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Santhi B
This project focuses on the time series data analysis for beginners using python. Model building is effective only after doing proper exploratory analysis and get insight into the data set. The objectives are as follows:
1. Importing required libraries and import time-series data sets.
2. Get basic descriptive statistics and review the summary of time-series data
3. Get inference from the visualization graphs of time series data
4. Check the behavior of time series data
5. Apply transformation functions to convert non-stationary to stationary
This Guided Project was created by a Coursera community member.
Register for this course and see more details by visiting:
OpenCourser.com/course/hcfhat/exploratory
Good to know
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Know what's good ,
what to watch for , and
possible dealbreakers
Provides a strong foundation for beginners in time series data analysis
Focuses on essential concepts and practical skills for time series data analysis using Python
Covers important aspects of time series data analysis, from exploratory analysis to model building
Taught by instructors with relevant experience in data analysis
Provides hands-on practice through interactive materials
May not cover more advanced topics or recent developments in time series analysis
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Save Exploratory Time Series Analysis to your list so you can find it easily later:
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Reviews summary
Beginner's guide to time series analysis
This course introduces learners to time series data analysis using Python. The course is aimed at beginners and uses clear, concise, and easy-to-follow content to walk learners through basic descriptive statistics, visualization, and transformation. The course is well-received with 82% of reviews giving it a perfect score of 5 out of 5 stars.
Provides a hands-on perspective to exploring time series data.
"Gives the user a quick hands on perspective to explore Time Series data."
Easy-to-follow course for beginners.
"The course content is very concise and easy to follow."
"Good for beginners"
Some instructions were off and links were broken.
"Didn't really learn much from this. A lot of the instructions were off and links were broken. "
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 Exploratory Time Series Analysis with these
activities:
Time Series Data Resources
Show steps
Compile a list of useful time series data resources, such as books, articles, and websites.
Show steps
-
Search for time series data resources
-
Create a list of resources
-
Share your list with other students
Time Series Analysis by Shumway and Stoffer
Show steps
Read this book to gain a deeper understanding of the fundamental concepts of time series analysis.
View
Time Series Analysis and Its Applications: With...
on Amazon
Show steps
-
Read the book
-
Complete the exercises
-
Apply the concepts to your own projects
Time Series Data Tutorial
Show steps
Complete this tutorial to reinforce your understanding of time series data analysis using Python.
Show steps
-
Watch the tutorial videos
-
Complete the practice exercises
-
Apply the techniques to a small dataset
Four other activities
Expand to see all activities and additional details
Show all seven activities
Time Series Data Analysis Exercises
Show steps
Practice analyzing time series data with these exercises.
Show steps
-
Import time series data
-
Explore the data
-
Build and evaluate time series models
Mentor a Junior Time Series Data Analyst
Show steps
Share your knowledge with a junior time series data analyst and help them develop their skills.
Browse courses on
Time Series Analysis
Show steps
-
Find a junior time series data analyst to mentor
-
Set up regular meetings
-
Provide guidance and support
Time Series Data Analysis Workshop
Show steps
Learn about advanced time series data analysis techniques from experts.
Browse courses on
Time Series Analysis
Show steps
-
Find a local time series data analysis workshop
-
Attend the workshop
-
Apply the techniques you learned to your own projects
Time Series Data Analysis Project
Show steps
Apply your skills to a real-world time series data analysis project.
Show steps
-
Define the project goals
-
Collect and prepare the data
-
Analyze the data
-
Build and evaluate time series models
-
Present your findings
Time Series Data Resources
Show steps
Compile a list of useful time series data resources, such as books, articles, and websites.
Show steps
Show steps
Show steps
- Search for time series data resources
- Create a list of resources
- Share your list with other students
Time Series Analysis by Shumway and Stoffer
Show steps
Read this book to gain a deeper understanding of the fundamental concepts of time series analysis.
View
Time Series Analysis and Its Applications: With...
on Amazon
Show steps
Show steps
Show steps
- Read the book
- Complete the exercises
- Apply the concepts to your own projects
Time Series Data Tutorial
Show steps
Complete this tutorial to reinforce your understanding of time series data analysis using Python.
Show steps
Show steps
Show steps
- Watch the tutorial videos
- Complete the practice exercises
- Apply the techniques to a small dataset
Four other activities
Expand to see all activities and additional details
Show all seven activities
Time Series Data Analysis Exercises
Show steps
Practice analyzing time series data with these exercises.
Show steps
Show steps
Show steps
- Import time series data
- Explore the data
- Build and evaluate time series models
Mentor a Junior Time Series Data Analyst
Show steps
Share your knowledge with a junior time series data analyst and help them develop their skills.
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Find a junior time series data analyst to mentor
- Set up regular meetings
- Provide guidance and support
Time Series Data Analysis Workshop
Show steps
Learn about advanced time series data analysis techniques from experts.
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Find a local time series data analysis workshop
- Attend the workshop
- Apply the techniques you learned to your own projects
Time Series Data Analysis Project
Show steps
Apply your skills to a real-world time series data analysis project.
Show steps
Show steps
Show steps
- Define the project goals
- Collect and prepare the data
- Analyze the data
- Build and evaluate time series models
- Present your findings
Career center
Learners who complete Exploratory Time Series Analysis will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data analysts clean, analyze, and interpret data to extract meaningful insights. Exploratory Time Series Analysis provides a solid foundation in time series data analysis, which is increasingly important in various industries, including finance, healthcare, and retail. This course can help data analysts identify trends, develop predictive models, and communicate their findings effectively, enhancing their ability to contribute to data-driven decision-making.
Quantitative Analyst
Quantitative Analyst
Quantitative analysts (quants) apply mathematical and statistical techniques to analyze financial data. Exploratory Time Series Analysis provides a strong foundation in time series analysis, which is essential for quants working in risk management, trading, and investment analysis. This course can help quants develop more accurate financial models, make more informed investment decisions, and mitigate risk.
Data Scientist
Data Scientist
Data scientists play a crucial role in extracting insights from large datasets. Exploratory Time Series Analysis can enhance their skillset by providing a deeper understanding of time-dependent data and enabling them to develop more robust predictive models. This course can be particularly beneficial for data scientists working in industries with time-series data, such as finance, healthcare, and manufacturing.
Financial Analyst
Financial Analyst
Financial analysts utilize various techniques, including time series analysis, to understand and predict financial trends and make informed investment decisions. Exploratory Time Series Analysis provides a strong foundation by enhancing an analyst's ability to identify patterns and anomalies in financial data, enabling them to make more accurate forecasts and develop more effective investment strategies.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data. Exploratory Time Series Analysis provides a comprehensive understanding of time series data analysis techniques, which are crucial for statisticians working in various fields, including finance, healthcare, and social sciences. This course can help statisticians develop more robust statistical models, make more informed inferences, and communicate their findings effectively.
Risk Analyst
Risk Analyst
Risk analysts evaluate and mitigate financial and operational risks. Exploratory Time Series Analysis provides valuable tools for identifying and assessing risks over time, enabling risk analysts to make more informed decisions and develop effective risk management strategies. This course can be particularly beneficial for risk analysts working in financial institutions, insurance companies, and regulatory bodies.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess and manage risk. Exploratory Time Series Analysis provides a strong foundation in time series analysis, which is essential for actuaries working in insurance, pensions, and other financial fields. This course can help actuaries develop more accurate risk models, make more informed decisions, and provide sound financial advice.
Economist
Economist
Economists analyze economic data to understand economic trends and make policy recommendations. Exploratory Time Series Analysis provides a strong understanding of time series data analysis, which is essential for economists working in academia, government, and the private sector. This course can help economists develop more accurate economic models, make more informed policy recommendations, and contribute to economic growth.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use mathematical and analytical techniques to solve complex business problems. Exploratory Time Series Analysis provides a foundation in time series analysis, which can be applied to optimize supply chains, improve production processes, and enhance customer experience. This course can help operations research analysts develop more effective solutions, improve operational efficiency, and make better decisions.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers build and deploy machine learning models to solve real-world problems. Exploratory Time Series Analysis provides a foundation in time series analysis, which is a specialized area of machine learning. This course can enhance the skills of machine learning engineers working on time-series data applications, such as forecasting, anomaly detection, and trend analysis. It can help them develop more accurate and robust machine learning models.
Market Researcher
Market Researcher
Market researchers analyze market trends and consumer behavior to inform marketing strategies. Exploratory Time Series Analysis provides a solid understanding of time-series data, which is crucial for understanding how market trends evolve over time. This course can help market researchers identify emerging trends, predict consumer behavior, and develop more effective marketing campaigns.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes and distribution of diseases in populations. Exploratory Time Series Analysis provides a solid understanding of time series data analysis, which is crucial for epidemiologists studying the spread of infectious diseases, chronic conditions, and other health outcomes over time. This course can help epidemiologists identify trends, develop predictive models, and implement effective public health interventions.
Financial Planner
Financial Planner
Financial planners help individuals and families achieve their financial goals. Exploratory Time Series Analysis provides a strong understanding of time series data analysis, which can be useful for financial planners working with clients who have complex financial situations or long-term financial goals. This course can help financial planners identify trends, develop personalized financial plans, and make more informed investment recommendations.
Business Analyst
Business Analyst
Business analysts identify and solve business problems using data-driven insights. Exploratory Time Series Analysis can enhance their ability to analyze historical data, identify trends, and make predictions. This course can help business analysts develop more effective business strategies, improve operational efficiency, and make more informed decisions.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software systems. While Exploratory Time Series Analysis is not directly related to software engineering, it may be useful for software engineers working on time-series data applications, such as data visualization tools, predictive analytics platforms, and financial modeling software. This course can help software engineers understand the fundamentals of time series analysis and develop more robust and efficient software solutions.
For more career information including salaries, visit:
OpenCourser.com/course/hcfhat/exploratory
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
Exploratory Time Series Analysis .
Save
Provides a comprehensive introduction to time series analysis, covering both theoretical and practical aspects. It is written in a clear and concise style, and includes numerous examples and exercises to help the reader understand the concepts.
Classic textbook on time series analysis and forecasting. It covers a wide range of topics, from the basics of time series analysis to advanced topics such as state space models.
Save
Classic textbook on time series analysis and forecasting. It covers a wide range of topics, from the basics of time series analysis to advanced topics such as state space models.
Classic textbook on time series analysis. It covers a wide range of topics, from the basics of time series analysis to advanced topics such as state space models.
Practical guide to time series analysis using R. It covers a wide range of topics, from the basics of time series analysis to advanced topics such as machine learning.
Save
Practical guide to forecasting. It covers a wide range of forecasting methods, from simple to complex.
Save
Practical guide to time series analysis. It covers a wide range of topics, from the basics of time series analysis to advanced topics such as machine learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/hcfhat/exploratory
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Time
1 hours
Via
Coursera
Institution
Coursera Community Project Network
Instructor
Santhi B
Good to know
Provides a strong foundation for beginners in time series data analysis
Focuses on essential concepts and practical skills for time series data analysis using Python
Covers important aspects of time series data analysis, from exploratory analysis to model building
Taught by instructors with relevant experience in data analysis
Provides hands-on practice through interactive materials
May not cover more advanced topics or recent developments in time series analysis
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