
Learn how to perform arithmetic operations on vectors in Python, control order with brackets, and compute division, exponentiation, quotient, and remainder for data science tasks.
In this lecture, we will learn about, what are variables, how to define a variable in python, distinguish between invalid/valid variable names, some arithmetic operations using Variables.
In this lecture, we will learn about type of data. We will also learn about different data types that exists in python. Will have a short discussion on each data type, which will be discussed in details in upcoming lectures. In this lecture, we will also learn about how to find the data type of a variable and how to change the data type.
In this lecture, we will learn about how to take an input from user, how to store it and how to use it.
We will also see about different ways of formatting the print statement.
Gather user input for name and scores in science, mathematics, English, and history, convert to numbers, and compute the overall percentage with Python formatting.
Explore boolean values, true and false, and see how relational and logical operators yield truth in conditions for data science in Python.
From python point of view, this is very important lecture.
As in this lecture, we will learn about indentation that needs to be maintained while writing loops, if else statements, functions etc.
Master Python string methods, including strip, lower, upper, replace, and split, and learn in and not in operations; handle backslashes, escape sequences, and newline or tab formatting for text processing.
Explore how to use for loops in Python to iterate ranges, lists, sets, and dictionaries, and generate sequences such as factorials with range-based patterns.
A complete guide to begin your python learning for data science, data analysis and machine learning.
For those, who has never written a single code in entire life and want to move into data science or advanced python, this course provides you a simple approach to learn coding from scratch using python as a tool and master it with illustrations and assignments.
For those, who are already experienced in coding, but want to move into advanced python, this course provides you ample hands-on exercises and assignments for deeply understanding the concept.
In this course, you will be learning from the very basics - which includes basic numbers, arithmetic operations, lists, sets, tuples, dictionaries, loops, if else statements, nested dictionaries, functions, recursive functions etc.
We will be using Jupyter notebook in order to execute all the codes. Jupyter notebook is a tool that is being used by all the multinational organisation, who hire people for analytics and machine learning jobs.
Key features:
# Learn Python from scratch - from installation to writing your first code to understand the basics and finally to reach advance level.
# No prior coding experience required.
# Command yourself in Jupyter Notebook.
# Prepare yourself for Data Analytics, Machine Learning, Python Development.
Have a great learning ahead.