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Python Developer Roadmap

Level 0: For New Programmers

If you are new to the programming world then in the initial week, just begin with learning text editors, IDEs, computer network basics, etc.

Level 1: Basics of Python

  • Data Types: Python has a hefty variety of data types which has some different variables. It assigns a memory bytes set to every single type and for every data type-particular set of operations are permitted.
  • Typecasting: You need to convert one data type into another in Python employing the typecasting method. Various functions can be employed to transform strings into integers, numeric values, or float, into string types.
  • Operators: These are the main symbols that assist the compiler to run some particular logical or mathematical operations.
  • Conditional Statement: There reaches a point where some statement is to form in a way if some conditions are true. The conditional statement assists to run such sort of job. You will find several conditional statements such as nested if, if-elif, if, if…else, etc.
  • Loops: These are the conditional statement that is formed as long as the conditional statement come backs true. You will see 3 different types of loops in a Python programming language which are while nested loop, loop, and for a loop.
  • Functions: These functions can be described as a whole group of statements in a program that runs a particular task. It is the reusable code employed to run a solely related task.
  • Data Structure: Data structure is a concept that assists in writing dynamic programs in any program. Certainly, Python is a high-level programming language with the basics of data structure as compared to other programming languages.

Level 2: Intermediate Python

  • Classes: These are the focal point of OOP and assist well to define the object in a view of its description however it divides the object itself.
  • Objects: These in OOP is a data type made by the software developer itself. It has various properties, objects, and methods.
  • Lambda: The function which is not well described employing the basic format of function mentioning def keyword is called lambda function.
  • Inheritance: It’s the procedure of sharing the functionality within different classes. Moreover, it assists to describe a class completely based on another class.
  • Lists: Lists are just like dynamic sized arrays, declared in other languages (vector in C++ and ArrayList in Java). Lists need not be homogeneous always which makes it the most powerful tool in Python.
  • Tuple: A Tuple is a collection of Python objects separated by commas. In some ways, a tuple is similar to a list in terms of indexing, nested objects, and repetition but a tuple is immutable, unlike lists that are mutable.
  • Set: A Set is an unordered collection data type that is iterable, mutable, and has no duplicate elements. Python’s set class represents the mathematical notion of a set.
  • Dictionary: Dictionary in Python is an ordered (since Py 3.7) [unordered (Py 3.6 & prior)] collection of data values, used to store data values like a map, which, unlike other Data Types that hold only a single value as an element, Dictionary holds key:value pair. Key-value is provided in the dictionary to make it more optimized.
  • Reflection: It’s the basic ability for a specific code to be able to find out specific attributes about various objects that may be passed as basic measures to a function.

Level 3: Frameworks & Libraries

  • Django: A high-level web framework mostly used in startups and enterprises for web development. It follows the MVC pattern and you can use multiple databases such as PostgreSQL, MySQL, SQLite, and Oracle.
  • Flask: Flask is one of the easiest microframeworks to learn in Python. If you wish to develop a simple and lightweight web application then Flask is suitable for that.
  • Tkinter: Tkinter is an open-source library and it allows you to build desktop GUI applications using Python. Learning Tkinter is simple and provides a graphical interface.
  • Numpy: It is an array-processing package and provides a high-performance array object. It is widely used for scientific computing with Python and provides essential features.
  • Pandas: Pandas is also a very good open-source library that is used for data analysis. It provides high-level data structures (such as DataFrame) and a vast variety of tools for analysis. Using this library, data manipulation becomes a much easier task.
  • Tensorflow: Most popular deep learning library developed by Google. It is a computational framework used to express algorithms that involve numerous Tensor operations.
  • PyQT: PyQt is one of the most powerful cross-platform GUI libraries owned by Nokia. It combines Python programming and the Qt library. It can be used to design graphical user interfaces for a desktop application.
  • Kivy: It can be used to create desktop applications also it supports platforms like Android, iOS, Linux & Raspberry Pi.
  • Scikit-Learn: A machine learning library for Python, designed to work with numerical libraries such as SciPy & NumPy.
  • PyTorch: PyTorch is an open source machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing

Level 4 : Start developing Projects

  • Simple interest/ EMI calculator
  • Weather application
  • Simple Crawler
  • E-commerce site
  • A Web-based crawler
  • Online CV generator
  • Visualising and forecasting stocks using Dash