Top 6 Python Courses on Coursera


Python, being in the boom, is encouraging students, current employees, and even everyone to learn it. And, of course, the large number of learning platforms available today will confuse you.

If you are searching for a high-quality Python course but are confused about which one to choose, you have landed on the right page. In this article, we will introduce you to the best python courses on Coursera. Coursera is a great education platform having beginner, intermediate, and even mixed-level courses.

Python for Everybody Specialization

This course will introduce you to the fundamental programming concepts of Python. It is a 100% online course with a flexible schedule. After the completion of every course in this specialization, you will earn a sharable certificate. You need to complete the hands-on project to earn this certificate.

There are 5 courses within this specialization:

  1. Programming for Everybody- This course teaches the basics of programming using Python. The course is divided into 7 weeks, and there is a new chapter introduced every week. This course provides excellent tutoring video lectures, reading material, and some additional material also.
  2. Python Data Structures- This course will introduce the core data structures of the Python programming language. This course is also partitioned into 7 weeks. Along with video lectures and reading material, you’ll get some quizzes, worked exercises, assignments, and many more benefits.
  3. Using Python to Access Web Data- This course will help you to scrape, parse, and read web data as well as access data using web APIs while working with HTML, XML, and JSON data formats in Python. It is divided into 6 weeks, and hence, 6 chapters are there.
  4. Using Databases with Python- This course will teach the basics of the Structured Query Language (SQL) as well as basic database design for storing data as part of a multi-step data gathering, analysis, and processing effort. The course is divided into 5 weeks (one chapter per week).
  5. Capstone: Retrieving, Processing, Visualizing Data in Python- Capstone is a final project. You’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization. It is divided into 7 chapters with 7 types of projects (one per week).

If you are giving 3 hrs/week to this course, you can complete the whole specialization in approximately 8 months.

Course NamePython for Everybody
TypeSpecialization
Rating4.8
Offered byUniversity of Michigan
InstructorCharles Russell Severance
LevelBeginner

If you are interested, click here to check the syllabus and course contents.

Crash Course on Python

This course is designed to teach you the basics of Python using the most common structures. This course will help you to write simple programs using Python and figure out how the building blocks of programming fit together. So if you are a complete beginner in Python, this is the course for you.

This is kind of a crash course that you can complete in approximately 32 hours. It is also a 100% online course with a flexible schedule. After the completion of this crash course, you will earn a sharable certificate.

This course is divided into 4 weeks with a chapter per week.

  1. Hello python– The course begins with an introduction week. This chapter introduces the Python programming language, automation using scripting, some functions, and keywords of the language. You’ll learn through video lectures, and besides that, you would have extra reading material and quizzes to test your skills.
  2. Basic Python– In this week, you’ll learn about syntax and data types of python and how to write the code. You’ll also learn about assigning data, functions, indentation, comments, operators, if statements, etc. Again, here you will have to pass the quizzes assigned.
  3. Loops– In this module, you’ll learn how to use and execute the loops in Python. You’ll also explore common errors when using for loops and how to fix them and how to use the range function with for loops.
  4. Strings, Lists and Dictionaries– In this module, you’ll learn about the ways to manipulate strings using indexing, slicing, and advanced formatting. You’ll also explore advanced data types: lists, tuples, and dictionaries. You’ll learn to manipulate data structures and how to combine them to store complex data.
Course NameCrash Course on Python
TypeCourse
Rating4.8
Offered byGoogle
InstructorGoogle Career Certificates
LevelBeginner

Click here to check the syllabus and course contents if you are interested.

Google IT Automation with Python

You will learn the in-demand technologies in this certification like- Python, Cloud, Git, IT Automation, etc. It is designed to teach Python and then how to use Python to automate common system administration tasks.

This course has a flexible schedule and is 100% online. After the completion of every course in this specialization, you will receive a sharable certificate. If you are giving 5 hrs/week to this course, you can complete the whole specialization in approximately 8 months.

There are 6 courses within this specialization:

  1. Crash Course on Python– This is the same course that we covered above. It is a part of this certification. You can either take this course separately or with this specialization.
  2. Using Python to interact with Operating System- In this course, you’ll learn to manipulate files and process them on your computer’s operating system.
  3. Introduction to Git and GitHub– By touching the latest technologies, this course will teach you how to keep track of the different versions of your code and configuration files using a popular version control system (VCS) called Git. It will help you learn how to create and manage an account on GitHub.
  4. Trobleshooting and Debugging Techniques– When it comes to programming, you always need tools to quickly identify and solve real-world problems. Thus, in this course, you’ll learn about strategies for solving technical problems and how to approach real-world scenarios.
  5. Configuration Management and the Cloud– In this course, you’ll understand how to automate the process for deploying new computers, keeping those machines updated, managing large-scale changes, and a lot more.
  6. Automation Real-World tasks with Python– This course would be the conclusion and implementation of everything you have learned so far. You’ll learn to tackle real-world scenarios in Qwiklabs and will also learn external Python modules.
Course NameGoogle IT Automation with Python Professional Certificate
TypeProfessional Certificate
Rating4.7
Offered byGoogle
InstructorGoogle Career Certificates
LevelBeginner

If you are interested in this course, click here to check the syllabus and course contents.

Applied Data Science with Python Specialization

This specialization is meant for learners having a background in Python programming basics, and want to apply statistics, machine learning, information visualization, text analysis, and social network analysis techniques.

You will get introduced to pandas, matplotlib, scikit-learn, nltk, etc. This 100% online course comes with a flexible schedule.

After completing each course in this specialization, you will get a sharable certificate, if you can complete the hands-on projects. If you are giving 7 hrs/week to this course, you can finish the entire specialization in about 5 months.

There are 5 courses within this specialization:

  1. Introduction to Data Science in Python- This course covers the basics of Python programming, including lambdas, reading and manipulating CSV files, NumPy library, etc. This course will also introduce the Pandas library, and students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.
  2. Applied Plotting, Charting and Data Representation in Python– This course focuses on reporting and charting using the matplotlib library. You’ll learn to create basic statistical charts and realize design decisions in the framework.
  3. Applied Machine Learning in Python– This course focuses more on the techniques and methods than on the statistics behind these methods. You’ll learn about Machine Learning and will be introduced to the scikit learn toolkit through the tutorials.
  4. Applied Text Mining in Python– You’ll learn text mining and text manipulation basics in this course. The course covers how text is handled by python, the structure of text both to the machine and to humans, an overview of the nltk framework for manipulating text, regular expression, cleaning text, and preparing text so that it can be used by machine learning processes.
  5. Applied Social Network Analyses in Python- In this course, you’ll learn about network analysis through tutorials using the NetworkX library.
Course NameApplied Data Science with Python
TypeSpecialization
Rating4.5
Offered byUniversity of Michigan
InstructorChristopher Brooks
LevelIntermediate

If you are interested, click here to check the course contents and syllabus.

Deep Learning Specialization

In this specialization, you will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers using Python and TensorFlow. You’ll tackle real-world problems such as speech recognition, machine translation, music synthesis, natural language processing, chatbots, and more.

This course has a flexible schedule. Once you complete each course in this specialization, you will earn a sharable certificate. The hands-on project needs to be completed to earn this certificate. If you can allocate 7 hrs/week to this course, you would be able to complete this specialization in just 5 months.

There are 5 courses within this specialization:

  1. Neutral Networks and Deep Learning– This course is an introduction to neural networks and deep learning.
  2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization- You’ll learn how to train and develop test sets and analyze bias/variance for building deep learning applications.
  3. Structuring Machine learning projects– This course focuses mainly on hands-on exercises. You’ll be building a machine learning project based on whatever learned so far.
  4. Convolutional Neural Networks– This course will help you build a convolutional neural network from scratch.
  5. Sequence Models– In this course, you’ll be able to build and train Recurrent Neural Networks.
Course NameDeep Learning Specialization
TypeSpecialization
Rating4.8
Offered byDeepLearning.AI
InstructorAndrew Ng
LevelIntermediate

Click here to check the course contents and syllabus on Coursera.

AI for Everyone

This is a basic course about AI. It’s not a practical tech course. You can take this course even if you are not a techie. This is kind of a crash course that you can complete in approximately 7 hours. You will earn a sharable certificate after completion.

This course is divided into 4 weeks i.e., 4 chapters:

  1. What is AI – In this chapter, you will get introduced to AI and Machine Learning with the help of some video lectures and quiz.
  2. Building AI Projects- In this chapter, you will understand the workflow of AI projects and will practice hands-on.
  3. Building AI in your company – In this lesson, you will learn about AI using case studies, real-world examples, and quizzes.
  4. AI and Society– This will give you a realistic view of the topic, some practice exercises, quizzes, videos and reading material.
Course NameAI For Everyone
TypeCourse
Rating4.8
Offered byDeepLearning.AI
InstructorAndrew Ng
LevelBeginner

If you are interested, click here to check out the course contents and syllabus.

Final Thoughts

These are some of the premium-quality courses available on Coursera. If you are planning to buy an online course, check them out and choose the one that suits you. Thanks for reading!

Ashwin Joy

I'm the face behind Pythonista Planet. I learned my first programming language back in 2015. Ever since then, I've been learning programming and immersing myself in technology. On this site, I share everything that I've learned about computer programming.

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