Python Developer Learning Roadmap 2021

Python Learning Roadmap 2021: Because of its extreme flexibility, Python is one of the most popular programming languages among data scientists, software engineers, and developers. Python is a general-purpose, interpreted programming language. Python can be used for a variety of tasks, including software development, web development, web scraping, data research, machine learning, artificial intelligence, competitive programming, and more. Python is the most sought-after language to learn in 2021, and it’s no surprise given its versatility.

Our custom-made Learning Paths will take your Python skills to the next level with an accelerated, hands-on study plan, whether you’re a beginner, intermediate, or advanced Pythonista.

You’ll find your way through the entire Python curriculum, so you’ll always know what to focus on next.

Why become a Python developer?

There are various reasons why studying Python should be the first step in your programming career. For starters, Python is simple to learn and read, with a basic grammar. Beginners and intermediate programmers both will find it simple to master the language. Second, Python is a general-purpose programming language with strong analytical capabilities and a large library of useful tools. Python’s flexibility allows a programmer to devote more time to the creation of various applications.

My favorite language for maintainability is Python. It has simple, clean syntax, object encapsulation, good library support, and optional named parameters.

– Bram Cohen (author of the peer-to-peer (P2P) BitTorrent protocol)

Python helps programmers to write fewer lines of code for programs that might otherwise require more lines in other languages. Python programs, for example, are slower than Java programs, but they also take far less time to develop because Python scripts are three to five times shorter. Some point are given below:

  1. Python is open-source and is free to use across all operating systems
  2. It is the most productive language
  3. You can do several things with Python
  4. Python has a vast and active community
  5. It has hundreds of built-in libraries and frameworks

Python is used by companies such as Google, Facebook, Netflix, IBM, and many others for a variety of jobs including software development, machine learning, web development, and more. Given Python’s growing popularity, it’s easy to see how beneficial it is to learn Python.

How to become a Python developer?

First, we will start with some essential skills and computer fundamentals you will require to become a Python developer —

Stage 1 — Computer Fundamentals

1.Git

One of the most widely used version control systems is Git. Git is an open-source, free program that may be used to track changes in a set of files, as well as build and manage source code during software development. Please see the resources below to learn more about Git —

  1. Version Control with Git (Coursera)
  2. Version Control with Git (Udacity)
  3. Learn Git (Codecademy)
  4. Git Documentation
2. Linux Command Line Basics

For any coder, learning the Linux command line is also important. I recommend that you spend some time understanding the fundamentals of these commands. If you want to be a Python developer, these commands will come in helpful. These free resources can assist you in learning more about Linux Commands —

  1. The Linux command line for beginners (Ubuntu)
  2. Linux Command Line Basics (Udacity)
3. GitHub

Isn’t it true that almost every recruiter nowadays requests a GitHub profile? It’s a great location to start building your online portfolio and showcase your abilities. A GitHub profile will help you stand out from the crowd. When you apply for competitive roles like data scientist, machine learning engineer, web developer, or Python developer, the first thing recruiters will look at is your GitHub profile. It gives recruiters an overview of your coding ability, problem-solving capabilities, and problem-solving technique. If you have a well-maintained, up-to-date GitHub profile, you have a better chance of standing out.

Without a question, knowing how to use GitHub is a valuable skill that will help you advance professionally. GitHub is used by millions of developers to share their work and create an online portfolio. Please take a look at the following free courses to learn more about GitHub:

  1. Introduction to Git and GitHub (Coursera)
  2. GitHub Learning Lab (GitHub)
  3. GitHub Ultimate: Master Git and GitHub — Beginner to Expert (Udemy)

Stage 2: —Python Basics

We’ll go on to learning the fundamentals of Python programming once we’ve completed the Computer Programming Fundamentals. These are the topics you should study in order to master Python’s fundamentals —

  1. Hello World with Python 3
  2. Basic Syntax
  3. Code Editors like Vim, Jupyter Notebook, Google Colab, Atom.
  4. Indentation
  5. Loops, Logical Operators
  6. Data types and Variables
  7. Operators
  8. Strings and Numbers
  9. Conditional statements and type conversion
  10. Functions and Built-in Functions

1. What to Learn in Python?

  • Learn the basics. Learn about its history, syntax, installation, and some basic constructs like statements, variables, and operators.
  • Find out about the applications of Python. Also, understand the differences between Python 2 and Python 3.
  • Learn about basic data structures like lists, sets, and dictionaries.
  • Understand important concepts like decision making and loops.
  • Learn how to create a virtual environment.
  • Move on to functions and recursion.
  • Get started with object-oriented concepts like classes and methods, and inheritance and overloading.
  • Find out about modules and packages, and get some experience with common modules like os, namedtuple, and calendar.
  • Learn file handling. Learn about more complex topics like generators and decorators, and shallow and deep copying.
  • Also, learn to generate and use random numbers and regular expressions.
  • Learn about more complex topics like networking, XML processing, and multiprocessing.
  • Learn to build GUIs with Python.
  • Find out about exceptions and how to handle them.
  • Learn to use SciPy, NumPy, and Pandas.
  • Learn to debug, unit-test, log, serialize, and access the database.

2. Things to master Python

a. Frameworks

You should now learn to work on a framework.

Python has some very powerful frameworks like Django, Flask, and CherryPy.

You can begin with Django, which is a very powerful framework following the DRY (Don’t Repeat Yourself) principle.

It makes work easier for you and takes care of trivial things.

b. ORM Libraries

ORM stands for Object Relational Mapping.

This is a way to query and manipulate data from a database using an object-oriented paradigm.

You can learn to use ORM libraries like SQLAlchemy and Django ORM. This is easier and faster than writing SQL.

c. Front-End Technologies

Technologies like HTML5, CSS3, and JavaScript/jQuery are not a requirement to be a Python developer.

But if you can, try to gain a basic understanding of these, and they will let you understand how things work and what is possible.

As a Python developer, you may need to work with the front-end team.

d. Version Control

Changes to a code multiple times by multiple people can ultimately break it.

You should learn GitHub and its simple terms like push, pull, fork, and commit if you want to implement version control (you should).

3. Build Projects in Python

You now have enough skills; building some personal python projects will give you confidence.

You can also build something to try and solve an actual problem you face.

Once you feel confident enough, you can then build for popular open-source projects like Django.

4. Where to learn?

There is no scarcity of resources when it comes to learning Python. You can find millions of free resources online to learn Python. Some of them are —

  1. Python for Everybody Specialization (Coursera)
  2. Python 3 Programming (Coursera)
  3. Introduction to Python Programming (edX)
  4. CS50’s Web Programming with Python and JavaScript (edX)
  5. Learn Python 3 (Codecademy)

Stage 3 — Data Structures and Algorithms in Python

We’ll move on to the most important part of Python, Data Structures and Algorithms, after we completing the Python Basics (DSA). Any programming language’s core components are these. For both software development and coding interviews, DSA is a must-have. To master the DSA, you should learn the following topics –

  1. Arrays and Linked Lists
  2. Binary Search Trees, Recursion
  3. Python Lists
  4. Tuples, Dictionaries, Sets, and Slicing
  5. Stacks and Queues
  6. Hashing, Hash Tables, Graph Traversing
  7. Sorting algorithms, Divide and Conquer
  8. Dynamic Programming

Check out the following resources for free to learn about Python DSA —

  1. Data Structures and Algorithms in Python (Jovian.ai)
  2. Mastering Data Structures and Algorithms in Python
  3. The Complete Data Structures and Algorithms Course in Python (Udemy)
  4. Intro to Data Structures and Algorithms (Udacity)
  5. Data Structures With Python (Geeks-for-Geeks)

Stage 4 — Advanced Python

After finishing the Python DSA, we will move towards some of the advanced concepts in Python. The relevant topics here are —

  1. Object-Oriented Programming
  2. Methods
  3. Functional Programming
  4. Inheritance
  5. Dunder
  6. Classes
  7. Decorators
  8. Lambda Functions
  9. Decorators
  10. Regular Expressions

Check out the following resources for free to learn about advanced Python —

  1. The Complete Python 3 Course: Beginner to Advanced! (Udemy)
  2. Learn Python Programming Masterclass (Udemy)

Stage 5 — Modules, Packages, I/O operators, and File Handling

After completing advanced concepts, we will move towards modules, packages, and file handling in Python. The relevant topics are —

  1. Numerical Modules, Random Modules, Counter, sys modules
  2. defaultdict and OrderedDict modules
  3. Pip and PyPI packages, DateTime, calendar modules
  4. Read/Write Files in Python
  5. Rename/Copy/managing files in Python
  6. OS Modules
  7. Zipping Files and Directories

Check out the following resources for free to learn about modules, package —

Path 1 — Towards Data Science

Harvard Business Review named Data Science as One of the Hottest Fields of the 21st Century. Data Science is an interdisciplinary field that uses algorithms, math, stats to extract meaningful insights from the data. Following are the things you should consider learning if you want to start your career in Data Science —

  1. Libraries such as Matplotlib, Pandas, NumPy, Seaborn
  2. Math and Stats
  3. Data Visualization
  4. Data Manipulation, Data Analysis, and Interpretation
  5. Database Management

There is no lack of resources when it comes to learning Data Science with Python. Check out the following resources to learn about Data Science with Python for free —

  1. Applied Data Science with Python Specialization (Coursera)
  2. Data Scientist with Python (Datacamp)
  3. Python Data Science Tutorials (realpython.org)
  4. IBM Data Science Professional Certificate (Coursera)
  5. Statistics with Python Specialization (Coursera)

Path 2 — Web Development

Things to consider while learning Web Development are

  1. Frontend Developer
  2. Backend Developer
  3. HTML, CSS
  4. Django, Flask
  5. JavaScript, TypeScript
  6. Angular, React JS, Vue.js
  7. Node.js, Ruby, PHP, MySQL

Check out the following resources to learn Web Development for free —

  1. Web Design for Everybody: Basics of Web Development & Coding Specialization (Coursera)
  2. HTML, CSS, and JavaScript for Web Developers (Coursera)
  3. IBM Full Stack Cloud Developer Professional Certificate (Coursera)
  4. HTML & CSS BY (W3School)
  5. Web Development Career Path (Codecademy)

Path 3 — Towards Machine Learning and Artificial Intelligence

Machine Learning is one of the fastest-growing fields today. You should learn the following things if you are interested in starting your career in the field of ML and AI —

  1. Applied Math and Stats
  2. Machine Learning Algorithms
  3. Libraries such as sci-kit learn, TensorFlow, Keras
  4. Prediction Model
  5. Neural Networks for Deep Learning
  6. Natural Language Processing

There are tons of resources available on the internet when it comes to Machine Learning. Check out the following resources to learn ML and AI for free —

  1. Machine Learning by Stanford (Coursera)
  2. Professional Certificate in Computer Science for Artificial Intelligence By HarvardX (edX)
  3. Machine Learning Foundations: A Case Study Approach (Coursera)
  4. Deep Learning Specialization (Coursera)
  5. DeepLearning.AI TensorFlow Developer Professional Certificate (Coursera)
  6. Natural Language Processing Specialization (Coursera)

Path 4 — Web Scraping, Computer Vision, and Automation Testing

Things to consider while learning Web Scraping and Automation Testing are —

  1. Web Scraping using BeautifulSoup, Requests libraries
  2. Selenium Web Driver
  3. Selenium Grid
  4. Computer Vision using OpenCV

Check out the following resources —

  1. TensorFlow: Advanced Techniques Specialization (Coursera)
  2. Introduction to Computer Vision and Image Processing (Coursera)
  3. Introduction to Computer Vision (Udacity)
  4. Deep Learning for Computer Vision (NPTEL)
  5. Using Python to Access Web Data (Coursera)
  6. Learning Python Test Automation (Automation Panda)
  7. Selenium Web driver with Python from Scratch + Frameworks (Udemy)

Stage 5 — Personal Python Projects

Building hands-on projects with Python as a programming language will help you gain practical coding skills. Working on your projects will boost your self-confidence and will help you to understand all the programming concepts. You will be using technical knowledge to build an impressive portfolio. It is the best way to show off your coding skills to future recruiters.

You Should one month Goal for learning Python

Source

As a beginner, your first-month goal should be-

  1. Get familiar with basic concepts (variable, condition, list, loop, function)
  2. Practice 30+ coding problems
  3. Build 2 projects to apply the concepts
  4. Get familiar with at least 2 frameworks
  5. Get started with IDE, Github, hosting, services, etc

This will make you a Junior Python Developer.

Overall Plan

Week-1: Get Familiar with Python

Just be curious to see how things can be done in Python. Check as many things as possible.

  1. Day -4: Medium Coding Problems (6 hours): Reverse a string (Check palindrome), Calculate GCD, Merge two sorted Array, Number guessing game, Calculate the age, etc.
  2. Day-5: Data Structures (6 hours): Stack, Queue, Dictionary, Tuples, Tree, Linked List.
  3. Day-6: OOP (6 hours): Object, Class, Method and constructor, OOP- Inheritance
  4. Day-7: Algorithm (6 hours): Search (Linear and Binary search), Sort (Bubble sort, Selection Sort), Recursive function (factorial, Fibonacci series), Time Complexity (Linear, Quadratic, and Constant)

Week-2: Start Software Development (Build Project)

Get into software development. Try out the things together to make a real-world project.

  1. Day-1: Get Familiar with an IDE(5 hours): IDE is the playground where you will write code for largest projects. You need to be good at one IDE. I will recommend starting with VS code install Python extension or Jupyter notebook.
  2. Day -2: Github (6 hour): Explore Github, create a repository. Try out Commit, diff, and Push code. Also, learn branch, merge, and pull Requests.
  3. Day 3: First Project: Simple Calculator (4 hours): Get familiar with Tkinter. Create a simple calculator.
  4. Day 4 5, 6: Personal Project (5 hours each day): Choose one of the projects and start working on it. If you have no idea what project you can work on. Check out this list: Some good Python projects.
  5. Day-7: Hosting (5 hours): Learn Server and hosting to host your project. Create a Heroku setup and deploy the app you built.

Week-3: Get Comfortable as a Programmer

Your week 3 goal is to get the overall process of a software development process. You will not need to master all of these. But you should know some basic parts because they will impact your everyday job.

  1. Day -1: Database Basics (6 hours): Basic SQL query (Create Table, Select, Where, Update), SQL Function (Avg, Max, Count), Relation database (Normalization), Inner Join, Outer Join, etc
  2. Day-2: Use Database with Python: (5 hours): Use a database framework (SQLite or Pandas), Connect to a database, create and insert data in multiple tables, Read data from tables.
  3. Day-3: API (5 hour): How to call an API. Learn JSON, micro-service, Rest API.
  4. Day-4: Numpy (4 hours): Get Familiar with Numpy and practice first 30 Numpy exercises
  5. Day-5, 6: Portfolio Website: (5 hours each day): Learn Django, Build a portfolio website with Django. Also checkout Flask framework.
  6. Day-7: Unit test, log, debug (4 hours): Learn unit test (PyTest), how to set up and check Log, and use Breakpoints.

WeeK-4: Get Serious to Get a Job(intern)

Your goal for week four is to seriously consider getting employed. Even if you don’t want to be hired right now, simply researching the path will teach you a lot.

  1. Day-1: Resume: (5 hours): Make a resume that is only one page long. Start with a summary of your skills. Lists of projects with Github links must be included.
  2. Day-2: Portfolio Website (6 hours): Create at least two blogs. Include them on the earlier Portfolio website you created.
  3. Day -3: LinkedIn Profile(4 hours): Create a LinkedIn Profile. Put everything from your resume in your LinkedIn.
  4. Day -4: Interview Preparation(7 hours): Common interview questions can be found on Google. In a white paper, practice coding 10 interview challenges. Take a look at sites like Glassdoor, Careercup, and others to find previous interview questions.
  5. DAY -5: Networking(~ hours): Come out of your hiding place. Begin attending Meetups and Networking Events. Meet up with other programmers and recruiters.
  6. DAY -6: Just Apply (~ hours): Look up “Python Jobs” on Google, LinkedIn, and local job sites. To apply for three jobs, choose three. Make each CV unique to the position you’re applying for. Find two or three things in each job criteria that you are unfamiliar with. Spend the following three to four days learning them.
  7. Day-7: Learn Through Rejections (~ hours): Figure up two things you should have understood to get the job every time you’re refused. Spend the following four to five days mastering each of them. Every rejection will help you become a better developer in this way.

Who is a Good Python Developer?

To be a good Python developer, you will need more than just technical knowledge and the following skills:

  • A problem-solving mindset
  • Strong communication skills- You’ll need to communicate project requirements and features to your team. This will also help you write better documentation.
  • An eagerness to learn new tools and libraries
  • Knowledge of how things work internally
  • Strong technical skills

Summary

We have discussed how to become a Python Developer and who is a good Python Developer.

If you follow the above career path wisely, you are on the way to achieve success.

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