Python Data Structures Course Reviews

This course is designed for beginners who have little or no prior programming experience.

The course covers fundamental data structures such as lists, dictionaries, and tuples, and also explores how to manipulate and work with data structures in Python. Topics covered include sorting algorithms, searching algorithms, and how to use regular expressions in Python.

Throughout the course, students will complete programming assignments to reinforce their understanding of the material. The course also includes quizzes and peer-graded assignments to assess students' knowledge.

Upon completing the course, students will have a solid understanding of basic data structures in Python and be able to write basic Python programs.

Course Content:

This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis. This course will cover Chapters 6-10 of the textbook “Python for Everybody”. This course covers Python 3.

The Python Data Structures course on Coursera, created by Charles Russell Severance, consists of 7 modules of content. Each module contains a series of video lectures, readings and programming assignments to reinforce learning.

Here is a detailed breakdown of the course content:

Module 1: Chapter Six: Strings (7 videos + 8 readings)

In this class, we pick up where we left off in the previous class, starting in Chapter 6 of the textbook and covering Strings and moving into data structures. The second week of this class is dedicated to getting Python installed if you want to actually run the applications on your desktop or laptop. If you choose not to install Python, you can just skip to the third week and get a head start.

Module 2: Unit: Installing and Using Python (5 videos + 2 readings)

In this module you will set things up so you can write Python programs. We do not require installation of Python for this class. You can write and test Python programs in the browser using the "Python Code Playground" in this lesson. Please read the "Using Python in this Class" material for details.

Module 3: Chapter Seven: Files (5 videos + 1 reading)

Up to now, we have been working with data that is read from the user or data in constants. But real programs process much larger amounts of data by reading and writing files on the secondary storage on your computer. In this chapter we start to write our first programs that read, scan, and process real data.

Module 4: Chapter Eight: Lists (7 videos)

As we want to solve more complex problems in Python, we need more powerful variables. Up to now we have been using simple variables to store numbers or strings where we have a single value in a variable. Starting with lists we will store many values in a single variable using an indexing scheme to store, organize, and retrieve different values from within a single variable. We call these multi-valued variables "collections" or "data structures".

• 8.1 - Lists•10 minutes•Preview module
• 8.2 - Manipulating Lists•9 minutes
• 8.3 - Lists and Strings•7 minutes
• Fun: Python Lists in Paris•0 minutes
• Worked Exercise: Lists•11 minutes
• Bonus: Office Hours - Chicago•0 minutes
• Bonus: Rasmus Lerdorf - Inventing the PHP Language•7 minutes

Module 5: Chapter Nine: Dictionaries (7 videos)

The Python dictionary is one of its most powerful data structures. Instead of representing values in a linear list, dictionaries store data as key / value pairs. Using key / value pairs gives us a simple in-memory "database" in a single Python variable.

• 9.1 - Dictionaries•9 minutes•Preview module
• 9.2 - Counting with Dictionaries•11 minutes
• 9.3 - Dictionaries and Files•13 minutes
• Worked Exercise: Dictionaries•24 minutes
• Bonus: Office Hours - Amsterdam•3 minutes
• Bonus: Brendan Eich - Inventing Javascript•11 minutes
• Fun: Dr. Chuck Goes Motocross Racing•2 minutes

Module 6: Chapter Ten: Tuples (6 videos)

Tuples are our third and final basic Python data structure. Tuples are a simple version of lists. We often use tuples in conjunction with dictionaries to accomplish multi-step tasks like sorting or looping through all of the data in a dictionary.

• 10 - Tuples•17 minutes•Preview module
• Worked Exercise: Tuples and Sorting•10 minutes
• Bonus: Office Hours - Puebla, Mexico•1 minute
• Bonus: John Resig - Inventing JQuery•10 minutes
• Douglas Crockford: JavaScript Object Notation (JSON)•7 minutes
• Fun: The Greatest Taco in the World•2 minutes

Module 7: Graduation (2 videos + 3 readings)

To celebrate your making it to the halfway point in our Python for Everybody Specialization, we welcome you to attend our online graduation ceremony. It is not very long, and it features a Commencement speaker and very short commencement speech.

Reviews:

The Python Data Structures course by Charles Russell Severance on Coursera has received generally positive reviews from past learners. Many have praised the course for its comprehensive coverage of Python programming language and its applications in data structures and file handling.

Learners appreciate the instructor's teaching style, which is described as clear, concise, and engaging. Many learners have noted that the instructor's use of practical examples and programming assignments helps to reinforce their understanding of the material and allows them to apply their knowledge to real-world problems.

The course content is also well-organized and covers a broad range of topics related to data structures, file handling, and database applications in Python. The course includes weekly programming assignments and quizzes to help learners reinforce their knowledge and test their understanding of the material.

However, some learners have noted that the course may be challenging for those who are new to programming or have limited experience with Python. Some of the programming assignments and quizzes can be difficult, and learners may need to spend additional time outside of the course to grasp some of the concepts.

Despite this, the course is highly recommended for those who are looking to expand their knowledge of Python programming language and its applications in data manipulation and analysis. The course has been praised for its relevance and applicability to real-world scenarios, and many learners have reported that the skills they acquired in the course have helped them in their professional careers.

Another strength of the course is the instructor's teaching style. Charles Russell Severance is an engaging and knowledgeable instructor who clearly has a passion for teaching programming. He has a talent for explaining complex concepts in a way that is easy to understand, and he is always willing to help students who are struggling with the material.

Overall, the Python Data Structures course by Charles Russell Severance on Coursera is a well-designed and comprehensive course that provides learners with the knowledge and skills needed to work with data structures and file handling in Python. The course is suitable for learners with some prior programming experience who are looking to expand their knowledge of Python for data manipulation and analysis.

At the time, the course has an average rating of 4.9 out of 5 stars based on over 92,135 ratings.

What you'll learn:

Upon completing the Python Data Structures course on Coursera, created by Charles Russell Severance, learners will have acquired the following skills:

1. Basic programming skills in Python: Learners will have a good understanding of Python programming language, including how to use variables, expressions, conditional statements, functions, loops, and data structures. They will learn how to write simple programs to solve basic programming problems, and how to debug and test their code.

2. Data structures in Python: Data structures are an essential component of programming, and the course covers several of the most commonly used data structures in Python, including strings, lists, dictionaries, and tuples. Learners will learn how to create, manipulate, and iterate over these data structures, and how to select the appropriate data structure for different programming problems.

3. Functions in Python: Functions are a powerful tool for organizing code and reducing redundancy. The course covers how to define and call functions, pass arguments, and return values. Learners will also learn about the scope of variables and how to debug functions.

4. File handling in Python: Reading and writing data to and from files is an essential task for many programming applications. The course covers how to open, read, and write to files in Python, and how to search for and manipulate data within a file.

5. Web data retrieval using Python: Web scraping and using APIs to retrieve data from websites is a crucial task in many programming projects. The course covers how to use Python to connect to websites, retrieve and parse data from websites using BeautifulSoup, and work with XML and JSON data formats.

By the end of the course, learners will have acquired a strong foundation in Python programming, data structures, file handling, and web data retrieval, enabling them to apply their skills in various programming projects and scenarios.

Author:

Charles Russell Severance is an American computer science professor and author who has made significant contributions to the field of online education. He was born on February 21, 1956, in the United States.

Severance is a clinical professor at the University of Michigan School of Information and teaches various courses on database systems and web application development. He is also the author of several textbooks on these subjects, including "Python for Everybody" and "Using SQLite."

Severance is perhaps best known for his contributions to the field of online education. He has been involved in the development of several massive open online courses (MOOCs) on platforms such as Coursera and edX. These courses have been widely popular and have reached millions of learners around the world.

Severance is known for his engaging teaching style and his ability to explain complex concepts in an accessible manner. He is a passionate advocate for open education and has played a significant role in making high-quality education accessible to people around the world.

Overall, Severance is a highly respected and accomplished computer science educator and author. His contributions to the field of online education have been invaluable, and his expertise in database systems and web application development has been widely recognized.

Requirements:

The Python Data Structures course by Charles Russell Severance on Coursera has the following requirements for learners:

1. Basic programming knowledge: Learners are expected to have basic programming knowledge, including variables, loops, functions, and conditionals.

2. Basic knowledge of Python: Learners should have a basic understanding of Python programming language, including data types, operators, and basic syntax.

3. Access to a computer: Learners should have access to a computer with a stable internet connection.

4. Python interpreter: Learners are required to have access to a Python interpreter to complete the programming assignments and quizzes.

5. Text editor: Learners should have a text editor installed on their computer to write and edit Python code.

6. Commitment: The course requires learners to commit to completing the weekly programming assignments and quizzes.

7. Time management: Learners should be able to manage their time effectively to complete the course within the given timeframe.

8. Self-motivation: Learners should be self-motivated and willing to learn new concepts and programming techniques.

Overall, the course requires learners to have a basic understanding of programming and Python, access to a computer and Python interpreter, and the ability to commit to the weekly programming assignments and quizzes. Learners should also have good time management skills, self-motivation, and a willingness to learn new concepts and programming techniques.