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Ryan Ahmed
In this hands-on project, we will understand the fundamentals of data analysis in Python and we will leverage the power of two important python libraries known as Numpy and pandas. NumPy and Pandas are two of the most widely used python libraries in data science. They offer high-performance, easy to use structures and data analysis tools.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/jw6dpc/python
What's inside
Syllabus
Python for Data Analysis: Pandas & NumPy
In this hands-on project, we will understand the fundamentals of data analysis in Python and we will leverage the power of two important python libraries known as Numpy and pandas. NumPy and Pandas are two of the most widely used python libraries in data science since they offer high-performance, easy to use structures and data analysis tools.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Well-suited for those new to data analysis, this course provides a solid foundation in Python, Numpy, and Pandas
By using widely used and powerful Python libraries, this course empowers learners to analyze and work with data
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Save Python for Data Analysis: Pandas & NumPy to your list so you can find it easily later:
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Reviews summary
Python, pandas, & numpy for data analysis
Learners say this Python course gets good reviews and is an excellent platform for beginners in data science who want to learn the basics of NumPy and Pandas. Reviews highlight that the instructor is clear and engaging. The course's projects and tasks are helpful and practical, allowing learners to apply their knowledge and build hands-on skills. Overall, this course is well-received and is a great option for those new to data science.
Clear and engaging instructor makes learning easier.
"Ryan is awesome."
"The instructor was excellent and the material covered would have almost endless applications an a wide variety of fields."
"He really tries to do a good job introducing a complicated topic in as simple fashion as possible."
Engaging projects help you apply your learning.
"This was excellent and way better than the other guided project."
"This project was very useful in getting skilled at using pandas and numpy throuh hands on learning."
"Absolutely wonderful Guided Project vs the 4 or 5 I've done. It is very much hands on."
Cloud workspace can be slow and difficult to use.
"Using the cloud workspace in the course was a problem. It was slow and hard to use, which made learning frustrating."
"Cloud workspace issues were frustrating and made learning difficult."
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 Python for Data Analysis: Pandas & NumPy with these
activities:
Follow beginner-friendly tutorials on Python
Show steps
Seek out online tutorials that provide step-by-step guidance on Python fundamentals, strengthening foundational knowledge.
Browse courses on
Python
Show steps
-
Identify beginner-level Python tutorials
-
Follow tutorials and complete exercises
-
Test your understanding through quizzes
Practice with Python packages
Show steps
Practice working with Python libraries to solidify understanding of their functions and syntax.
Browse courses on
Python
Show steps
-
Install Python packages
-
Execute Python commands
-
Complete coding exercises
Practice data manipulation with Numpy
Show steps
Work through practice exercises that cover various Numpy array operations and functions, reinforcing comprehension of its capabilities.
Browse courses on
NumPy
Show steps
-
Solve data analysis tasks using Numpy
-
Load datasets into Numpy arrays
-
Perform array manipulations
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore tutorials on Pandas data analysis
Show steps
Seek out tutorials that demonstrate practical Pandas applications, enhancing your understanding of its capabilities in data analysis.
Browse courses on
Pandas
Show steps
-
Find tutorials on Pandas data analysis
-
Follow tutorials and work through examples
-
Experiment with Pandas functions and explore its documentation
Practice data analysis with Pandas
Show steps
Engage in hands-on exercises covering essential Pandas operations, fostering proficiency in data manipulation and analysis.
Browse courses on
Pandas
Show steps
-
Load data into Pandas DataFrames
-
Perform data cleaning and preprocessing
-
Analyze data using Pandas functions
Explore advanced tutorials on Numpy
Show steps
Delve into tutorials that cover advanced Numpy concepts, expanding your knowledge and skills in array manipulation and operations.
Browse courses on
NumPy
Show steps
-
Search for advanced Numpy tutorials
-
Follow tutorials and complete coding challenges
-
Apply Numpy techniques to solve real-world problems
Write a blog post on Python for data analysis
Show steps
Compose a blog post that shares your insights and learnings about using Python for data analysis, reinforcing your understanding and helping others.
Browse courses on
Python
Show steps
-
Choose a topic related to Python data analysis
-
Research and gather information
-
Write and edit your blog post
-
Publish and promote your blog post
Develop a Python data analysis project
Show steps
Embark on a project that involves applying Python libraries to solve a real-world data analysis problem, showcasing your comprehension.
Browse courses on
Python
Show steps
-
Identify a data analysis problem
-
Gather and clean data
-
Apply Python libraries to analyze data
-
Present and interpret results
Follow beginner-friendly tutorials on Python
Show steps
Seek out online tutorials that provide step-by-step guidance on Python fundamentals, strengthening foundational knowledge.
Browse courses on
Python
Show steps
Show steps
Show steps
- Identify beginner-level Python tutorials
- Follow tutorials and complete exercises
- Test your understanding through quizzes
Practice with Python packages
Show steps
Practice working with Python libraries to solidify understanding of their functions and syntax.
Browse courses on
Python
Show steps
Show steps
Show steps
- Install Python packages
- Execute Python commands
- Complete coding exercises
Practice data manipulation with Numpy
Show steps
Work through practice exercises that cover various Numpy array operations and functions, reinforcing comprehension of its capabilities.
Browse courses on
NumPy
Show steps
Show steps
Show steps
- Solve data analysis tasks using Numpy
- Load datasets into Numpy arrays
- Perform array manipulations
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore tutorials on Pandas data analysis
Show steps
Seek out tutorials that demonstrate practical Pandas applications, enhancing your understanding of its capabilities in data analysis.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Find tutorials on Pandas data analysis
- Follow tutorials and work through examples
- Experiment with Pandas functions and explore its documentation
Practice data analysis with Pandas
Show steps
Engage in hands-on exercises covering essential Pandas operations, fostering proficiency in data manipulation and analysis.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Load data into Pandas DataFrames
- Perform data cleaning and preprocessing
- Analyze data using Pandas functions
Explore advanced tutorials on Numpy
Show steps
Delve into tutorials that cover advanced Numpy concepts, expanding your knowledge and skills in array manipulation and operations.
Browse courses on
NumPy
Show steps
Show steps
Show steps
- Search for advanced Numpy tutorials
- Follow tutorials and complete coding challenges
- Apply Numpy techniques to solve real-world problems
Write a blog post on Python for data analysis
Show steps
Compose a blog post that shares your insights and learnings about using Python for data analysis, reinforcing your understanding and helping others.
Browse courses on
Python
Show steps
Show steps
Show steps
- Choose a topic related to Python data analysis
- Research and gather information
- Write and edit your blog post
- Publish and promote your blog post
Develop a Python data analysis project
Show steps
Embark on a project that involves applying Python libraries to solve a real-world data analysis problem, showcasing your comprehension.
Browse courses on
Python
Show steps
Show steps
Show steps
- Identify a data analysis problem
- Gather and clean data
- Apply Python libraries to analyze data
- Present and interpret results
Career center
Learners who complete Python for Data Analysis: Pandas & NumPy will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst gathers, interprets, and presents data to help businesses make informed decisions. The course Python for Data Analysis: Pandas & NumPy provides a solid foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Data Analysts to effectively perform their job duties.
Data Scientist
Data Scientist
Data Scientists use their knowledge of math, statistics, and programming to extract insights from data. The course Python for Data Analysis: Pandas & NumPy provides a strong foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Data Scientists to effectively perform their job duties.
Statistician
Statistician
Statisticians use their knowledge of math and statistics to collect, analyze, and interpret data. The course Python for Data Analysis: Pandas & NumPy provides a strong foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Statisticians to effectively perform their job duties.
Financial Analyst
Financial Analyst
Financial Analysts use their knowledge of finance and economics to make investment recommendations. The course Python for Data Analysis: Pandas & NumPy provides a strong foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Financial Analysts to effectively perform their job duties.
Market Researcher
Market Researcher
Market Researchers use their knowledge of marketing and research to collect, analyze, and interpret data about consumers. The course Python for Data Analysis: Pandas & NumPy provides a strong foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Market Researchers to effectively perform their job duties.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business and technology to analyze and improve business processes. The course Python for Data Analysis: Pandas & NumPy provides a strong foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Business Analysts to effectively perform their job duties.
Software Engineer
Software Engineer
Software Engineers use their knowledge of computer science and programming to design, develop, and maintain software applications. The course Python for Data Analysis: Pandas & NumPy provides a strong foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Software Engineers to effectively perform their job duties.
Data Engineer
Data Engineer
Data Engineers use their knowledge of data management and programming to build and maintain data pipelines. The course Python for Data Analysis: Pandas & NumPy provides a strong foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Data Engineers to effectively perform their job duties.
Database Administrator
Database Administrator
Database Administrators use their knowledge of databases and programming to design, develop, and maintain database systems. The course Python for Data Analysis: Pandas & NumPy provides a strong foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Database Administrators to effectively perform their job duties.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use their knowledge of machine learning and programming to develop and maintain machine learning models. The course Python for Data Analysis: Pandas & NumPy provides a strong foundation for this role by teaching students how to use Python libraries like NumPy and Pandas to manipulate, analyze, and visualize data. These skills are essential for Machine Learning Engineers to effectively perform their job duties.
Product Manager
Product Manager
Product Managers use their knowledge of product management and marketing to develop and launch new products. The course Python for Data Analysis: Pandas & NumPy may be useful for this role by providing students with a foundation in data analysis, which can be helpful for understanding customer needs and developing successful products.
Marketing Manager
Marketing Manager
Marketing Managers use their knowledge of marketing and business to develop and execute marketing campaigns. The course Python for Data Analysis: Pandas & NumPy may be useful for this role by providing students with a foundation in data analysis, which can be helpful for understanding customer behavior and developing effective marketing campaigns.
Sales Manager
Sales Manager
Sales Managers use their knowledge of sales and business to develop and execute sales strategies. The course Python for Data Analysis: Pandas & NumPy may be useful for this role by providing students with a foundation in data analysis, which can be helpful for understanding customer needs and developing effective sales strategies.
Customer Success Manager
Customer Success Manager
Customer Success Managers use their knowledge of customer service and relationship management to ensure that customers are satisfied with their products or services. The course Python for Data Analysis: Pandas & NumPy may be useful for this role by providing students with a foundation in data analysis, which can be helpful for understanding customer needs and developing effective customer success strategies.
Project Manager
Project Manager
Project Managers use their knowledge of project management and business to plan, execute, and close projects. The course Python for Data Analysis: Pandas & NumPy may be useful for this role by providing students with a foundation in data analysis, which can be helpful for understanding project progress and making informed decisions.
For more career information including salaries, visit:
OpenCourser.com/course/jw6dpc/python
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
Python for Data Analysis: Pandas & NumPy.
Save
Provides a comprehensive overview of deep learning. It covers a wide range of topics, from neural networks and convolutional neural networks to recurrent neural networks and generative adversarial networks. It good choice for students and researchers who want to learn the fundamentals of deep learning.
Provides a comprehensive overview of data science using Python, covering topics such as data manipulation, data exploration, machine learning, and deep learning. It valuable resource for both beginners and experienced data scientists.
Provides a comprehensive overview of data analysis using Python. It covers a wide range of topics, from data manipulation and visualization to machine learning and deep learning. It good choice for students and researchers who want to learn the fundamentals of data analysis.
Provides a comprehensive overview of deep learning using TensorFlow. It covers a wide range of topics, from neural networks and convolutional neural networks to recurrent neural networks and generative adversarial networks. It good choice for students and researchers who want to learn the fundamentals of deep learning.
Provides a comprehensive overview of feature engineering for machine learning. It covers a wide range of topics, from data cleaning and transformation to feature selection and dimensionality reduction. It good choice for students and researchers who want to learn the fundamentals of feature engineering.
Provides a comprehensive overview of data manipulation using Pandas. It covers a wide range of topics, from data cleaning and transformation to data aggregation and grouping. It good choice for students and researchers who want to learn the fundamentals of data manipulation.
Provides a practical introduction to deep learning using Python. It covers a wide range of topics, from neural networks and convolutional neural networks to recurrent neural networks and generative adversarial networks. It good choice for beginners who want to learn the basics of deep learning.
Provides a practical introduction to machine learning using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It covers a wide range of machine learning algorithms and techniques, and it is suitable for both beginners and experienced machine learning practitioners.
Provides a gentle introduction to data science using Python. It covers a wide range of topics, from data manipulation and visualization to machine learning and deep learning. It good choice for beginners who want to learn the basics of data science.
Provides a gentle introduction to data science using Python. It covers a wide range of topics, from data cleaning and transformation to data visualization and machine learning. It good choice for beginners who want to learn the basics of data science in a friendly and accessible manner.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jw6dpc/python
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Language
English
Good to know
Well-suited for those new to data analysis, this course provides a solid foundation in Python, Numpy, and Pandas
By using widely used and powerful Python libraries, this course empowers learners to analyze and work with data
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