Python For Everybody Specialization Review
Intro
Table of Contents
"Python for Everybody" is one of the most popular MOOC specializations. It will introduce you to fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. But, enrolling and studying in the program is a big commitment. In this guide, I will explain the program details, the pros and cons, and the next steps ahead.
You should read this guide before you join any Python online course but if you are in a hurry and want a quick Yes/No answer on whether you should join this Coursera specialization or not then the answer is Yes, by all means, you should go for it.
This is one of the most comprehensive Python courses on Coursera and covers all the necessary areas like basics, data structure, database, web scrapping with python, and much more. More than 750K people have already joined this course which is also big proof of its quality.
Many people say that learning a programming language can be a difficult task and can take months and months to learn even the basics so then you start developing your own products whether it was a web service or a mobile app but what if I say that there is a language that can be learned in a few weeks and that language called python.
We even conducted a cohort on some of the courses from this specialization:
In this post, I will give a review of the “Python for Everybody” Specialization. Specifically, I will talk about the following points:
1. The courses
2. The Projects
3. Prior Requirements
4. Duration
5. The Pros
6. The Cons
7. What to study next
1. The Courses
The entire specialization consists of 4 courses + 1 Capstone Project.
1. Programming for Everybody (Getting Started with Python):
This course aims to teach everyone the basics of programming computers using Python. You will learn the basics of how one constructs a program from a series of simple instructions in Python. The course has no prerequisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. It’s an easy-to-learn MOOC with minimum requirements, acting as the perfect step to get started.
2. Python Data Structures:
This course will introduce the core data structures of the Python programming language. You 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. If you ever felt intimidated by Data Structures, then you don’t have to anymore! This MOOC provides a very student-friendly introduction to Data Structures.
3. Using Python to Access Web Data:
This course will show how one can treat the Internet as a source of data. You will scrape, parse, and read web data as well as access data using web APIs. You will work with HTML, XML, and JSON data formats in Python. This is where you finally step away from the basics of Python programming, and get into application. Accessing web data is such an important skill. In addition, learning how to use APIs will also give you a push in your software learning journey.
4. Using Databases with Python:
This course will introduce you to the basics of 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 will use SQLite3 as its database. You will also build web crawlers and multi-step data gathering and visualization processes. You will use the D3.js library to do basic data visualization.
Just like the previous course, this course application-oriented. In this course, you will use Python for data analytics - you will perform data cleaning, fetching, and some exploratory analysis. Again, good MOOC for getting started with Analytics.
5. Capstone Project- Retrieving, Processing, and Visualizing Data with Python: In the capstone, you will build a series of applications to retrieve, process and visualize data using Python. The projects will involve all the elements of the specialization. In the first part of the capstone, you will do some visualizations to become familiar with the technologies in use and then you will pursue your own project to visualize some other data that you have or can find. Note: Technically, you can finish this course (and obtain the certification) solely for solving 1 quiz. But, in order to make the most of this program, I’d encourage you to complete their “Honors Track” projects as well.
2. The Projects
In the capstone MOOC, you will build 3 main projects:
1. Building a Search Engine:
You will download and run a simple version of the Google PageRank Algorithm. The course creators will provide you with sample code and lectures that walk through the sample code. In this project, You will be able to spider some simple content that the creators provide and then play with the program to spider some other content. Part of the fun of this assignment is when things go wrong and you figure out how to solve a problem when the program wanders into some data that breaks its retrieval and parsing. So you will get used to starting over with a fresh database and running your web crawl.
2. Spidering and Modeling Email Data:
In this project, you will download, process, and visualize an email corpus from the Sakai open-source project from 2004-2011. This is a data analytics project, where you will crawl, clean, model, and visualize email data.
3. Visualizing Email Data:
In the last project, you will visualize the email data. Specifically, you will create a word cloud. While a word cloud might seem a little silly and over-used, it is actually a very engaging way to visualize a frequency distribution or histogram In addition, you will show how the data is being changed over time.
3. Prior Requirements
This specialization is meant for beginners. I believe this is a great course if you are completely new to programming. It’s also a great fit for CS students, who just learned C/C++ in college, and now want to learn Python.
If you are learning programming for the first time, then this program is a great fit for you. Engaging videos, experienced and humorous instructors, and plentiful programming exercises - this program has it all!
4. Duration
This is completely subjective - depending on your prior background, and current schedule. But, I’d say it’ll take you 2-3 months to finish the entire specialization. Sure, some learners will take less time, and some more. This is just an estimate.
The program is not super demanding - you can expect to spend 3-4 hours every week to complete the entire program on time.
5. Why we love this Specialization (The Pros)
1. Beginner Friendly: As mentioned, this specialization is a great way to get started with your coding journey. You actually learn quite a few intermediate topics throughout the course: Data Structures, APIs, working with Databased, and Data Analytics.
2. Program Structure: The instructors have divided the entire syllabus into 4-5 courses. Each course is roughly around 4 weeks. And, in each week, you have <1 hour of primary learning content. I love this breaking down of content, makes it really easy to digest and learn. You also receive optional content (like “office hours”) which is more conversation-based.
3. Free and accessible: I love the fact that the instructor has shared the MOOC content in several ways for free. You can access the content on Coursera, on FreeCodeCamp’s YT Channel, through the free ebook, or through the custom learning website.
Note, you can submit all your coding assignments on their customer learning website for free. But, you won’t find the capstone project there. On the other hand, you can audit the courses on Coursera for free (here’s how). But, in order to submit your work and access the Capstone, you will need to pay a fee.
6. The Cons (Kinda)
This is a great program, and honestly, I don’t have a strong reason why you shouldn’t consider this program. However, I will say that this specialization does not provide sufficient depth in Python, or DSA, or Data Analytics. Some of our Moocable members have found this program too easy, and thus, not engaging our useful enough.
So, if you are looking for an in-depth program, I would suggest that you pursue another program. Of course, if you are completely new to Python, then first study this program and then move to another program.
7. What to study next?
A common question members ask is “what to study next” or “what to study instead?”. These are my suggestions:
1. If you are looking for an intermediate MOOC on Python (after completing this Specialization), you can check out: -
Python Programming MOOC 2022 by University of Helsinki.
This program provides more depth and covers more intermediate topics in Python Programming.
2. If you have a good Python foundation, and want to focus on applications, then you can check out:
- For Web Dev: Django for Everybody Specialization
- For Data Analytics: Applied Data Science with Python Specialization
- For Automation: Automate the Boring Stuff with Python
