🐍 Python has rapidly grown to become one of the most used language in the tech industry. Objective Of This Path ? The objective of this learning path is to share with the audience my journey, the path which I took, the resources(both free and paid) which I referred and continue to refer to this day. The course contains paid courses which offer high value and also corresponding free versions of the same topics. The advantage of paid courses is that they are updated from time to time so you always get access to the latest content. Career Paths Which Python Opens Up ? -- Backend Development -- Data Analytics -- Data Engineering -- Data Scientist -- Machine Learning & AI How Is This Path Structured ? -- Structured courses which teach everything about Python in single video -- IDE Setup for Python(PyCharm, Jupyterlab, VsCode) -- Managing virtual environments in Python using venv and miniconda -- Individual video content for important Python concepts such as Decorators, Generators, Logging, Unit Testing, OOPs -- Courses for Python Backend & Web Development covering Flask, Django & FastAPI -- Courses for Python Data Engineering & Data Analysis covering Pandas, Numpy, Matplotlib, Seaborn -- Courses for Python Data Science, Machine Learning/AI covering Pytorch, NLP and various machine learning concepts Hope my journey & it's learning benefit anyone who takes this path.

Become a Data Scientist with Google Sponsored courses. Objectives - Learn the fundamentals of Python Programming for Data Analysis - Common terminology used in Data Science - Data Science Life cycle - How to use Python in Data Science - Quickly covers Machine Learning concepts using Python - Hands-on projects using Machine Learning and Deep learning frameworks like tensorflow

- Basics of the Python programming language. - The core concepts of data science libraries in Python. - Become proficient in manipulating and visualizing data in Python. - Understand the principles of machine learning and predictive modeling. - Learn how to use Python to access public datasets and create data-driven applications. - Become familiar with the capabilities of the Python scientific stack for data analysis.

- Basics of Python - Object and Data Structures - Comparison Operators - Statements - Methods and Functions - Master Object Oriented Programming - Modules and Packages - Errors and Exceptions Handling