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⇱ Python Foundations for Data Handling | Coursera

Python Foundations for Data Handling

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Efficiently manipulate Python strings and work with data structures like lists, dictionaries, and sets.

  • Develop problem-solving skills for handling data-related tasks using Python.

  • Gain hands-on experience with data visualization using Python libraries such as Matplotlib and Plotly.

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Assessments

4 assignments

Taught in English

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This course is part of the Data Understanding and Data Visualization with Python Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 3 modules in this course

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A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will explore the foundations of Python, focusing on key data handling techniques essential for real-world applications. By learning how to work with Python’s powerful libraries, you will become proficient in handling, manipulating, and visualizing data. You will gain a deep understanding of Python data structures, including lists, dictionaries, and strings, and how to apply them in data-related tasks. The course is structured to start with the basics, introducing Python strings and methods before moving into more advanced topics like data structures and object manipulation. You will get hands-on experience with data operations in Python, including insertion, deletion, and slicing, followed by quizzes to reinforce the concepts learned. Throughout the course, you will practice problem-solving techniques and explore abstract concepts that enhance your ability to work with complex data structures in Python. This course is ideal for beginners in Python programming who are interested in data analysis and handling. No prior programming experience is required, but a basic understanding of mathematics and logic will be helpful. The difficulty level is beginner, making it accessible to anyone new to programming or Python. By the end of the course, you will be able to manipulate and handle data structures efficiently, apply string operations, and utilize Python libraries to create data visualizations. You will also gain the ability to solve complex data handling problems using Python.

In this module, we will introduce the course and give you a clear understanding of the topics we will cover. You’ll learn about the essential Python libraries such as NumPy, Pandas, Matplotlib, and more, which are critical for data handling and visualization. The module also sets expectations for the learning path and provides a roadmap for success.

What's included

4 videos2 readings

4 videos•Total 27 minutes
  • Introduction to the Specialization•12 minutes
  • Introduction to Instructor•2 minutes
  • Focus of the Course•4 minutes
  • Content of the Course•8 minutes
2 readings•Total 20 minutes
  • Introduction to the Course 'Python Foundations for Data Handling•10 minutes
  • Full Specialization Resources•10 minutes

In this module, we will explore Python’s string data type and how to manipulate strings using various methods. You’ll learn how to slice, index, and work with escape sequences to format and manipulate string data effectively. Practical quizzes will help reinforce your understanding of these core concepts.

What's included

11 videos1 assignment

11 videos•Total 63 minutes
  • Introduction to Strings•9 minutes
  • Multi-Line Strings•6 minutes
  • Indexing Strings•14 minutes
  • Indexing Strings Quiz•1 minute
  • Indexing Strings Solution•2 minutes
  • String Methods•15 minutes
  • String Methods Quiz•1 minute
  • String Methods Solution•2 minutes
  • String Escape Sequences•10 minutes
  • String Escape Sequences Quiz•1 minute
  • String Escape Sequences Solution•2 minutes
1 assignment•Total 15 minutes
  • Strings in Python - Assessment•15 minutes

In this module, we will dive into Python's essential data structures, such as lists, tuples, sets, and dictionaries. You’ll learn how to manipulate these structures using insertion, deletion, and slicing operations. Through practical exercises, you'll develop the problem-solving skills needed to work efficiently with Python data structures.

What's included

16 videos1 reading3 assignments

16 videos•Total 84 minutes
  • Introduction to Data Structure•7 minutes
  • Data Structures - Defining and Indexing•6 minutes
  • Data Structures - Insertion and Deletion•7 minutes
  • Data Structures-Insertion and Deletion Quiz•1 minute
  • Data Structures-Insertion and Deletion Solution•2 minutes
  • Data Structures - Insertion and Deletion Python Practice•7 minutes
  • Data Structures-Insertion and Deletion Python Practice Quiz•1 minute
  • Data Structures insertion And Deletion python Practice Solution•1 minute
  • Data Structures - Deep Copy or Reference and Slicing•8 minutes
  • Data Structures-Deep Copy or Reference and Slicing Quiz•1 minute
  • Data Structures-Deep Copy or Reference and Slicing Solution•2 minutes
  • Data Structures - Exploring Methods Using TAB Completion•7 minutes
  • Data Structures - Abstract Ways•7 minutes
  • Data Structures - Problem Solving Practice•19 minutes
  • Data Structures Problem Solving Practice Quiz•2 minutes
  • Data Structures-Problem Solving Practice Solution•5 minutes
1 reading•Total 10 minutes
  • Conclusion to the Course 'Python Foundations for Data Handling'•10 minutes
3 assignments•Total 90 minutes
  • Full Course Practice Assessment•15 minutes
  • Python Data Structure - Assessment•15 minutes
  • Full Course Assessment•60 minutes

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Frequently asked questions

Python Foundations for Data Handling is a course designed to help you master the foundational concepts in Python programming with a focus on handling data. The course introduces essential Python libraries such as NumPy, Pandas, Matplotlib, and others that are widely used in data analysis, data visualization, and geographical data handling. This course is relevant because data handling is crucial in various fields like data science, AI, business analysis, and many others, where the ability to manage and analyze data efficiently is key to making informed decisions.

This course is part of a specialization that provides you with a solid foundation in Python programming, particularly in handling and analyzing data. It covers fundamental concepts such as string manipulation, Python data structures, and the use of key libraries like Pandas for data manipulation and Matplotlib for data visualization. By the end of the course, you will have a clear understanding of how to work with data, visualize it, and perform basic data analysis tasks.

After completing the Python Foundations for Data Handling course, you will be able to use Python effectively for data manipulation and visualization. You will be proficient in working with strings, lists, dictionaries, and other data structures. Additionally, you will be comfortable using Python libraries such as Pandas, NumPy, Matplotlib, and others to analyze and visualize datasets. This skill set will help you in a variety of data-driven roles, such as data analyst, data scientist, or even in machine learning applications.

This course is designed for beginners with no prior programming experience, although basic familiarity with general computing concepts will be helpful. You don’t need any prior knowledge of Python, but a basic understanding of mathematics and statistics will help you grasp some of the concepts related to data manipulation and visualization.

This course is ideal for anyone looking to get started with Python programming for data-related tasks. It’s particularly beneficial for aspiring data analysts, data scientists, business analysts, or anyone interested in learning how to work with data using Python. Whether you are transitioning into a data-centric role or looking to enhance your technical skills, this course will equip you with the knowledge you need.

The course takes approximately 5 hours to complete. This includes video lectures, quizzes, and hands-on exercises designed to help you practice the concepts you’ve learned. The time may vary depending on your pace and prior knowledge of Python.

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

This course is currently available only to learners who have paid or received financial aid, when available.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,