Learning Python was really challenging for me, but it didn’t have to be.
I graduated college with a history degree and no job prospects a little over ten years ago. Later on, I established myself as a respected machine learning engineer, data science consultant, and eventually the company’s chief executive officer.
However, this achievement did not happen instantly. The process of learning Python was tedious, time-consuming, and disheartening for me.
If I had my time over, I’d do things the way I’m about to explain to you. It would have helped me advance in my job much more quickly, save me countless hours of unnecessary work, and relieved a great deal of pressure.
If you want to learn Python properly, this book will show you how.
The First Step Is Realizing Why Most Fail
There is no need to make the effort to learn Python. In fact, if you have access to the correct tools, it may be really simple (and even enjoyable).
The Issue with Most Educational Materials
The learning curve for Python is artificially inflated in many of the available courses. I’ll use anecdote to make my argument clear.
I wanted to use Python for the things that interested me, like building websites, when I initially started studying it. The course I was taking unfortunately required me to devote a significant amount of time to studying syntax. It hurt like hell.
Python programming remained alien and puzzling during the entire course. It sounded completely foreign. It’s not surprising that I got bored rather quickly.
Unfortunately, the vast majority of Python guides seem quite identical to this one. They presume you need to master all of Python syntax before you can start doing anything interesting. Is it any wonder most people give up?
If you want to have fun with Python, you shouldn’t waste your time on boring jobs like these. Consider the use of AI in tasks such as data mining, web development, and the design of a self-flying drone.
Many attempts later, I finally landed on a method that yielded satisfactory results for me. In fact, I think this is the most effective method for learning Python.
As a first step, I invested minimal effort on committing Python syntax to memory. Then I applied what I had learnt to a task that genuinely interested me.
If you follow the instructions below, you’ll have a blast while also accelerating your learning.
In fact, I created Dataquest to facilitate this superior method of education. With our data science courses, you may skip the tedious details and jump right into project development. Examine the lessons we offer here. Costs nothing to join up.
The second step is to figure out what drives you.
The good news is that if you put in the time and effort, anyone can become very proficient with Python.
When I was first starting out, it was hard for me to stay up and memorize syntax. On the other hand, I didn’t mind staying up late to complete an intriguing project in which I used Python foundations.
What’s the lesson here? You need to uncover what motivates you and get passionate about it! Select one or two foci of interest to pursue initially.
- Science of Data and Automatic Learning
- Mobile software
- Science of Computers
- Analyzing Data and Processing It
- Machines, Sensors, and Robots
- Work Process Automation
The Python language can be used to create robots. Straight out of the Raspberry Pi Cookbook.
Step 3: Quickly Acquire the Necessary Syntax
I understand. We’ll spend minimal time on syntax, like I promised. This is a necessary but inconvenient procedure that cannot be avoided.
If you want to learn Python but are having trouble staying motivated, check out these helpful resources:
To simplify the process of learning Python and data science, I created Dataquest, an introductory programming course written in Python. Dataquest provides a framework for learning Python syntax within the context of data science. By studying meteorological data, for instance, you’ll be exposed to fundamental Python commands.
You may learn Python, from the fundamentals to more advanced programming, with this book.
The Python Tutorial – The official Python documentation and tutorial site.
I can’t stress this enough: Master the syntax you’re comfortable with and go on. Ideally, you will spend a couple of weeks on this phase, but no more than a month.
The sooner you can begin applying what you learn, the more quickly you will progress. If you forget the syntax, you can always look it up again.
As a quick reminder, you should be studying Python 3. Many online “learn Python” resources, alas, are stuck in the past and only offer instruction in Python 2. However, as Python 2 is no longer maintained, any vulnerabilities it may have will remain unpatched.
Fourth, develop well-organized projects.
Start working on projects once you have a firm grasp of Python’s fundamental syntax. Applying your information immediately away will assist you recall everything you’ve studied.
Before venturing out on your own, it’s best to gain experience with structured assignments. Here at Dataquest, we’ve incorporated structured projects into nearly all of our Python courses for pedagogical purposes. That way, you may put your new knowledge to use right away.
Some completed Dataquest assignments are displayed below. Which one makes you the most curious?
You may learn how to install Jupyter locally and run Python code in a Jupyter Notebook.
Have some laughs by building a real, playable, and interactive word guessing game in Python.
Making an App for Ordering meals — Use Python to build a fully-featured, user-friendly app for ordering meals.
Fans of the Star Wars franchise won’t want to miss this organized initiative based on actual data from the film, which aims to clean and visualize that data.
Use a machine learning pipeline to make accurate price predictions for automobiles.
Discover the ins and outs of training a machine learning model for weather forecasting.
Exploring eBay automobile Sales Data: Analyze and clean a real dataset regarding automobile sales from eBay.
Construct a k-nearest neighbors classifier to assess a patient’s likelihood of developing heart disease.
Motivation for Organized Tasks
There is no “best” way to initiate a structured project. What drives you, and what you hope to achieve, will determine the ideal resources for you while you learn Python.
Do you want to learn more about data science and machine learning in general? Do you have a particular website or app in mind that you’d want to create? Some places to look for ideas are listed below, broken down by topic:
- One type of game that can be created with Pygame. This is version 1.0 of Phil Hassey’s Barbie and the Seahorse Adventures.
- Integration of Python and Arduino: Use Python to manage Arduino-connected sensors.
- How to Use a Raspberry Pi and Python to Create Your Own Hardware Projects.
- How to Use Python for Robot Construction is a Guide to Learning Robotics.
- Robotics with the Raspberry Pi and Python: A Cookbook is a great way to learn the ropes.
- Workflow Automation Scripts
- Learn Python to Automate Your Life and save time on mundane things.
- There must be projects. They challenge you to grow as a developer, introduce you to novel areas of Python, and give you an opportunity to highlight your skills to prospective employers. You can go on to more independent work after completing a few organized assignments.
The Fifth Step: Independently Develop Python Applications
Once you’ve completed a few well-defined projects, you can increase the pace. Independent Python projects are a great way to accelerate your education.
Here’s the trick: tackle a simple task first. It’s preferable to complete a modest undertaking than to begin a massive one and fail to see it through to completion.
How to Find Interesting Python Projects: 8 Suggestions
I understand how challenging it may be to zero in on a worthwhile Python endeavor.
- Extend the projects you were working on earlier and add extra functionality.
- Learn more about Python using our collection of starter projects.
- Find local Python meetups and introduce yourself to folks working on cool stuff.
- Discover open-source projects that might use your help.
- Check with local charities to see if they have a need for volunteer programmers.
- Try to build upon or modify existing projects that have already been created. You should probably begin on Github.
- Read the blogs of other individuals in your field to be inspired.
- Imagine gadgets that would simplify your routine. Create them, then.
- 17 Concepts for New Python Tasks
- Want some more ideas? To further spark your imagination, consider the following:
Ideas for Data Science and Deep Learning-Based Projects
A state-by-state election polling map
Predictive algorithm for regional climate
Financial market forecasting instrument
A computer program that can synthesize concise summaries of news articles
- Create an interactive take on this map first found on RealClearPolitics.
- Conceptualization of Mobile Apps
- A mobile application that logs the daily mileage you walk
- A mobile application that alerts you to weather changes
- An instant, geo-specific conversation
- Ideas for a Website Project
- A web resource for weekly menu preparation
- A platform where players may rate and comment on video games
- A place to take notes
- Ideas for a Python Game Project
- A mobile game played by moving about and seizing different areas.
- Puzzle-solving in which code is the primary tool
- Ideas for a Hardware/Sensor/Robot-Related Project
- Wireless home security sensors
- A more advanced alarm clock
- An autonomous robot with obstacle detection
Web data extraction software
The important thing is to just start doing something. The risk of never starting a project exists if you spend too much time trying to locate the ideal one.
My first solo effort involved porting my R-based essay-grading method to the Python programming language. It wasn’t a lovely finished product, but it helped me feel accomplished and launch my skill development.
Keep in mind that problems will arise. There will be bugs and mistakes in your code as you create your project. Please find some useful links below.
Here Are the Top 3 Places to Turn When You’re Stuck in Python
Don’t give in to defeat.
StackOverflow is a QA website dedicated to programming questions and answers. You may find Python-specific questions here.
Google: the primary resource of every professional software developer. Invaluable for figuring out what went wrong. Here’s a case in point.
Python’s official documentation is a great resource for learning more about Python.
Sixth, continue to take on increasingly difficult tasks.
If you’re good at working on your own, keep challenging yourself by taking on bigger and more ambitious tasks. You’ll need to keep up your motivation if you want to learn Python.
When you’ve reached a point of confidence in your constructions, you can go on to more challenging projects. If you want to develop your abilities and learn new things, you need to keep taking on new challenges.
Python: Five Practice Exercises
When that moment comes, consider these options:
Just try breaking down your plans for a complete newcomer.
Determine if your tool can be scaled. Can it process more datasets or deal with higher volumes of users?
Make an effort to speed up the program.
Think about how you could expand the audience for your tool.
Think about the best way to sell your product.
Moving Python Forward
Keep in mind that Python is ever-changing. Few people can say they have a firm grasp of Python’s intricacies. These are the persons responsible for making it.
What are your options now? Always expanding your knowledge and honing your abilities by taking on new challenges.
You’ll probably feel bad about the quality of your code when you look back on it in six months. Have hope! When you reach this milestone, you’ll know you’re heading in the correct direction.
You have everything you need to get going if you’re the type of person who does well with little guidance. However, our courses may be useful if you require a bit more direction.
When I set out to help individuals learn more efficiently and stay away from roadblocks, I came up with the idea for Dataquest. Within minutes, you’ll be creating code and completing projects from scratch.
Learn Python for business analysis, data analysis, data engineering, or data science with our career tracks that take you from zero to expert in as little as a few months. Alternatively, you can test out our beginner Python course right here to see if it’s right for you.
Standard Python Queries
Is it difficult to study Python?
The learning curve for Python can be steep. If you follow the procedure I’ve given here, however, you’ll find that it’s far simpler than you might have anticipated.
How much does it cost to learn Python?
Many excellent Python tutorials may be found for no cost online. For instance, here at Dataquest, you may access dozens of Python tutorials at no cost. Our data science learning platform is free to join and features an interactive interface.
One drawback of a free education is that it often requires piecing together different free resources. This implies you’ll have to put in more time investigating your next course of study and potential methods of doing so.
Some of the educational features of paid platforms (like Dataquest’s in-browser coding tutorials) may be superior to those of free ones. They also save you the time of having to discover and develop your own curriculum.
Can you start from scratch (i.e., with no prior coding expertise) and learn Python?
Yes. Python is an excellent language for those who have never written any code before because it is easy to learn. Students who have no background in coding can learn the skills they need to succeed in the growing field of data analytics with the help of Dataquest.
How much time do you need to master Python?
As with acquiring a spoken language, a programmer’s education is never complete. Due to the dynamic nature of language, there is always something new to study. Even so, it doesn’t take long to become proficient at developing Python code that serves its intended purpose.
When will I be ready to start working? What you want to accomplish, what kind of work you want to do, and how much time you have available to study are all factors.
We surveyed Dataquest students in 2020, and they said they were able to complete the course in under a year. A lot of people managed to do it in under a year. That’s with only ten hours of studying a week at most.
Just how can I speed up my Python education?
If you want to study Python for a specific purpose (say, game development or data analysis), you should look for a platform that teaches that purpose (or create your own curriculum).
That way, you won’t have to waste time studying Python features that aren’t directly applicable to your job.
Is a Python certification required to get a job?
Not likely at all. In data science, certifications don’t carry much weight. Skills, not degrees, are what matter most to potential employers.
Translation? A GitHub full of amazing Python code is considerably more important than a certificate.
Is Python 3 better than Python 2?
The clear winner is Python 3. This was still up for discussion just a few years ago. Despite the claims of fanatics, Python 3 has not “killed Python.” Python 3 is the de facto standard today.
Do other fields besides data science and machine learning find Python useful?
Yes. Python is widely utilized in the professional world because to its popularity and adaptability.
Python is a core component of our data science and ML curriculum. However, you can put your knowledge of Python to use in various contexts. Financial services, website creation, software engineering, video game design, and more all make use of it.
Python data analysis skills are transferable and may be applied in many different contexts. If you work with spreadsheets, for instance, chances are there are things you could be doing faster and better with Python.
Python’s applicability is virtually limitless. Get on board the revolution train. Ready to get started? Find out how Dataquest’s online Python courses might benefit you and sign up right away for free.