in software development. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Software Engineers.
Product Manager
Product Manager
Product Managers use their expertise in product development and data analysis to define, build, and launch new products. This course may be useful for aspiring Product Managers as it provides a solid foundation in data analysis, which is increasingly used in product development. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Product Managers.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use their expertise in data analysis and business intelligence tools to provide insights and recommendations to business leaders. This course may be useful for aspiring Business Intelligence Analysts as it provides a solid foundation in data analysis, which is essential for this role. The course covers various types of data analysis, including descriptive, predictive, and diagnostic analysis, as well as introduces learners to fundamental data analytics math and statistics. By completing this course, learners will gain the skills and knowledge necessary to succeed as Business Intelligence Analysts.
For more career information including salaries, visit:
OpenCourser.com/course/m8mcpl/fundamentals
Reading list
We've selected ten 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
Fundamentals of Data Analysis.
Provides a comprehensive overview of data analytics, covering the key concepts, tools, and techniques used in the field. It valuable resource for beginners who want to learn more about data analytics, as well as for experienced professionals who want to refresh their knowledge.
Provides a practical guide to data science for business professionals. It covers the key concepts, tools, and techniques used to analyze data and make informed decisions. It valuable resource for business professionals who want to learn more about data science.
Save
Provides a comprehensive overview of data mining. It covers the key concepts, tools, and techniques used to extract knowledge from data. It valuable resource for data miners who want to learn more about the field.
Save
Provides a comprehensive overview of machine learning for data analytics. It covers the key concepts, tools, and techniques used to build and deploy machine learning models. It valuable resource for data analysts who want to learn more about machine learning.
Save
Provides a comprehensive overview of deep learning for data analytics. It covers the key concepts, tools, and techniques used to build and deploy deep learning models. It valuable resource for data analysts who want to learn more about deep learning.
Save
Provides a practical introduction to data visualization. It covers the key concepts, tools, and techniques used to create effective data visualizations. It valuable resource for data analysts who want to learn more about data visualization.
Provides a comprehensive overview of statistical methods for data analysis. It covers the key concepts, tools, and techniques used to analyze data. It valuable resource for data analysts who want to learn more about statistics.
Save
Provides a comprehensive guide to data analysis using R. It covers the key concepts, tools, and techniques used to analyze data with R. It valuable resource for data analysts who want to learn more about R.
Save
Provides a comprehensive guide to using R for data science. It covers the key concepts, tools, and techniques used to analyze data with R. It valuable resource for data scientists who want to learn more about R.
Provides a comprehensive guide to using Python for data analysis. It covers the key concepts, tools, and techniques used to analyze data with Python. It valuable resource for data analysts who want to learn more about Python.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/m8mcpl/fundamentals
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Effort
This course requires 4 weeks at about 3-5 hours/week to complete.
Level
Introductory
Via
Coursera
Institution
LearnQuest
Instructor
Erik Herman
Language
English
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This course belongs to a
collection
called
Key Technologies in Data Analytics. It's comprised of four courses:
- Fundamentals of Cloud Computing
- Fundamentals of Data Analysis (viewing)
- Fundamentals of Big Data
- Fundamentals of Data Warehousing
Good to know
Examines various types of data analysis, a core understanding in the industry
Covers the data analysis process from start to finish to develop essential skills
Highlights the essential tools and skills for effective data analysis
Reinforces foundational math and statistics concepts in a data analysis context
Develops methodologies and workflows to structure the data analysis process
May require prior knowledge and experience in data analysis
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